1
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Baltussen MG, de Jong TJ, Duez Q, Robinson WE, Huck WTS. Chemical reservoir computation in a self-organizing reaction network. Nature 2024; 631:549-555. [PMID: 38926572 PMCID: PMC11254755 DOI: 10.1038/s41586-024-07567-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 05/14/2024] [Indexed: 06/28/2024]
Abstract
Chemical reaction networks, such as those found in metabolism and signalling pathways, enable cells to process information from their environment1,2. Current approaches to molecular information processing and computation typically pursue digital computation models and require extensive molecular-level engineering3. Despite considerable advances, these approaches have not reached the level of information processing capabilities seen in living systems. Here we report on the discovery and implementation of a chemical reservoir computer based on the formose reaction4. We demonstrate how this complex, self-organizing chemical reaction network can perform several nonlinear classification tasks in parallel, predict the dynamics of other complex systems and achieve time-series forecasting. This in chemico information processing system provides proof of principle for the emergent computational capabilities of complex chemical reaction networks, paving the way for a new class of biomimetic information processing systems.
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Affiliation(s)
- Mathieu G Baltussen
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands
| | - Thijs J de Jong
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands
| | - Quentin Duez
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands
| | - William E Robinson
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands
| | - Wilhelm T S Huck
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands.
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2
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Li Y, Yu S, Qing H, Hong Y, Zhao Y, Qi F, Su H, Yin J. Reprogrammable and reconfigurable mechanical computing metastructures with stable and high-density memory. SCIENCE ADVANCES 2024; 10:eado6476. [PMID: 38924402 PMCID: PMC11204216 DOI: 10.1126/sciadv.ado6476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 05/21/2024] [Indexed: 06/28/2024]
Abstract
Mechanical computing encodes information in deformed states of mechanical systems, such as multistable structures. However, achieving stable mechanical memory in most multistable systems remains challenging and often limited to binary information. Here, we report leveraging coupling kinematic bifurcation in rigid cube-based mechanisms with elasticity to create transformable, multistable mechanical computing metastructures with stable, high-density mechanical memory. Simply stretching the planar metastructure forms a multistable corrugated platform. It allows for independent mechanical or magnetic actuation of individual bistable element, serving as pop-up voxels for display or binary units for various tasks such as information writing, erasing, reading, encryption, and mechanologic computing. Releasing the pre-stretched strain stabilizes the prescribed information, resistant to external mechanical or magnetic perturbations, whereas re-stretching enables editable mechanical memory, akin to selective zones or disk formatting for information erasure and rewriting. Moreover, the platform can be reprogrammed and transformed into a multilayer configuration to achieve high-density memory.
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Affiliation(s)
- Yanbin Li
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27606, USA
| | - Shuangyue Yu
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27606, USA
| | - Haitao Qing
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27606, USA
| | - Yaoye Hong
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27606, USA
| | - Yao Zhao
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27606, USA
| | - Fangjie Qi
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27606, USA
| | - Hao Su
- Corresponding author. (H.S.); (J.Y.)
| | - Jie Yin
- Corresponding author. (H.S.); (J.Y.)
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3
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Mei T, Zhou Y, Chen CQ. Mechanical Neural Networks with Explicit and Robust Neurons. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2310241. [PMID: 38898738 DOI: 10.1002/advs.202310241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 05/21/2024] [Indexed: 06/21/2024]
Abstract
Mechanical computing provides an information processing method to realize sensing-analyzing-actuation integrated mechanical intelligence and, when combined with neural networks, can be more efficient for data-rich cognitive tasks. The requirement of solving implicit and usually nonlinear equilibrium equations of motion in training mechanical neural networks makes computation challenging and costly. Here, an explicit mechanical neuron is developed of which the response can be directly determined without the need of solving equilibrium equations. A training method is proposed to ensure the robustness of the neuron, i.e., insensitivity to defects and perturbations. The explicitness and robustness of the neurons facilitate the assembly of various network structures. Two exemplified networks, a robust mechanical convolutional neural network and a mechanical recurrent neural network with long short-term memory capabilities for associative learning, are experimentally demonstrated. The introduction of the explicit and robust mechanical neuron streamlines the design of mechanical neural networks fulfilling robotic matter with a level of intelligence.
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Affiliation(s)
- Tie Mei
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
| | - Yuan Zhou
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
| | - Chang Qing Chen
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
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4
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Liu J, Teunisse M, Korovin G, Vermaire IR, Jin L, Bense H, van Hecke M. Controlled pathways and sequential information processing in serially coupled mechanical hysterons. Proc Natl Acad Sci U S A 2024; 121:e2308414121. [PMID: 38768343 PMCID: PMC11145188 DOI: 10.1073/pnas.2308414121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 03/21/2024] [Indexed: 05/22/2024] Open
Abstract
The complex sequential response of frustrated materials results from the interactions between material bits called hysterons. Hence, a central challenge is to understand and control these interactions, so that materials with targeted pathways and functionalities can be realized. Here, we show that hysterons in serial configurations experience geometrically controllable antiferromagnetic-like interactions. We create hysteron-based metamaterials that leverage these interactions to realize targeted pathways, including those that break the return point memory property, characteristic of independent or weakly interacting hysterons. We uncover that the complex response to sequential driving of such strongly interacting hysteron-based materials can be described by finite state machines. We realize information processing operations such as string parsing in materia, and outline a general framework to uncover and characterize the FSMs for a given physical system. Our work provides a general strategy to understand and control hysteron interactions, and opens a broad avenue toward material-based information processing.
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Affiliation(s)
- Jingran Liu
- Huygens-Kamerlingh Onnes Lab, Leiden Institute of Physics, Universiteit Leiden, NL-2300 RALeiden, The Netherlands
- Laboratory for Multiscale Mechanics and Medical Science, State Key Lab for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi’an Jiaotong University, Xi’an710049, China
| | - Margot Teunisse
- Huygens-Kamerlingh Onnes Lab, Leiden Institute of Physics, Universiteit Leiden, NL-2300 RALeiden, The Netherlands
- AMOLF, 1098 XGAmsterdam, The Netherlands
| | - George Korovin
- Huygens-Kamerlingh Onnes Lab, Leiden Institute of Physics, Universiteit Leiden, NL-2300 RALeiden, The Netherlands
| | - Ivo R. Vermaire
- Huygens-Kamerlingh Onnes Lab, Leiden Institute of Physics, Universiteit Leiden, NL-2300 RALeiden, The Netherlands
| | - Lishuai Jin
- Huygens-Kamerlingh Onnes Lab, Leiden Institute of Physics, Universiteit Leiden, NL-2300 RALeiden, The Netherlands
- AMOLF, 1098 XGAmsterdam, The Netherlands
| | - Hadrien Bense
- AMOLF, 1098 XGAmsterdam, The Netherlands
- Nonlinear Physical Chemistry Unit, Université Libre de Bruxelles, 1050Bruxelles, Belgium
| | - Martin van Hecke
- Huygens-Kamerlingh Onnes Lab, Leiden Institute of Physics, Universiteit Leiden, NL-2300 RALeiden, The Netherlands
- AMOLF, 1098 XGAmsterdam, The Netherlands
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5
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Shankar S, Scharrer LVD, Bowick MJ, Marchetti MC. Design rules for controlling active topological defects. Proc Natl Acad Sci U S A 2024; 121:e2400933121. [PMID: 38748571 PMCID: PMC11127047 DOI: 10.1073/pnas.2400933121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 04/12/2024] [Indexed: 05/27/2024] Open
Abstract
Topological defects play a central role in the physics of many materials, including magnets, superconductors, and liquid crystals. In active fluids, defects become autonomous particles that spontaneously propel from internal active stresses and drive chaotic flows stirring the fluid. The intimate connection between defect textures and active flow suggests that properties of active materials can be engineered by controlling defects, but design principles for their spatiotemporal control remain elusive. Here, we propose a symmetry-based additive strategy for using elementary activity patterns, as active topological tweezers, to create, move, and braid such defects. By combining theory and simulations, we demonstrate how, at the collective level, spatial activity gradients act like electric fields which, when strong enough, induce an inverted topological polarization of defects, akin to a negative susceptibility dielectric. We harness this feature in a dynamic setting to collectively pattern and transport interacting active defects. Our work establishes an additive framework to sculpt flows and manipulate active defects in both space and time, paving the way to design programmable active and living materials for transport, memory, and logic.
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Affiliation(s)
- Suraj Shankar
- Department of Physics, Harvard University, Cambridge, MA02138
- Department of Physics, University of Michigan, Ann Arbor, MI48109
| | - Luca V. D. Scharrer
- Department of Physics, University of California, Santa Barbara, CA93106
- Department of Physics, The University of Chicago, Chicago, IL60637
| | - Mark J. Bowick
- Department of Physics, University of California, Santa Barbara, CA93106
- Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA93106
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6
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Sirote-Katz C, Shohat D, Merrigan C, Lahini Y, Nisoli C, Shokef Y. Emergent disorder and mechanical memory in periodic metamaterials. Nat Commun 2024; 15:4008. [PMID: 38773062 PMCID: PMC11109184 DOI: 10.1038/s41467-024-47780-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 04/12/2024] [Indexed: 05/23/2024] Open
Abstract
Ordered mechanical systems typically have one or only a few stable rest configurations, and hence are not considered useful for encoding memory. Multistable and history-dependent responses usually emerge from quenched disorder, for example in amorphous solids or crumpled sheets. In contrast, due to geometric frustration, periodic magnetic systems can create their own disorder and espouse an extensive manifold of quasi-degenerate configurations. Inspired by the topological structure of frustrated artificial spin ices, we introduce an approach to design ordered, periodic mechanical metamaterials that exhibit an extensive set of spatially disordered states. While our design exploits the correspondence between frustration in magnetism and incompatibility in meta-mechanics, our mechanical systems encompass continuous degrees of freedom, and thus generalize their magnetic counterparts. We show how such systems exhibit non-Abelian and history-dependent responses, as their state can depend on the order in which external manipulations were applied. We demonstrate how this richness of the dynamics enables to recognize, from a static measurement of the final state, the sequence of operations that an extended system underwent. Thus, multistability and potential to perform computation emerge from geometric frustration in ordered mechanical lattices that create their own disorder.
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Affiliation(s)
- Chaviva Sirote-Katz
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, 69978, Israel
| | - Dor Shohat
- School of Physics and Astronomy, Tel Aviv University, Tel Aviv, 69978, Israel
| | - Carl Merrigan
- School of Mechanical Engineering, Tel Aviv University, Tel Aviv, 69978, Israel
| | - Yoav Lahini
- School of Physics and Astronomy, Tel Aviv University, Tel Aviv, 69978, Israel
- Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv, 69978, Israel
| | - Cristiano Nisoli
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
| | - Yair Shokef
- School of Mechanical Engineering, Tel Aviv University, Tel Aviv, 69978, Israel.
- Center for Physics and Chemistry of Living Systems, Tel Aviv University, Tel Aviv, 69978, Israel.
- Center for Computational Molecular and Materials Science, Tel Aviv University, Tel Aviv, 69978, Israel.
- International Institute for Sustainability with Knotted Chiral Meta Matter, Hiroshima University, Higashi-Hiroshima, Hiroshima, 739-8526, Japan.
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7
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Hatanaka D, Takeshita H, Kataoka M, Okamoto H, Tsuruta K, Yamaguchi H. Valley Pseudospin Polarized Evanescent Coupling between Microwave Ring Resonator and Waveguide in Phononic Topological Insulators. NANO LETTERS 2024; 24:5570-5577. [PMID: 38634512 DOI: 10.1021/acs.nanolett.4c00806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
A coupled ring-waveguide structure is at the core of bosonic wave-based information processing systems, enabling advanced wave manipulations such as filtering, routing, and multiplexing. However, its miniaturization is challenging due to momentum conservation issues in rings with larger curvature that induce significant backscattering and radiation leakage and hampering stable operation. Here, we address it by taking an alternative approach of using topological technology in wavelength-scale and microwave ring-waveguide coupled systems built in nanoengineered phononic crystals. Our approach, which leverages pseudospin conservation in valley topological systems, eliminates phonon backscattering and achieves directional evanescent coupling. The resultant hypersonic waves in the tiny ring exhibit robust transport and resonant circulation. Furthermore, the ring-waveguide hybridization enables critical coupling, where valley-dependent ring-waveguide interference blocks the transmission. Our findings reveal the capability of topological phenomena for managing ultrahigh-frequency phonons in nano/microscale structures and pave the way for advanced phononic circuits in classical and quantum signal processing applications.
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Affiliation(s)
- Daiki Hatanaka
- NTT Basic Research Laboratories, NTT Corporation, Atsugi, Kanagawa 243-0198, Japan
| | - Hiroaki Takeshita
- Department of Electrical and Electronic Engineering, Okayama University, Okayama 700-8530, Japan
| | - Motoki Kataoka
- Department of Electrical and Electronic Engineering, Okayama University, Okayama 700-8530, Japan
| | - Hajime Okamoto
- NTT Basic Research Laboratories, NTT Corporation, Atsugi, Kanagawa 243-0198, Japan
| | - Kenji Tsuruta
- Department of Electrical and Electronic Engineering, Okayama University, Okayama 700-8530, Japan
| | - Hiroshi Yamaguchi
- NTT Basic Research Laboratories, NTT Corporation, Atsugi, Kanagawa 243-0198, Japan
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8
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Toofani A, Eraghi SH, Basti A, Rajabi H. Complexity biomechanics: a case study of dragonfly wing design from constituting composite material to higher structural levels. Interface Focus 2024; 14:20230060. [PMID: 38618231 PMCID: PMC11008961 DOI: 10.1098/rsfs.2023.0060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 01/25/2024] [Indexed: 04/16/2024] Open
Abstract
Presenting a novel framework for sustainable and regenerative design and development is a fundamental future need. Here we argue that a new framework, referred to as complexity biomechanics, which can be used for holistic analysis and understanding of natural mechanical systems, is key to fulfilling this need. We also present a roadmap for the design and development of intelligent and complex engineering materials, mechanisms, structures, systems, and processes capable of automatic adaptation and self-organization in response to ever-changing environments. We apply complexity biomechanics to elucidate how the different structural components of a complex biological system as dragonfly wings, from ultrastructure of the cuticle, the constituting bio-composite material of the wing, to higher structural levels, collaboratively contribute to the functionality of the entire wing system. This framework not only proposes a paradigm shift in understanding and drawing inspiration from natural systems but also holds potential applications in various domains, including materials science and engineering, biomechanics, biomimetics, bionics, and engineering biology.
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Affiliation(s)
- Arman Toofani
- Mechanical Intelligence (MI) Research Group, South Bank Applied BioEngineering Research (SABER), School of Engineering, London South Bank University, London, UK
- Faculty of Mechanical Engineering, University of Guilan, Rasht, Iran
| | - Sepehr H. Eraghi
- Mechanical Intelligence (MI) Research Group, South Bank Applied BioEngineering Research (SABER), School of Engineering, London South Bank University, London, UK
- Division of Mechanical Engineering and Design, School of Engineering, London South Bank University, London, UK
| | - Ali Basti
- Faculty of Mechanical Engineering, University of Guilan, Rasht, Iran
| | - Hamed Rajabi
- Mechanical Intelligence (MI) Research Group, South Bank Applied BioEngineering Research (SABER), School of Engineering, London South Bank University, London, UK
- Division of Mechanical Engineering and Design, School of Engineering, London South Bank University, London, UK
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9
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Byun J, Pal A, Ko J, Sitti M. Integrated mechanical computing for autonomous soft machines. Nat Commun 2024; 15:2933. [PMID: 38575563 PMCID: PMC10995184 DOI: 10.1038/s41467-024-47201-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 03/25/2024] [Indexed: 04/06/2024] Open
Abstract
Mechanical computing offers a new modality to formulate computational autonomy in intelligent matter or machines without any external powering or active elements. Transition (or solitary) waves, induced by nonreciprocity in mechanical metamaterials comprising a chain of bistable elements, have proven to be a key ingredient for dissipation-free transmission and computation of mechanical information. However, advanced processing of mechanical information in existing designs is hindered by its dissipation when interacting with networked logic gates. Here, we present a metamaterial design strategy that allows non-dispersive mechanical solitary waves to compute multi-level cascaded logic functions, termed 'integrated mechanical computing', by propagating through a network of structurally heterogeneous computing units. From a perspective of characteristic potential energy, we establish an analytical framework that helps in understanding the solitary wave-based mechanical computation, and governs the mechanical design of key determinants for realizing cascaded logic computation, such as soliton profile and logic elements. The developed integrated mechanical computing systems are shown to receive, transmit and compute mechanical information to actuate intelligent soft machine prototypes in a seamless and integrated manner. These findings would pave the way for future intelligent robots and machines that perform computational operations between various non-electrical environmental inputs.
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Affiliation(s)
- Junghwan Byun
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Soft Hybrid Materials Research Center, Korea Institute of Science and Technology, 02792, Seoul, Republic of Korea
| | - Aniket Pal
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute of Applied Mechanics, University of Stuttgart, 70569, Stuttgart, Germany
| | - Jongkuk Ko
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Department of Chemical and Biological Engineering, Gachon University, Gyeonggi-do, 13120, Republic of Korea
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany.
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland.
- School of Medicine and College of Engineering, Koç University, 34450, Istanbul, Turkey.
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10
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El Helou C, Hyatt LP, Buskohl PR, Harne RL. Intelligent electroactive material systems with self-adaptive mechanical memory and sequential logic. Proc Natl Acad Sci U S A 2024; 121:e2317340121. [PMID: 38527196 PMCID: PMC10998560 DOI: 10.1073/pnas.2317340121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 02/09/2024] [Indexed: 03/27/2024] Open
Abstract
By synthesizing the requisite functionalities of intelligence in an integrated material system, it may become possible to animate otherwise inanimate matter. A significant challenge in this vision is to continually sense, process, and memorize information in a decentralized way. Here, we introduce an approach that enables all such functionalities in a soft mechanical material system. By integrating nonvolatile memory with continuous processing, we develop a sequential logic-based material design framework. Soft, conductive networks interconnect with embedded electroactive actuators to enable self-adaptive behavior that facilitates autonomous toggling and counting. The design principles are scaled in processing complexity and memory capacity to develop a model 8-bit mechanical material that can solve linear algebraic equations based on analog mechanical inputs. The resulting material system operates continually to monitor the current mechanical configuration and to autonomously search for solutions within a desired error. The methods created in this work are a foundation for future synthetic general intelligence that can empower materials to autonomously react to diverse stimuli in their environment.
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Affiliation(s)
- Charles El Helou
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA16802
| | - Lance P. Hyatt
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA16802
| | - Philip R. Buskohl
- Functional Materials Division, Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson AFB, OH45433
| | - Ryan L. Harne
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA16802
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11
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Li T, Li Y. 3D Tiled Auxetic Metamaterial: A New Family of Mechanical Metamaterial with High Resilience and Mechanical Hysteresis. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2309604. [PMID: 38183315 DOI: 10.1002/adma.202309604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 11/28/2023] [Indexed: 01/08/2024]
Abstract
For artificial materials, desired properties often conflict. For example, engineering materials often achieve high energy dissipation by sacrificing resilience and vice versa, or desired auxeticity by losing their isotropy, which limits their performance and applications. To solve these conflicts, a strategy is proposed to create novel mechanical metamaterial via 3D space filling tiles with engaging key-channel pairs, exemplified via auxetic 3D keyed-octahedron-cuboctahedron metamaterials. This metamaterial shows high resilience while achieving large mechanical hysteresis synergistically under large compressive strain. Especially, this metamaterial exhibits ideal isotropy approaching the theoretical limit of isotropic Poisson's ratio, -1, as rarely seen in existing 3D mechanical metamaterials. In addition, the new class of metamaterials provides wide tunability on mechanical properties and behaviors, including an unusual coupled auxeticity and twisting behavior under normal compression. The designing methodology is illustrated by the integral of numerical modeling, theoretical analysis, and experimental characterization. The new mechanical metamaterials have broad applications in actuators and dampers, soft robotics, biomedical materials, and engineering materials/systems for energy dissipation.
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Affiliation(s)
- Tiantian Li
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA02115, USA
| | - Yaning Li
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA02115, USA
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12
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Wu L, Lu Y, Li P, Wang Y, Xue J, Tian X, Ge S, Li X, Zhai Z, Lu J, Lu X, Li D, Jiang H. Mechanical Metamaterials for Handwritten Digits Recognition. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2308137. [PMID: 38145964 PMCID: PMC10933649 DOI: 10.1002/advs.202308137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/14/2023] [Indexed: 12/27/2023]
Abstract
The increasing needs for new types of computing lie in the requirements in harsh environments. In this study, the successful development of a non-electrical neural network is presented that functions based on mechanical computing. By overcoming the challenges of low mechanical signal transmission efficiency and intricate layout design methodologies, a mechanical neural network based on bistable kirigami-based mechanical metamaterials have designed. In preliminary tests, the system exhibits high reliability in recognizing handwritten digits and proves operable in low-temperature environments. This work paves the way for a new, alternative computing system with broad applications in areas where electricity is not accessible. By integrating with the traditional electronic computers, the present system lays the foundation for a more diversified form of computing.
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Affiliation(s)
- Lingling Wu
- State Key Laboratory for Manufacturing Systems EngineeringXi'an Jiaotong UniversityXi'an710049China
| | - Yuyang Lu
- School of EngineeringWestlake UniversityHangzhouZhejiang310030China
- Westlake Institute for Advanced StudyHangzhouZhejiang310024China
| | - Penghui Li
- School of EngineeringWestlake UniversityHangzhouZhejiang310030China
| | - Yong Wang
- School of Aeronautics and AstronauticsZhejiang UniversityHangzhouZhejiang310027China
| | - Jiacheng Xue
- State Key Laboratory for Manufacturing Systems EngineeringXi'an Jiaotong UniversityXi'an710049China
| | - Xiaoyong Tian
- State Key Laboratory for Manufacturing Systems EngineeringXi'an Jiaotong UniversityXi'an710049China
| | - Shenhao Ge
- School of EngineeringWestlake UniversityHangzhouZhejiang310030China
| | - Xiaowen Li
- School of EngineeringWestlake UniversityHangzhouZhejiang310030China
- Westlake Institute for Advanced StudyHangzhouZhejiang310024China
| | - Zirui Zhai
- School for Engineering of MatterTransport and EnergyArizona State UniversityTempeArizona85287USA
| | - Junqiang Lu
- Department of PhysicsShaoxing UniversityShaoxing312000China
| | - Xiaoli Lu
- Department of PhysicsZhejiang Normal UniversityJinhua321000China
| | - Dichen Li
- State Key Laboratory for Manufacturing Systems EngineeringXi'an Jiaotong UniversityXi'an710049China
| | - Hanqing Jiang
- School of EngineeringWestlake UniversityHangzhouZhejiang310030China
- Westlake Institute for Advanced StudyHangzhouZhejiang310024China
- Research Center for Industries of the FutureWestlake UniversityHangzhouZhejiang310030China
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13
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Jin L, Yang S. Engineering Kirigami Frameworks Toward Real-World Applications. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2308560. [PMID: 37983878 DOI: 10.1002/adma.202308560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 11/05/2023] [Indexed: 11/22/2023]
Abstract
The surge in advanced manufacturing techniques has led to a paradigm shift in the realm of material design from developing completely new chemistry to tailoring geometry within existing materials. Kirigami, evolved from a traditional cultural and artistic craft of cutting and folding, has emerged as a powerful framework that endows simple 2D sheets with unique mechanical, thermal, optical, and acoustic properties, as well as shape-shifting capabilities. Given its flexibility, versatility, and ease of fabrication, there are significant efforts in developing kirigami algorithms to create various architectured materials for a wide range of applications. This review summarizes the fundamental mechanisms that govern the transformation of kirigami structures and elucidates how these mechanisms contribute to their distinctive properties, including high stretchability and adaptability, tunable surface topography, programmable shape morphing, and characteristics of bistability and multistability. It then highlights several promising applications enabled by the unique kirigami designs and concludes with an outlook on the future challenges and perspectives of kirigami-inspired metamaterials toward real-world applications.
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Affiliation(s)
- Lishuai Jin
- Department of Materials Science and Engineering, University of Pennsylvania, 3231 Walnut Street, Philadelphia, PA, 19104, USA
| | - Shu Yang
- Department of Materials Science and Engineering, University of Pennsylvania, 3231 Walnut Street, Philadelphia, PA, 19104, USA
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14
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Oh E, Kane AQ, Truby RL. Architected Poly(ionic liquid) Composites with Spatially Programmable Mechanical Properties and Mixed Conductivity. ACS APPLIED MATERIALS & INTERFACES 2024; 16:10736-10745. [PMID: 38354100 DOI: 10.1021/acsami.3c18512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2024]
Abstract
Structural electrolytes present advantages over liquid varieties, which are critical to myriad applications. In particular, structural electrolytes based on polymerized ionic liquids or poly(ionic liquids) (pILs) provide wide electrochemical windows, high thermal stability, nonvolatility, and modular chemistry. However, current methods of fabricating structural electrolytes from pILs and their composites present limitations. Recent advances have been made in 3D printing pIL electrolytes, but current printing techniques limit the complexity of forms that can be achieved, as well as the ability to control mechanical properties or conductivity. We introduce a method for fabricating architected pIL composites as structural electrolytes via embedded 3D (EMB3D) printing. We present a modular design for formulating ionic liquid (IL) monomer composite inks that can be printed into sparse, lightweight, free-standing lattices with different functionalities. In addition to characterizing the rheological and mechanical behaviors of IL monomer inks and pIL lattices, we demonstrate the self-sensing capabilities of our printed structural electrolytes during cyclic compression. Finally, we use our inks and printing method to spatially program self-sensing capabilities in pIL lattices through heterogeneous architectures as well as ink compositions that provide mixed ionic-electronic conductivity. Our free-form approach to fabricating structural electrolytes in complex, 3D forms with programmable, anisotropic properties has broad potential use in next-generation sensors, soft robotics, bioelectronics, energy storage devices, and more.
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Affiliation(s)
- EunBi Oh
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Alexander Q Kane
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Ryan L Truby
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
- Department of Mechanical Engineering, Northwestern University, Evanston, Illinois 60208, United States
- Center for Robotics and Biosystems, Northwestern University, Evanston, Illinois 60208, United States
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15
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Czajkowski M, Rocklin DZ. Duality and Sheared Analytic Response in Mechanism-Based Metamaterials. PHYSICAL REVIEW LETTERS 2024; 132:068201. [PMID: 38394578 DOI: 10.1103/physrevlett.132.068201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 11/17/2023] [Accepted: 11/28/2023] [Indexed: 02/25/2024]
Abstract
Mechanical metamaterials designed around a zero-energy pathway of deformation known as a mechanism, challenge the conventional picture of elasticity and generate complex spatial response that remains largely uncharted. Here, we present a unified theoretical framework to showing that the presence of a unimode in a 2D structure generates a space of anomalous zero-energy sheared analytic modes. The spatial profiles of these stress-free strain patterns is dual to equilibrium stress configurations. We show a transition at an exceptional point between bulk modes in structures with conventional Poisson ratios (anauxetic) and evanescent surface modes for negative Poisson ratios (auxetic). We suggest a first application of these unusual response properties as a switchable signal amplifier and filter for use in mechanical circuitry and computation.
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Affiliation(s)
- Michael Czajkowski
- School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - D Zeb Rocklin
- School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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16
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Shklyaev OE, Balazs AC. Interlinking spatial dimensions and kinetic processes in dissipative materials to create synthetic systems with lifelike functionality. NATURE NANOTECHNOLOGY 2024; 19:146-159. [PMID: 38057363 DOI: 10.1038/s41565-023-01530-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 09/21/2023] [Indexed: 12/08/2023]
Abstract
Biological systems spontaneously convert energy input into the actions necessary to survive. Motivated by the efficacy of these processes, researchers aim to forge materials systems that exhibit the self-sustained and autonomous functionality found in nature. Success in this effort will require synthetic analogues of the following: a metabolism to generate energy, a vasculature to transport energy and materials, a nervous system to transmit 'commands', a musculoskeletal system to translate commands into physical action, regulatory networks to monitor the entire enterprise, and a mechanism to convert 'nutrients' into growing materials. Design rules must interconnect the material's structural and kinetic properties over ranges of length (that can vary from the nano- to mesoscale) and timescales to enable local energy dissipations to power global functionality. Moreover, by harnessing dynamic interactions intrinsic to the material, the system itself can perform the work needed for its own functionality. Here, we assess the advances and challenges in dissipative materials design and at the same time aim to spur developments in next-generation functional, 'living' materials.
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Affiliation(s)
- Oleg E Shklyaev
- Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Anna C Balazs
- Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
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17
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Slesarenko V, Pastewka L. The bumpy road to friction control. Science 2024; 383:150-151. [PMID: 38207043 DOI: 10.1126/science.adn1075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
The frictional properties of material interfaces can be rationally designed.
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Affiliation(s)
- Viacheslav Slesarenko
- Department of Microsystems Engineering, University of Freiburg, 79110 Freiburg, Germany
- Cluster of Excellence livMatS, Freiburg Center for Interactive Materials and Bioinspired Technologies, University of Freiburg, 79110 Freiburg, Germany
| | - Lars Pastewka
- Department of Microsystems Engineering, University of Freiburg, 79110 Freiburg, Germany
- Cluster of Excellence livMatS, Freiburg Center for Interactive Materials and Bioinspired Technologies, University of Freiburg, 79110 Freiburg, Germany
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18
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Zhang B, Xue Y, Park HS, Jiang JW. Flexible nanomechanical bit based on few-layer graphene. Phys Chem Chem Phys 2024; 26:822-829. [PMID: 38095185 DOI: 10.1039/d3cp03241h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2024]
Abstract
Mechanical computers have gained intense research interest at size scales ranging from nano to macro as they may complement electronic computers operating in extreme environments. While nanoscale mechanical computers may be easier to integrate with traditional electronic components, most current nanomechanical computers are based on volatile resonator systems that require continuous energy input. In this study, we propose a non-volatile nanomechanical bit based on the quasi-stable configurations of few-layer graphene with void defects, and demonstrate its multiple quasi-stable states by deriving an analytic relationship for the void configuration based on a competition between the bending energy and the cohesive energy. Using this nanomechanical bit, typical logic gates are constructed to perform Boolean calculations, including NOT, AND, OR, NAND and NOR gates, and demonstrate reprogrammability between these logic gates. We also study the accuracy and the stability of the nanomechanical bits based on the few-layer graphene. These findings provide a novel approach to realize the nanomechanical computing process.
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Affiliation(s)
- Bin Zhang
- Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai Institute of Applied Mathematics and Mechanics, Shanghai Frontier Science Center of Mechanoinformatics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200072, People's Republic of China.
| | - Yixuan Xue
- Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai Institute of Applied Mathematics and Mechanics, Shanghai Frontier Science Center of Mechanoinformatics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200072, People's Republic of China.
| | - Harold S Park
- Department of Mechanical Engineering, Boston University, Boston, Massachusetts 02215, USA
| | - Jin-Wu Jiang
- Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai Institute of Applied Mathematics and Mechanics, Shanghai Frontier Science Center of Mechanoinformatics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200072, People's Republic of China.
- Zhejiang Laboratory, Hangzhou 311100, China
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19
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Liao J, Majidi C, Sitti M. Liquid Metal Actuators: A Comparative Analysis of Surface Tension Controlled Actuation. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2300560. [PMID: 37358049 DOI: 10.1002/adma.202300560] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 06/09/2023] [Indexed: 06/27/2023]
Abstract
Liquid metals, with their unique combination of electrical and mechanical properties, offer great opportunities for actuation based on surface tension modulation. Thanks to the scaling laws of surface tension, which can be electrochemically controlled at low voltages, liquid metal actuators stand out from other soft actuators for their remarkable characteristics such as high contractile strain rates and higher work densities at smaller length scales. This review summarizes the principles of liquid metal actuators and discusses their performance as well as theoretical pathways toward higher performances. The objective is to provide a comparative analysis of the ongoing development of liquid metal actuators. The design principles of the liquid metal actuators are analyzed, including low-level elemental principles (kinematics and electrochemistry), mid-level structural principles (reversibility, integrity, and scalability), and high-level functionalities. A wide range of practical use cases of liquid metal actuators from robotic locomotion and object manipulation to logic and computation is reviewed. From an energy perspective, strategies are compared for coupling the liquid metal actuators with an energy source toward fully untethered robots. The review concludes by offering a roadmap of future research directions of liquid metal actuators.
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Affiliation(s)
- Jiahe Liao
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569, Stuttgart, Germany
| | - Carmel Majidi
- Robotics Institute, Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, Zürich, 8092, Switzerland
- School of Medicine, College of Engineering, Koç University, Istanbul, 34450, Turkey
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20
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Zhou X, Ren X, Xiao D, Zhang J, Huang R, Li Z, Sun X, Wu X, Qiu CW, Nori F, Jing H. Higher-order singularities in phase-tracked electromechanical oscillators. Nat Commun 2023; 14:7944. [PMID: 38040766 PMCID: PMC10692225 DOI: 10.1038/s41467-023-43708-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 11/17/2023] [Indexed: 12/03/2023] Open
Abstract
Singularities ubiquitously exist in different fields and play a pivotal role in probing the fundamental laws of physics and developing highly sensitive sensors. Nevertheless, achieving higher-order (≥3) singularities, which exhibit superior performance, typically necessitates meticulous tuning of multiple (≥3) coupled degrees of freedom or additional introduction of nonlinear potential energies. Here we propose theoretically and confirm using mechanics experiments, the existence of an unexplored cusp singularity in the phase-tracked (PhT) steady states of a pair of coherently coupled mechanical modes without the need for multiple (≥3) coupled modes or nonlinear potential energies. By manipulating the PhT singularities in an electrostatically tunable micromechanical system, we demonstrate an enhanced cubic-root response to frequency perturbations. This study introduces a new phase-tracking method for studying interacting systems and sheds new light on building and engineering advanced singular devices with simple and well-controllable elements, with potential applications in precision metrology, portable nonreciprocal devices, and on-chip mechanical computing.
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Affiliation(s)
- Xin Zhou
- College of Intelligence Science and Technology, NUDT, 410073, Changsha, China.
| | - Xingjing Ren
- College of Intelligence Science and Technology, NUDT, 410073, Changsha, China
| | - Dingbang Xiao
- College of Intelligence Science and Technology, NUDT, 410073, Changsha, China
| | - Jianqi Zhang
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences, 430071, Wuhan, China
| | - Ran Huang
- Center for Quantum Computing, Cluster for Pioneering Research, RIKEN, Wako-shi, Saitama, 351-0198, Japan
| | - Zhipeng Li
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Xiaopeng Sun
- College of Intelligence Science and Technology, NUDT, 410073, Changsha, China
| | - Xuezhong Wu
- College of Intelligence Science and Technology, NUDT, 410073, Changsha, China.
| | - Cheng-Wei Qiu
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Franco Nori
- Center for Quantum Computing, Cluster for Pioneering Research, RIKEN, Wako-shi, Saitama, 351-0198, Japan.
- Department of Physics, University of Michigan, Ann Arbor, MI, 48109-1040, USA.
| | - Hui Jing
- Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education, Department of Physics and Synergetic Innovation Center for Quantum Effects and Applications, Hunan Normal University, 410081, Changsha, China.
- Academy for Quantum Science and Technology, Zhengzhou University of Light Industry, 450002, Zhengzhou, China.
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21
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Zhang Y, Deshmukh A, Wang KW. Embodying Multifunctional Mechano-Intelligence in and Through Phononic Metastructures Harnessing Physical Reservoir Computing. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2305074. [PMID: 37870205 DOI: 10.1002/advs.202305074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/21/2023] [Indexed: 10/24/2023]
Abstract
Recent advances in autonomous systems have prompted a strong demand for the next generation of adaptive structures and materials to possess built-in intelligence in their mechanical domain, the so-called mechano-intelligence (MI). Previous MI attempts mainly focused on specific case studies and lacked a systematic foundation in effectively and efficiently constructing and integrating different intelligent functions. Here, a new approach is uncovered to create multifunctional MI in adaptive structures using physical reservoir computing (PRC). That is, to concurrently embody computing power and the key elements of intelligence, namely perception, decision-making, and commanding, directly in the mechanical domain, advancing from conventional reliance on add-on computers and massive electronics. As an exemplar platform, a mechanically intelligent phononic metastructure is developed by harnessing its high-degree-of-freedom nonlinear dynamics as PRC power. Through analyses and experiments, multiple intelligent structural functions are demonstrated ranging from self-tuning wave controls to wave-based logic gates. This research provides the much-needed basis for creating future smart structures and materials that greatly surpass the state of the art-such as lower power consumption, more direct interactions, and better survivability in harsh environments or under cyberattacks. Moreover, it enables the addition of new functions and autonomy to systems without overburdening the onboard computers.
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Affiliation(s)
- Yuning Zhang
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Aditya Deshmukh
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Kon-Well Wang
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
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22
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Zheng X, Zhang X, Chen TT, Watanabe I. Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2302530. [PMID: 37332101 DOI: 10.1002/adma.202302530] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 05/27/2023] [Indexed: 06/20/2023]
Abstract
Mechanical metamaterials are meticulously designed structures with exceptional mechanical properties determined by their microstructures and constituent materials. Tailoring their material and geometric distribution unlocks the potential to achieve unprecedented bulk properties and functions. However, current mechanical metamaterial design considerably relies on experienced designers' inspiration through trial and error, while investigating their mechanical properties and responses entails time-consuming mechanical testing or computationally expensive simulations. Nevertheless, recent advancements in deep learning have revolutionized the design process of mechanical metamaterials, enabling property prediction and geometry generation without prior knowledge. Furthermore, deep generative models can transform conventional forward design into inverse design. Many recent studies on the implementation of deep learning in mechanical metamaterials are highly specialized, and their pros and cons may not be immediately evident. This critical review provides a comprehensive overview of the capabilities of deep learning in property prediction, geometry generation, and inverse design of mechanical metamaterials. Additionally, this review highlights the potential of leveraging deep learning to create universally applicable datasets, intelligently designed metamaterials, and material intelligence. This article is expected to be valuable not only to researchers working on mechanical metamaterials but also those in the field of materials informatics.
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Affiliation(s)
- Xiaoyang Zheng
- Center for Basic Research on Materials, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, 305-0047, Japan
- Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8573, Japan
| | - Xubo Zhang
- Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8573, Japan
| | - Ta-Te Chen
- Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan
- National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, 305-0047, Japan
| | - Ikumu Watanabe
- Center for Basic Research on Materials, National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, 305-0047, Japan
- Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8573, Japan
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23
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Allein F, Anastasiadis A, Chaunsali R, Frankel I, Boechler N, Diakonos FK, Theocharis G. Strain topological metamaterials and revealing hidden topology in higher-order coordinates. Nat Commun 2023; 14:6633. [PMID: 37857621 PMCID: PMC10587163 DOI: 10.1038/s41467-023-42321-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 10/06/2023] [Indexed: 10/21/2023] Open
Abstract
Topological physics has revolutionized materials science, introducing topological phases of matter in diverse settings ranging from quantum to photonic and phononic systems. Herein, we present a family of topological systems, which we term "strain topological metamaterials", whose topological properties are hidden and unveiled only under higher-order (strain) coordinate transformations. We firstly show that the canonical mass dimer, a model that can describe various settings such as electrical circuits and optics, among others, belongs to this family where strain coordinates reveal a topological nontriviality for the edge states at free boundaries. Subsequently, we introduce a mechanical analog of the Majorana-supporting Kitaev chain, which supports topological edge states for both fixed and free boundaries within the proposed framework. Thus, our findings not only extend the way topological edge states are identified, but also promote the fabrication of novel topological metamaterials in various fields, with more complex, tailored boundaries.
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Affiliation(s)
- Florian Allein
- Univ. Lille, CNRS, Centrale Lille, Junia, Univ. Polytechnique Hauts-de-France, UMR 8520-IEMN-Institut d'Electronique de Microélectronique et de Nanotechnologie, 59000, Lille, France
| | - Adamantios Anastasiadis
- Laboratoire d'Acoustique de l'Université du Mans (LAUM), UMR 6613, Institut d'Acoustique-Graduate School (IA-GS), CNRS, Le Mans Université, Le Mans, France
| | - Rajesh Chaunsali
- Department of Aerospace Engineering, Indian Institute of Science, Bangalore, 560012, India
| | - Ian Frankel
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Nicholas Boechler
- Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | | | - Georgios Theocharis
- Laboratoire d'Acoustique de l'Université du Mans (LAUM), UMR 6613, Institut d'Acoustique-Graduate School (IA-GS), CNRS, Le Mans Université, Le Mans, France.
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24
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Dorin P, Khan M, Wang KW. Uncovering and Experimental Realization of Multimodal 3D Topological Metamaterials for Low-Frequency and Multiband Elastic Wave Control. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2304793. [PMID: 37664881 PMCID: PMC10602582 DOI: 10.1002/advs.202304793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Indexed: 09/05/2023]
Abstract
Topological mechanical metamaterials unlock confined and robust elastic wave control. Recent breakthroughs have precipitated the development of 3D topological metamaterials, which facilitate extraordinary wave manipulation along 2D planar and layer-dependent waveguides. The 3D topological metamaterials studied thus far are constrained to function in single-frequency bandwidths that are typically in a high-frequency regime, and a comprehensive experimental investigation remains elusive. In this paper, these research gaps are addressed and the state of the art is advanced through the synthesis and experimental realization of a 3D topological metamaterial that exploits multimodal local resonance to enable low-frequency elastic wave control over multiple distinct frequency bands. The proposed metamaterial is geometrically configured to create multimodal local resonators whose frequency characteristics govern the emergence of four unique low-frequency topological states. Numerical simulations uncover how these topological states can be employed to achieve polarization-, frequency-, and layer-dependent wave manipulation in 3D structures. An experimental study results in the attainment of complete wave fields that illustrate 2D topological waveguides and multi-polarized wave control in a physical testbed. The outcomes from this work provide insight that will aid future research on 3D topological mechanical metamaterials and reveal the applicability of the proposed metamaterial for wave control applications.
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Affiliation(s)
- Patrick Dorin
- Department of Mechanical EngineeringUniversity of MichiganAnn ArborMI48109USA
| | - Mustafa Khan
- Department of Mechanical EngineeringUniversity of MichiganAnn ArborMI48109USA
| | - K. W. Wang
- Department of Mechanical EngineeringUniversity of MichiganAnn ArborMI48109USA
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25
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Jiao P, Mueller J, Raney JR, Zheng XR, Alavi AH. Mechanical metamaterials and beyond. Nat Commun 2023; 14:6004. [PMID: 37752150 PMCID: PMC10522661 DOI: 10.1038/s41467-023-41679-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 09/14/2023] [Indexed: 09/28/2023] Open
Abstract
Mechanical metamaterials enable the creation of structural materials with unprecedented mechanical properties. However, thus far, research on mechanical metamaterials has focused on passive mechanical metamaterials and the tunability of their mechanical properties. Deep integration of multifunctionality, sensing, electrical actuation, information processing, and advancing data-driven designs are grand challenges in the mechanical metamaterials community that could lead to truly intelligent mechanical metamaterials. In this perspective, we provide an overview of mechanical metamaterials within and beyond their classical mechanical functionalities. We discuss various aspects of data-driven approaches for inverse design and optimization of multifunctional mechanical metamaterials. Our aim is to provide new roadmaps for design and discovery of next-generation active and responsive mechanical metamaterials that can interact with the surrounding environment and adapt to various conditions while inheriting all outstanding mechanical features of classical mechanical metamaterials. Next, we deliberate the emerging mechanical metamaterials with specific functionalities to design informative and scientific intelligent devices. We highlight open challenges ahead of mechanical metamaterial systems at the component and integration levels and their transition into the domain of application beyond their mechanical capabilities.
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Affiliation(s)
- Pengcheng Jiao
- Ocean College, Zhejiang University, Zhoushan, Zhejiang, China
| | - Jochen Mueller
- Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jordan R Raney
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA, USA
| | - Xiaoyu Rayne Zheng
- Department of Materials Science and Engineering, University of California, Berkeley, CA, USA
| | - Amir H Alavi
- Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
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26
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Tholen HM, Ambulo CP, Lee KM, Buskohl PR, Harne RL. Optomechanical computing in liquid crystal elastomers. SOFT MATTER 2023; 19:6978-6986. [PMID: 37665593 DOI: 10.1039/d3sm00819c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Embodied decision-making in soft, engineered matter has sparked recent interest towards the development of intelligent materials. Such decision-making capabilities can be realized in soft materials via digital information processing with combinational logic operations. Although previous research has explored soft material actuators and embedded logic in soft materials, achieving a high degree of autonomy in these material systems remains a challenge. Light is an ideal stimulus to trigger information processing in soft materials due to its low thermal effect and remote use. Thus, one approach for developing soft, autonomous materials is to integrate optomechanical computing capabilities in photoresponsive materials. Here, we establish a methodology to embed combinational logic circuitry in a photoresponsive liquid crystal elastomer (LCE) film. These LCEs are designed with embedded switches and integrated circuitry using liquid metal-based conductive traces. The resulting optomechanical computing LCEs can effectively process optical information via light, thermal, and mechanical energy conversion. The methods introduced in this work to fabricate a material capable of optical information processing can facilitate the implementation of a sense of sight in soft robotic systems and other compliant devices.
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Affiliation(s)
- Haley M Tholen
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, USA.
| | - Cedric P Ambulo
- Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, OH, USA
- Azimuth Corporation, Fairborn, OH, USA
| | - Kyung Min Lee
- Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, OH, USA
- Azimuth Corporation, Fairborn, OH, USA
| | - Philip R Buskohl
- Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, OH, USA
| | - Ryan L Harne
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, USA.
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27
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Vafa F, Mahadevan L. Statics and diffusive dynamics of surfaces driven by p-atic topological defects. SOFT MATTER 2023; 19:6652-6663. [PMID: 37641854 DOI: 10.1039/d3sm00257h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Inspired by epithelial morphogenesis, we consider a minimal model for the shaping of a surface driven by p-atic topological defects. We show that a positive (negative) defect can dynamically generate a (hyperbolic) cone whose shape evolves diffusively, and predict that a defect of charge + 1/p leads to a final semi-cone angle β which satisfies the inequality . By exploiting the fact that for axisymmetric surfaces, the extrinsic geometry is tightly coupled to the intrinsic geometry, we further show that the resulting stationary shape of a membrane with negligible bending modulus and embedded polar order is a deformed lemon with two defects at antipodal points. Finally, we close by pointing out that our results may be relevant beyond epithelial morphogenesis in such contexts as shape transitions in macroscopic closed spheroidal surfaces such as pollen grains.
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Affiliation(s)
- Farzan Vafa
- Center of Mathematical Sciences and Applications, Harvard University, Cambridge, MA 02138, USA.
| | - L Mahadevan
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
- Departments of Physics, and Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
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28
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Zhong Y, Tang W, Xu H, Qin K, Yan D, Fan X, Qu Y, Li Z, Jiao Z, Yang H, Zou J. Phase-transforming mechanical metamaterials with dynamically controllable shape-locking performance. Natl Sci Rev 2023; 10:nwad192. [PMID: 37565196 PMCID: PMC10411672 DOI: 10.1093/nsr/nwad192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 06/24/2023] [Accepted: 06/30/2023] [Indexed: 08/12/2023] Open
Abstract
Active mechanical metamaterials with customizable structures and deformations, active reversible deformation, dynamically controllable shape-locking performance and stretchability are highly suitable for applications in soft robotics and flexible electronics, yet it is challenging to integrate them due to their mutual conflicts. Here, we introduce a class of phase-transforming mechanical metamaterials (PMMs) that integrate the above properties. Periodically arranging basic actuating units according to the designed pattern configuration and positional relationship, PMMs can customize complex and diverse structures and deformations. Liquid-vapor phase transformation provides active reversible large deformation while a silicone matrix offers stretchability. The contained carbonyl iron powder endows PMMs with dynamically controllable shape-locking performance, thereby achieving magnetically assisted shape locking and energy storing in different working modes. We build a theoretical model and finite element simulation to guide the design process of PMMs, so as to develop a variety of PMMs with different functions suitable for different applications, such as a programmed PMM, reconfigurable antenna, soft lens, soft mechanical memory, biomimetic hand, biomimetic flytrap and self-contained soft gripper. PMMs are applicable to achieve various 2D deformations and 2D-to-3D deformations, and integrate multiple properties, including customizable structures and deformations, active reversible deformation, rapid reversible shape locking, adjustable energy storing and stretchability, which could open a new application avenue in soft robotics and flexible electronics.
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Affiliation(s)
- Yiding Zhong
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Wei Tang
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
- Institute of Process Equipment, College of Energy Engineering, Zhejiang University, Hangzhou 310027, China
| | - Huxiu Xu
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Kecheng Qin
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Dong Yan
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Xujun Fan
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Yang Qu
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Zhaoyang Li
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Zhongdong Jiao
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Huayong Yang
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Jun Zou
- State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
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29
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Abstract
Mechanical computing requires matter to adapt behavior according to retained knowledge, often through integrated sensing, actuation, and control of deformation. However, inefficient access to mechanical memory and signal propagation limit mechanical computing modules. To overcome this, we developed an in-memory mechanical computing architecture where computing occurs within the interaction network of mechanical memory units. Interactions embedded within data read-write interfaces provided function-complete and neuromorphic computing while reducing data traffic and simplifying data exchange. A reprogrammable mechanical binary neural network and a mechanical self-learning perceptron were demonstrated experimentally in 3D printed mechanical computers, as were all 16 logic gates and truth-table entries that are possible with two inputs and one output. The in-memory mechanical computing architecture enables the design and fabrication of intelligent mechanical systems.
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Affiliation(s)
- Tie Mei
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, PR China
| | - Chang Qing Chen
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, PR China.
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30
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He Q, Yin R, Hua Y, Jiao W, Mo C, Shu H, Raney JR. A modular strategy for distributed, embodied control of electronics-free soft robots. SCIENCE ADVANCES 2023; 9:eade9247. [PMID: 37418520 DOI: 10.1126/sciadv.ade9247] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 06/02/2023] [Indexed: 07/09/2023]
Abstract
Robots typically interact with their environments via feedback loops consisting of electronic sensors, microcontrollers, and actuators, which can be bulky and complex. Researchers have sought new strategies for achieving autonomous sensing and control in next-generation soft robots. We describe here an electronics-free approach for autonomous control of soft robots, whose compositional and structural features embody the sensing, control, and actuation feedback loop of their soft bodies. Specifically, we design multiple modular control units that are regulated by responsive materials such as liquid crystal elastomers. These modules enable the robot to sense and respond to different external stimuli (light, heat, and solvents), causing autonomous changes to the robot's trajectory. By combining multiple types of control modules, complex responses can be achieved, such as logical evaluations that require multiple events to occur in the environment before an action is performed. This framework for embodied control offers a new strategy toward autonomous soft robots that operate in uncertain or dynamic environments.
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Affiliation(s)
- Qiguang He
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rui Yin
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yucong Hua
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Weijian Jiao
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chengyang Mo
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hang Shu
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jordan R Raney
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
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31
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Harrellson SG, DeLay MS, Chen X, Cavusoglu AH, Dworkin J, Stone HA, Sahin O. Hydration solids. Nature 2023; 619:500-505. [PMID: 37286609 PMCID: PMC10530534 DOI: 10.1038/s41586-023-06144-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Accepted: 04/27/2023] [Indexed: 06/09/2023]
Abstract
Hygroscopic biological matter in plants, fungi and bacteria make up a large fraction of Earth's biomass1. Although metabolically inert, these water-responsive materials exchange water with the environment and actuate movement2-5 and have inspired technological uses6,7. Despite the variety in chemical composition, hygroscopic biological materials across multiple kingdoms of life exhibit similar mechanical behaviours including changes in size and stiffness with relative humidity8-13. Here we report atomic force microscopy measurements on the hygroscopic spores14,15 of a common soil bacterium and develop a theory that captures the observed equilibrium, non-equilibrium and water-responsive mechanical behaviours, finding that these are controlled by the hydration force16-18. Our theory based on the hydration force explains an extreme slowdown of water transport and successfully predicts a strong nonlinear elasticity and a transition in mechanical properties that differs from glassy and poroelastic behaviours. These results indicate that water not only endows biological matter with fluidity but also can-through the hydration force-control macroscopic properties and give rise to a 'hydration solid' with unusual properties. A large fraction of biological matter could belong to this distinct class of solid matter.
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Affiliation(s)
| | - Michael S DeLay
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Xi Chen
- Department of Biological Sciences, Columbia University, New York, NY, USA
- Advanced Science Research Center (ASRC) at the Graduate Center of the City University of New York, New York, NY, USA
| | - Ahmet-Hamdi Cavusoglu
- Department of Chemical Engineering, Columbia University, New York, NY, USA
- Merck Digital Sciences Studio (MDSS), Newark, NJ, USA
| | - Jonathan Dworkin
- Department of Microbiology and Immunology, Columbia University, New York, NY, USA
| | - Howard A Stone
- Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, USA
| | - Ozgur Sahin
- Department of Physics, Columbia University, New York, NY, USA.
- Department of Biological Sciences, Columbia University, New York, NY, USA.
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32
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Kwakernaak LJ, van Hecke M. Counting and Sequential Information Processing in Mechanical Metamaterials. PHYSICAL REVIEW LETTERS 2023; 130:268204. [PMID: 37450791 DOI: 10.1103/physrevlett.130.268204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/30/2023] [Indexed: 07/18/2023]
Abstract
Materials with an irreversible response to cyclic driving exhibit an evolving internal state which, in principle, encodes information on the driving history. Here we realize irreversible metamaterials that count mechanical driving cycles and store the result into easily interpretable internal states. We extend these designs to aperiodic metamaterials that are sensitive to the order of different driving magnitudes, and realize "lock and key" metamaterials that only reach a specific state for a given target driving sequence. Our metamaterials are robust, scalable, and extendable, give insight into the transient memories of complex media, and open new routes towards smart sensing, soft robotics, and mechanical information processing.
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Affiliation(s)
- Lennard J Kwakernaak
- Huygens-Kamerlingh Onnes Laboratory, Universiteit Leiden, PO Box 9504, 2300 RA Leiden, Netherlands and AMOLF, Science Park 104, 1098 XG Amsterdam, Netherlands
| | - Martin van Hecke
- Huygens-Kamerlingh Onnes Laboratory, Universiteit Leiden, PO Box 9504, 2300 RA Leiden, Netherlands and AMOLF, Science Park 104, 1098 XG Amsterdam, Netherlands
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33
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Guo X, Guzmán M, Carpentier D, Bartolo D, Coulais C. Non-orientable order and non-commutative response in frustrated metamaterials. Nature 2023; 618:506-512. [PMID: 37316720 DOI: 10.1038/s41586-023-06022-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 03/27/2023] [Indexed: 06/16/2023]
Abstract
From atomic crystals to animal flocks, the emergence of order in nature is captured by the concept of spontaneous symmetry breaking1-4. However, this cornerstone of physics is challenged when broken symmetry phases are frustrated by geometrical constraints. Such frustration dictates the behaviour of systems as diverse as spin ices5-8, confined colloidal suspensions9 and crumpled paper sheets10. These systems typically exhibit strongly degenerated and heterogeneous ground states and hence escape the Ginzburg-Landau paradigm of phase ordering. Here, combining experiments, simulations and theory we uncover an unanticipated form of topological order in globally frustrated matter: non-orientable order. We demonstrate this concept by designing globally frustrated metamaterials that spontaneously break a discrete [Formula: see text] symmetry. We observe that their equilibria are necessarily heteregeneous and extensively degenerated. We explain our observations by generalizing the theory of elasticity to non-orientable order-parameter bundles. We show that non-orientable equilibria are extensively degenerated due to the arbitrary location of topologically protected nodes and lines where the order parameter must vanish. We further show that non-orientable order applies more broadly to objects that are non-orientable themselves, such as buckled Möbius strips and Klein bottles. Finally, by applying time-dependent local perturbations to metamaterials with non-orientable order, we engineer topologically protected mechanical memories11-19, achieve non-commutative responses and show that they carry an imprint of the braiding of the loads' trajectories. Beyond mechanics, we envision non-orientability as a robust design principle for metamaterials that can effectively store information across scales, in fields as diverse as colloidal science8, photonics20, magnetism7 and atomic physics21.
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Affiliation(s)
- Xiaofei Guo
- Institute of Physics, Universiteit van Amsterdam, Amsterdam, the Netherlands.
- Harbin Institute of Technology, Harbin, China.
| | - Marcelo Guzmán
- Univ. Lyon, ENS de Lyon, Univ. Claude Bernard, CNRS, Laboratoire de Physique, Lyon, France
| | - David Carpentier
- Univ. Lyon, ENS de Lyon, Univ. Claude Bernard, CNRS, Laboratoire de Physique, Lyon, France.
| | - Denis Bartolo
- Univ. Lyon, ENS de Lyon, Univ. Claude Bernard, CNRS, Laboratoire de Physique, Lyon, France.
| | - Corentin Coulais
- Institute of Physics, Universiteit van Amsterdam, Amsterdam, the Netherlands.
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34
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Wang X, Meng Z, Chen CQ. Robotic Materials Transformable Between Elasticity and Plasticity. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2206637. [PMID: 36793150 PMCID: PMC10161124 DOI: 10.1002/advs.202206637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 01/12/2023] [Indexed: 05/06/2023]
Abstract
Robotic materials, with coupled sensing, actuation, computation, and communication, have attracted increasing attention because they are able to not only tune their conventional passive mechanical property via geometrical transformation or material phase change but also become adaptive and even intelligent to suit varying environments. However, the mechanical behavior of most robotic materials is either reversible (elastic) or irreversible (plastic), but not transformable between them. Here, a robotic material whose behavior is transformable between elastic and plastic is developed, based upon an extended neutrally stable tensegrity structure. The transformation does not depend on conventional phase transition and is fast. By integrating with sensors, the elasticity-plasticity transformable (EPT) material is able to self-sense deformation and decides whether to undergo transformation or not. This work expands the capability of the mechanical property modulation of robotic materials.
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Affiliation(s)
- Xinyuan Wang
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
| | - Zhiqiang Meng
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
| | - Chang Qing Chen
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
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35
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Meng Z, Yan H, Liu M, Qin W, Genin GM, Chen CQ. Encoding and Storage of Information in Mechanical Metamaterials. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2301581. [PMID: 37083263 PMCID: PMC10369242 DOI: 10.1002/advs.202301581] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 03/29/2023] [Indexed: 05/03/2023]
Abstract
Information processing using material's own properties has gained increasing interest. Mechanical metamaterials, due to their diversity of deformation modes and wide design space, can be used to realize information processing, such as computing and storage. Here a mechanical metamaterial system is demonstrated for material-based encoding and storage of data through programmed reconfigurations of the metamaterial's structured building blocks. Sequential encoding and decoding are achieved in the three-dimensional (3D) printed pixelated mechanical metamaterial via kirigami-based "pixels" with programmable, temperature-dependent bistability. The mechanical metamaterial is demonstrated via a multistep deformation of encoding messages of texts and surfaces with arrays of binary data, and then decoding them by applying a predetermined stretching and heating regimen to sequentially retrieve layers of stored information and display them on its surface. This approach serves as a general framework to enable the encoding and storage of data with mechanical metamaterials.
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Affiliation(s)
- Zhiqiang Meng
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
| | - Hujie Yan
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
| | - Mingchao Liu
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Republic of Singapore
| | - Wenkai Qin
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
| | - Guy M Genin
- Mechanical Engineering and Materials Science, Washington University, St. Louis, MO 63130, USA
- NSF Science and Technology Center for Engineering Mechanobiology, St. Louis, MO 63130, USA
| | - Chang Qing Chen
- Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, 100084, P. R. China
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36
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Zou X, Yaqoob U, Ahmed S, Wang Y, Salama KN, Fariborzi H. An interconnect-free micro-electromechanical 7-bit arithmetic device for multi-operand programmable computing. MICROSYSTEMS & NANOENGINEERING 2023; 9:42. [PMID: 37025566 PMCID: PMC10070399 DOI: 10.1038/s41378-023-00508-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 01/06/2023] [Accepted: 01/31/2023] [Indexed: 06/19/2023]
Abstract
Computational power density and interconnection between transistors have grown to be the dominant challenges for the continued scaling of complementary metal-oxide-semiconductor (CMOS) technology due to limited integration density and computing power. Herein, we designed a novel, hardware-efficient, interconnect-free microelectromechanical 7:3 compressor using three microbeam resonators. Each resonator is configured with seven equal-weighted inputs and multiple driven frequencies, thus defining the transformation rules for transmitting resonance frequency to binary outputs, performing summation operations, and displaying outputs in compact binary format. The device achieves low power consumption and excellent switching reliability even after 3 × 103 repeated cycles. These performance improvements, including enhanced computational power capacity and hardware efficiency, are paramount for moderately downscaling devices. Finally, our proposed paradigm shift for circuit design provides an attractive alternative to traditional electronic digital computing and paves the way for multioperand programmable computing based on electromechanical systems.
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Affiliation(s)
- Xuecui Zou
- CEMSE Division, King Abdullah University of Science and Technology, Thuwal, 23955 Saudi Arabia
| | - Usman Yaqoob
- CEMSE Division, King Abdullah University of Science and Technology, Thuwal, 23955 Saudi Arabia
| | - Sally Ahmed
- CEMSE Division, King Abdullah University of Science and Technology, Thuwal, 23955 Saudi Arabia
| | - Yue Wang
- CEMSE Division, King Abdullah University of Science and Technology, Thuwal, 23955 Saudi Arabia
| | - Khaled Nabil Salama
- CEMSE Division, King Abdullah University of Science and Technology, Thuwal, 23955 Saudi Arabia
| | - Hossein Fariborzi
- CEMSE Division, King Abdullah University of Science and Technology, Thuwal, 23955 Saudi Arabia
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37
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Yan W, Li S, Deguchi M, Zheng Z, Rus D, Mehta A. Origami-based integration of robots that sense, decide, and respond. Nat Commun 2023; 14:1553. [PMID: 37012246 PMCID: PMC10070436 DOI: 10.1038/s41467-023-37158-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 03/03/2023] [Indexed: 04/05/2023] Open
Abstract
Origami-inspired engineering has enabled intelligent materials and structures to process and react to environmental stimuli. However, it is challenging to achieve complete sense-decide-act loops in origami materials for autonomous interaction with environments, mainly due to the lack of information processing units that can interface with sensing and actuation. Here, we introduce an integrated origami-based process to create autonomous robots by embedding sensing, computing, and actuating in compliant, conductive materials. By combining flexible bistable mechanisms and conductive thermal artificial muscles, we realize origami multiplexed switches and configure them to generate digital logic gates, memory bits, and thus integrated autonomous origami robots. We demonstrate with a flytrap-inspired robot that captures 'living prey', an untethered crawler that avoids obstacles, and a wheeled vehicle that locomotes with reprogrammable trajectories. Our method provides routes to achieve autonomy for origami robots through tight functional integration in compliant, conductive materials.
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Affiliation(s)
- Wenzhong Yan
- Mechanical and Aerospace Engineering Department, UCLA, Los Angeles, CA, USA.
| | - Shuguang Li
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA
- Department of Mechanical Engineering, Tsinghua University, Beijing, P.R. China
| | - Mauricio Deguchi
- Mechanical and Aerospace Engineering Department, UCLA, Los Angeles, CA, USA
| | - Zhaoliang Zheng
- Electrical and Computer Engineering Department, UCLA, Los Angeles, CA, USA
| | - Daniela Rus
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, USA
| | - Ankur Mehta
- Electrical and Computer Engineering Department, UCLA, Los Angeles, CA, USA
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38
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Luo Y, Abidian MR, Ahn JH, Akinwande D, Andrews AM, Antonietti M, Bao Z, Berggren M, Berkey CA, Bettinger CJ, Chen J, Chen P, Cheng W, Cheng X, Choi SJ, Chortos A, Dagdeviren C, Dauskardt RH, Di CA, Dickey MD, Duan X, Facchetti A, Fan Z, Fang Y, Feng J, Feng X, Gao H, Gao W, Gong X, Guo CF, Guo X, Hartel MC, He Z, Ho JS, Hu Y, Huang Q, Huang Y, Huo F, Hussain MM, Javey A, Jeong U, Jiang C, Jiang X, Kang J, Karnaushenko D, Khademhosseini A, Kim DH, Kim ID, Kireev D, Kong L, Lee C, Lee NE, Lee PS, Lee TW, Li F, Li J, Liang C, Lim CT, Lin Y, Lipomi DJ, Liu J, Liu K, Liu N, Liu R, Liu Y, Liu Y, Liu Z, Liu Z, Loh XJ, Lu N, Lv Z, Magdassi S, Malliaras GG, Matsuhisa N, Nathan A, Niu S, Pan J, Pang C, Pei Q, Peng H, Qi D, Ren H, Rogers JA, Rowe A, Schmidt OG, Sekitani T, Seo DG, Shen G, Sheng X, Shi Q, Someya T, Song Y, Stavrinidou E, Su M, Sun X, Takei K, Tao XM, Tee BCK, Thean AVY, Trung TQ, Wan C, Wang H, Wang J, Wang M, Wang S, Wang T, Wang ZL, Weiss PS, Wen H, Xu S, Xu T, Yan H, Yan X, Yang H, Yang L, Yang S, Yin L, Yu C, Yu G, Yu J, Yu SH, Yu X, Zamburg E, Zhang H, Zhang X, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhao S, Zhao X, Zheng Y, Zheng YQ, Zheng Z, Zhou T, Zhu B, Zhu M, Zhu R, Zhu Y, Zhu Y, Zou G, Chen X. Technology Roadmap for Flexible Sensors. ACS NANO 2023; 17:5211-5295. [PMID: 36892156 PMCID: PMC11223676 DOI: 10.1021/acsnano.2c12606] [Citation(s) in RCA: 194] [Impact Index Per Article: 194.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.
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Affiliation(s)
- Yifei Luo
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
- Innovative Centre for Flexible Devices (iFLEX), School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Mohammad Reza Abidian
- Department of Biomedical Engineering, University of Houston, Houston, Texas 77024, United States
| | - Jong-Hyun Ahn
- School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Deji Akinwande
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Microelectronics Research Center, The University of Texas at Austin, Austin, Texas 78758, United States
| | - Anne M Andrews
- Department of Chemistry and Biochemistry, California NanoSystems Institute, and Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, and Hatos Center for Neuropharmacology, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Markus Antonietti
- Colloid Chemistry Department, Max Planck Institute of Colloids and Interfaces, 14476 Potsdam, Germany
| | - Zhenan Bao
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Magnus Berggren
- Laboratory of Organic Electronics, Department of Science and Technology, Campus Norrköping, Linköping University, 83 Linköping, Sweden
- Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC), SE-100 44 Stockholm, Sweden
| | - Christopher A Berkey
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94301, United States
| | - Christopher John Bettinger
- Department of Biomedical Engineering and Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
| | - Jun Chen
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Peng Chen
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637457, Singapore
| | - Wenlong Cheng
- Nanobionics Group, Department of Chemical and Biological Engineering, Monash University, Clayton, Australia, 3800
- Monash Institute of Medical Engineering, Monash University, Clayton, Australia3800
| | - Xu Cheng
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, PR China
| | - Seon-Jin Choi
- Division of Materials of Science and Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Alex Chortos
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47906, United States
| | - Canan Dagdeviren
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Reinhold H Dauskardt
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94301, United States
| | - Chong-An Di
- Beijing National Laboratory for Molecular Sciences, CAS Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Michael D Dickey
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27606, United States
| | - Xiangfeng Duan
- Department of Chemistry and Biochemistry, California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Antonio Facchetti
- Department of Chemistry and the Materials Research Center, Northwestern University, Evanston, Illinois 60208, United States
| | - Zhiyong Fan
- Department of Electronic and Computer Engineering and Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China
| | - Yin Fang
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637457, Singapore
| | - Jianyou Feng
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, PR China
| | - Xue Feng
- Laboratory of Flexible Electronics Technology, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China
| | - Huajian Gao
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Republic of Singapore
| | - Wei Gao
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, California, 91125, United States
| | - Xiwen Gong
- Department of Chemical Engineering, Department of Materials Science and Engineering, Department of Electrical Engineering and Computer Science, Applied Physics Program, and Macromolecular Science and Engineering Program, University of Michigan, Ann Arbor, Michigan, 48109 United States
| | - Chuan Fei Guo
- Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xiaojun Guo
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Martin C Hartel
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Zihan He
- Beijing National Laboratory for Molecular Sciences, CAS Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - John S Ho
- Institute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- The N.1 Institute for Health, National University of Singapore, Singapore 117456, Singapore
| | - Youfan Hu
- School of Electronics and Center for Carbon-Based Electronics, Peking University, Beijing 100871, China
| | - Qiyao Huang
- School of Fashion and Textiles, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
| | - Yu Huang
- Department of Materials Science and Engineering, California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Fengwei Huo
- Key Laboratory of Flexible Electronics (KLOFE) and Institute of Advanced Materials (IAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211816, PR China
| | - Muhammad M Hussain
- mmh Labs, Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47906, United States
| | - Ali Javey
- Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720, United States
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Unyong Jeong
- Department of Materials Science and Engineering, Pohang University of Science and Engineering (POSTECH), Pohang, Gyeong-buk 37673, Korea
| | - Chen Jiang
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
| | - Xingyu Jiang
- Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Xili, Nanshan District, Shenzhen, Guangdong 518055, PR China
| | - Jiheong Kang
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Daniil Karnaushenko
- Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, Chemnitz 09126, Germany
| | | | - Dae-Hyeong Kim
- Center for Nanoparticle Research, Institute for Basic Science (IBS), School of Chemical and Biological Engineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Il-Doo Kim
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Dmitry Kireev
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Microelectronics Research Center, The University of Texas at Austin, Austin, Texas 78758, United States
| | - Lingxuan Kong
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637457, Singapore
| | - Chengkuo Lee
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore 117608, Singapore
- National University of Singapore Suzhou Research Institute (NUSRI), Suzhou Industrial Park, Suzhou 215123, China
- NUS Graduate School-Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore 119077, Singapore
| | - Nae-Eung Lee
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, Kyunggi-do 16419, Republic of Korea
| | - Pooi See Lee
- School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
- Singapore-HUJ Alliance for Research and Enterprise (SHARE), Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Tae-Woo Lee
- Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea
- School of Chemical and Biological Engineering, Seoul National University, Seoul 08826, Republic of Korea
- Institute of Engineering Research, Research Institute of Advanced Materials, Seoul National University, Soft Foundry, Seoul 08826, Republic of Korea
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Fengyu Li
- College of Chemistry and Materials Science, Jinan University, Guangzhou, Guangdong 510632, China
| | - Jinxing Li
- Department of Biomedical Engineering, Department of Electrical and Computer Engineering, Neuroscience Program, BioMolecular Science Program, and Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48823, United States
| | - Cuiyuan Liang
- School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Chwee Teck Lim
- Department of Biomedical Engineering, National University of Singapore, Singapore 117583, Singapore
- Mechanobiology Institute, National University of Singapore, Singapore 117411, Singapore
- Institute for Health Innovation and Technology, National University of Singapore, Singapore 119276, Singapore
| | - Yuanjing Lin
- School of Microelectronics, Southern University of Science and Technology, Shenzhen 518055, China
| | - Darren J Lipomi
- Department of Nano and Chemical Engineering, University of California, San Diego, La Jolla, California 92093-0448, United States
| | - Jia Liu
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, Massachusetts, 02134, United States
| | - Kai Liu
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Nan Liu
- Beijing Key Laboratory of Energy Conversion and Storage Materials, College of Chemistry, Beijing Normal University, Beijing 100875, PR China
| | - Ren Liu
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, Massachusetts, 02134, United States
| | - Yuxin Liu
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
- Department of Biomedical Engineering, N.1 Institute for Health, Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore 119077, Singapore
| | - Yuxuan Liu
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Zhiyuan Liu
- Neural Engineering Centre, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China 518055
| | - Zhuangjian Liu
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Republic of Singapore
| | - Xian Jun Loh
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
| | - Nanshu Lu
- Department of Aerospace Engineering and Engineering Mechanics, Department of Electrical and Computer Engineering, Department of Mechanical Engineering, Department of Biomedical Engineering, Texas Materials Institute, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Zhisheng Lv
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
| | - Shlomo Magdassi
- Institute of Chemistry and the Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - George G Malliaras
- Electrical Engineering Division, Department of Engineering, University of Cambridge CB3 0FA, Cambridge United Kingdom
| | - Naoji Matsuhisa
- Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
| | - Arokia Nathan
- Darwin College, University of Cambridge, Cambridge CB3 9EU, United Kingdom
| | - Simiao Niu
- Department of Biomedical Engineering, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Jieming Pan
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
| | - Changhyun Pang
- School of Chemical Engineering and Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Qibing Pei
- Department of Materials Science and Engineering, Department of Mechanical and Aerospace Engineering, California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Huisheng Peng
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, PR China
| | - Dianpeng Qi
- School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Huaying Ren
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California, 90095, United States
| | - John A Rogers
- Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, Illinois 60208, United States
- Department of Materials Science and Engineering, Department of Mechanical Engineering, Department of Biomedical Engineering, Departments of Electrical and Computer Engineering and Chemistry, and Department of Neurological Surgery, Northwestern University, Evanston, Illinois 60208, United States
| | - Aaron Rowe
- Becton, Dickinson and Company, 1268 N. Lakeview Avenue, Anaheim, California 92807, United States
- Ready, Set, Food! 15821 Ventura Blvd #450, Encino, California 91436, United States
| | - Oliver G Schmidt
- Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, Chemnitz 09126, Germany
- Material Systems for Nanoelectronics, Chemnitz University of Technology, Chemnitz 09107, Germany
- Nanophysics, Faculty of Physics, TU Dresden, Dresden 01062, Germany
| | - Tsuyoshi Sekitani
- The Institute of Scientific and Industrial Research (SANKEN), Osaka University, Osaka, Japan 5670047
| | - Dae-Gyo Seo
- Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Guozhen Shen
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
| | - Xing Sheng
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Institute for Precision Medicine, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China
| | - Qiongfeng Shi
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore 117608, Singapore
- National University of Singapore Suzhou Research Institute (NUSRI), Suzhou Industrial Park, Suzhou 215123, China
| | - Takao Someya
- Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan
| | - Yanlin Song
- Key Laboratory of Green Printing, Institute of Chemistry, Chinese Academy of Sciences, Beijing, Beijing 100190, China
| | - Eleni Stavrinidou
- Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, SE-601 74 Norrkoping, Sweden
| | - Meng Su
- Key Laboratory of Green Printing, Institute of Chemistry, Chinese Academy of Sciences, Beijing, Beijing 100190, China
| | - Xuemei Sun
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, PR China
| | - Kuniharu Takei
- Department of Physics and Electronics, Osaka Metropolitan University, Sakai, Osaka 599-8531, Japan
| | - Xiao-Ming Tao
- Research Institute for Intelligent Wearable Systems, School of Fashion and Textiles, Hong Kong Polytechnic University, Hong Kong, China
| | - Benjamin C K Tee
- Materials Science and Engineering, National University of Singapore, Singapore 117575, Singapore
- iHealthtech, National University of Singapore, Singapore 119276, Singapore
| | - Aaron Voon-Yew Thean
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Singapore Hybrid-Integrated Next-Generation μ-Electronics Centre (SHINE), Singapore 117583, Singapore
| | - Tran Quang Trung
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, Kyunggi-do 16419, Republic of Korea
| | - Changjin Wan
- School of Electronic Science and Engineering, Nanjing University, Nanjing 210023, China
| | - Huiliang Wang
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas 78712, United States
| | - Joseph Wang
- Department of Nanoengineering, University of California, San Diego, California 92093, United States
| | - Ming Wang
- Frontier Institute of Chip and System, State Key Laboratory of Integrated Chip and Systems, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, China
- the Shanghai Qi Zhi Institute, 41th Floor, AI Tower, No.701 Yunjin Road, Xuhui District, Shanghai 200232, China
| | - Sihong Wang
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois, 60637, United States
| | - Ting Wang
- State Key Laboratory of Organic Electronics and Information Displays and Jiangsu Key Laboratory for Biosensors, Institute of Advanced Materials (IAM), Nanjing University of Posts and Telecommunications, 9 Wenyuan Road, Nanjing 210023, China
| | - Zhong Lin Wang
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 100083, China
- Georgia Institute of Technology, Atlanta, Georgia 30332-0245, United States
| | - Paul S Weiss
- California NanoSystems Institute, Department of Chemistry and Biochemistry, Department of Bioengineering, and Department of Materials Science and Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Hanqi Wen
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637457, Singapore
- Institute of Flexible Electronics Technology of THU, Jiaxing, Zhejiang, China 314000
| | - Sheng Xu
- Department of Nanoengineering, Department of Electrical and Computer Engineering, Materials Science and Engineering Program, and Department of Bioengineering, University of California San Diego, La Jolla, California, 92093, United States
| | - Tailin Xu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, 518060, PR China
| | - Hongping Yan
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Xuzhou Yan
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Hui Yang
- Tianjin Key Laboratory of Molecular Optoelectronic Sciences, Department of Chemistry, School of Science, Tianjin University, Tianjin, China, 300072
| | - Le Yang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
- Department of Materials Science and Engineering, National University of Singapore (NUS), 9 Engineering Drive 1, #03-09 EA, Singapore 117575, Singapore
| | - Shuaijian Yang
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, United Kingdom
| | - Lan Yin
- School of Materials Science and Engineering, The Key Laboratory of Advanced Materials of Ministry of Education, State Key Laboratory of New Ceramics and Fine Processing, and Center for Flexible Electronics Technology, Tsinghua University, Beijing, 100084, China
| | - Cunjiang Yu
- Department of Engineering Science and Mechanics, Department of Biomedical Engineering, Department of Material Science and Engineering, Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania, 16802, United States
| | - Guihua Yu
- Materials Science and Engineering Program and Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas, 78712, United States
| | - Jing Yu
- School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Shu-Hong Yu
- Department of Chemistry, Institute of Biomimetic Materials and Chemistry, Hefei National Research Center for Physical Science at the Microscale, University of Science and Technology of China, Hefei 230026, China
| | - Xinge Yu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Evgeny Zamburg
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Singapore Hybrid-Integrated Next-Generation μ-Electronics Centre (SHINE), Singapore 117583, Singapore
| | - Haixia Zhang
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication; Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing 100871, China
| | - Xiangyu Zhang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Singapore Hybrid-Integrated Next-Generation μ-Electronics Centre (SHINE), Singapore 117583, Singapore
| | - Xiaosheng Zhang
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xueji Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, PR China
| | - Yihui Zhang
- Applied Mechanics Laboratory, Department of Engineering Mechanics; Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, PR China
| | - Yu Zhang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Singapore Hybrid-Integrated Next-Generation μ-Electronics Centre (SHINE), Singapore 117583, Singapore
| | - Siyuan Zhao
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, Massachusetts, 02134, United States
| | - Xuanhe Zhao
- Department of Mechanical Engineering, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, United States
| | - Yuanjin Zheng
- Center for Integrated Circuits and Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Yu-Qing Zheng
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication; School of Integrated Circuits, Peking University, Beijing 100871, China
| | - Zijian Zheng
- Department of Applied Biology and Chemical Technology, Faculty of Science, Research Institute for Intelligent Wearable Systems, Research Institute for Smart Energy, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
| | - Tao Zhou
- Center for Neural Engineering, Department of Engineering Science and Mechanics, The Huck Institutes of the Life Sciences, Materials Research Institute, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Bowen Zhu
- Key Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province, School of Engineering, Westlake University, Hangzhou 310024, China
| | - Ming Zhu
- Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore
| | - Rong Zhu
- Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Yangzhi Zhu
- Terasaki Institute for Biomedical Innovation, Los Angeles, California, 90064, United States
| | - Yong Zhu
- Department of Mechanical and Aerospace Engineering, Department of Materials Science and Engineering, and Department of Biomedical Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Guijin Zou
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Republic of Singapore
| | - Xiaodong Chen
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
- Innovative Center for Flexible Devices (iFLEX), Max Planck-NTU Joint Laboratory for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
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Tyburec M, Zeman J. Bounded Wang tilings with integer programming and graph-based heuristics. Sci Rep 2023; 13:4865. [PMID: 36964189 PMCID: PMC10039085 DOI: 10.1038/s41598-023-31786-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 03/17/2023] [Indexed: 03/26/2023] Open
Abstract
Wang tiles enable efficient pattern compression while avoiding the periodicity in tile distribution via programmable matching rules. However, most research in Wang tilings has considered tiling the infinite plane. Motivated by emerging applications in materials engineering, we consider the bounded version of the tiling problem and offer four integer programming formulations to construct valid or nearly-valid Wang tilings: a decision, maximum-rectangular tiling, maximum cover, and maximum adjacency constraint satisfaction formulations. To facilitate a finer control over the resulting tilings, we extend these programs with tile-based, color-based, packing, and variable-sized periodic constraints. Furthermore, we introduce an efficient heuristic algorithm for the maximum-cover variant based on the shortest path search in directed acyclic graphs and derive simple modifications to provide a 1/2 approximation guarantee for arbitrary tile sets, and a 2/3 guarantee for tile sets with cyclic transducers. Finally, we benchmark the performance of the integer programming formulations and of the heuristic algorithms showing that the heuristics provide very competitive outputs in a fraction of time. As a by-product, we reveal errors in two well-known aperiodic tile sets: the Knuth tile set contains a tile unusable in two-way infinite tilings, and the Lagae corner tile set is not aperiodic.
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Affiliation(s)
- Marek Tyburec
- Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Thákurova 7, 16000, Prague 6, Czech Republic.
- Department of Decision-Making Theory, Institute of Information Theory and Automation, Czech Academy of Sciences, Pod Vodárenskou věží 4, 18200, Prague 8, Czech Republic.
| | - Jan Zeman
- Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Thákurova 7, 16000, Prague 6, Czech Republic
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Bongard J, Levin M. There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines. Biomimetics (Basel) 2023; 8:biomimetics8010110. [PMID: 36975340 PMCID: PMC10046700 DOI: 10.3390/biomimetics8010110] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 02/24/2023] [Accepted: 03/01/2023] [Indexed: 03/18/2023] Open
Abstract
The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing”—the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.
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Affiliation(s)
- Joshua Bongard
- Department of Computer Science, University of Vermont, Burlington, VT 05405, USA
| | - Michael Levin
- Allen Discovery Center at Tufts University, 200 Boston Ave., Suite 4600, Medford, MA 02155, USA
- Correspondence: ; Tel.: +(617)-627-6161
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41
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Pashine N, Nasab AM, Kramer-Bottiglio R. Reprogrammable allosteric metamaterials from disordered networks. SOFT MATTER 2023; 19:1617-1623. [PMID: 36752560 DOI: 10.1039/d2sm01284g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Prior works on disordered mechanical metamaterial networks-consisting of fixed nodes connected by discrete bonds-have shown that auxetic and allosteric responses can be achieved by pruning a specific set of the bonds from an originally random network. However, bond pruning is irreversible and yields a single bulk response. Using material stiffness as a tunable design parameter, we create metamaterial networks where allosteric responses are achieved without bond removal. Such systems are experimentally realized through variable stiffness bonds that can strengthen and weaken on-demand. In a disordered mechanical network with variable stiffness bonds, different subsets of bonds can be strategically softened to achieve different bulk responses, enabling a multiplicity of reprogrammable input/output allosteric responses.
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Affiliation(s)
- Nidhi Pashine
- School of Engineering & Applied Science, Yale University, New Haven, CT, 06520, USA.
| | - Amir Mohammadi Nasab
- School of Engineering & Applied Science, Yale University, New Haven, CT, 06520, USA.
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42
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Zhao Y, Hong Y, Qi F, Chi Y, Su H, Yin J. Self-Sustained Snapping Drives Autonomous Dancing and Motion in Free-Standing Wavy Rings. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2207372. [PMID: 36366927 DOI: 10.1002/adma.202207372] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 10/30/2022] [Indexed: 06/16/2023]
Abstract
Harnessing snapping, an instability phenomenon observed in nature (e.g., Venus flytraps), for autonomy has attracted growing interest in autonomous soft robots. However, achieving self-sustained snapping and snapping-driven autonomous motions in soft robots remains largely unexplored. Here, harnessing bistable, ribbon ring-like structures for realizing self-sustained snapping in a library of soft liquid-crystal elastomer wavy rings under constant thermal and photothermal actuation are reported. The self-sustained snapping induces continuous ring flipping that drives autonomous dancing or crawling motions on the ground and underwater. The 3D, free-standing wavy rings employ either a highly symmetric or symmetry-broken twisted shape with tunable geometric asymmetries. It is found that the former favors periodic self-dancing motion in place due to isotropic friction, while the latter shows a directional crawling motion along the predefined axis of symmetry during fabrication due to asymmetric friction. It shows that the crawling speed can be tuned by the geometric asymmetries with a peak speed achieved at the highest geometric asymmetry. Lastly, it is shown that the autonomous crawling ring can also adapt its body shape to pass through a confined space that is over 30% narrower than its body size.
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Affiliation(s)
- Yao Zhao
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA
| | - Yaoye Hong
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA
| | - Fangjie Qi
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA
| | - Yinding Chi
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA
| | - Hao Su
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA
| | - Jie Yin
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA
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43
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Seet I, Ouldridge TE, Doye JPK. Simulation of reversible molecular mechanical logic gates and circuits. Phys Rev E 2023; 107:024134. [PMID: 36932514 DOI: 10.1103/physreve.107.024134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 10/21/2022] [Indexed: 06/18/2023]
Abstract
Landauer's principle places a fundamental lower limit on the work required to perform a logically irreversible operation. Logically reversible gates provide a way to avoid these work costs and also simplify the task of making the computation as a whole thermodynamically reversible. The inherent reversibility of mechanical logic gates would make them good candidates for the design of practical logically reversible computing systems if not for the relatively large size and mass of such systems. In this paper we outline the design and simulation of reversible molecular mechanical logic gates that come close to the limits of thermodynamic reversibility even under the effects of thermal noise, and outline associated circuit components from which arbitrary combinatorial reversible circuits can be constructed and simulated. We demonstrate that isolated components can be operated in a thermodynamically reversible manner, and explore the complexities of combining components to implement more complex computations. Finally, we demonstrate a method to construct arbitrarily large reversible combinatorial circuits using multiple external controls and signal boosters with a working half-adder circuit.
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Affiliation(s)
- Ian Seet
- Physical and Theoretical Chemistry Laboratory, Department of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, United Kingdom
| | - Thomas E Ouldridge
- Department of Bioengineering, Imperial College London, Royal School of Mines, Exhibition Road, London SW7 2AZ, United Kingdom
| | - Jonathan P K Doye
- Physical and Theoretical Chemistry Laboratory, Department of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, United Kingdom
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Cai G, Xu F, Chen B, Li X, Huang J, Mi S. Variable-position centrifugal platform achieves droplet manipulation and logic circuitries on-chip. LAB ON A CHIP 2023; 23:349-361. [PMID: 36606538 DOI: 10.1039/d2lc00761d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Taking information as material to realize non-electronic physical computing is a promising idea, which facilitates the integration of technologies in different fields such as chemistry, biology, and mechanical control into a new computing platform. Here, we propose a novel, efficient and robust manipulation platform that drives droplet computing by way of inertial force. Combining this with droplet flow path design, we demonstrated multiple basic functions of droplet manipulation, including storage, dosing, interrupts, controllable release and addressing. These basic functions without external control lay the foundation for the realization of droplet calculation. We developed AND, OR, and XOR logic gates of the "liquid circuit" and combined them into a binary adder, which successfully completed the addition of four-digit binary numbers through droplet movement. Moreover, we attempted to perform algorithmic design for biological information under the control of droplets based on synchronous logical operations, developing the possibility of biological applications. This programmable physical computing system exists independently of electronic computing, aiming to supplement and expand the computing methods outside the field of electronic technology and to open a new method for the algorithmic operation of materials after combining new physical computing technologies such as biological or chemical computing.
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Affiliation(s)
- Gangpei Cai
- Bio-manufacturing Engineering Laboratory, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China
| | - Fei Xu
- Bio-manufacturing Engineering Laboratory, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China
| | - Bailiang Chen
- Bio-manufacturing Engineering Laboratory, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China
| | - Xiang Li
- Bio-manufacturing Engineering Laboratory, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China
| | - Jiajun Huang
- Bio-manufacturing Engineering Laboratory, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China
- Research Institute of Tsinghua University in Shenzhen, Nanshan District, Shenzhen, China
| | - Shengli Mi
- Bio-manufacturing Engineering Laboratory, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China
- Research Institute of Tsinghua University in Shenzhen, Nanshan District, Shenzhen, China
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45
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Tauber FJ, Slesarenko V. Early career scientists converse on the future of soft robotics. Front Robot AI 2023; 10:1129827. [PMID: 36909362 PMCID: PMC9994530 DOI: 10.3389/frobt.2023.1129827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/09/2023] [Indexed: 02/24/2023] Open
Abstract
During the recent decade, we have witnessed an extraordinary flourishing of soft robotics. Rekindled interest in soft robots is partially associated with the advances in manufacturing techniques that enable the fabrication of sophisticated multi-material robotic bodies with dimensions ranging across multiple length scales. In recent manuscripts, a reader might find peculiar-looking soft robots capable of grasping, walking, or swimming. However, the growth in publication numbers does not always reflect the real progress in the field since many manuscripts employ very similar ideas and just tweak soft body geometries. Therefore, we unreservedly agree with the sentiment that future research must move beyond "soft for soft's sake." Soft robotics is an undoubtedly fascinating field, but it requires a critical assessment of the limitations and challenges, enabling us to spotlight the areas and directions where soft robots will have the best leverage over their traditional counterparts. In this perspective paper, we discuss the current state of robotic research related to such important aspects as energy autonomy, electronic-free logic, and sustainability. The goal is to critically look at perspectives of soft robotics from two opposite points of view provided by early career researchers and highlight the most promising future direction, that is, in our opinion, the employment of soft robotic technologies for soft bio-inspired artificial organs.
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Affiliation(s)
- Falk J Tauber
- Cluster of Excellence livMatS, FIT-Freiburg Center for Interactive Materials and Bioinspired Technologies, University of Freiburg, Freiburg im Breisgau, Germany.,Plant Biomechanics Group (PBG) Freiburg, Botanic Garden of the University of Freiburg, Freiburg im Breisgau, Germany
| | - Viacheslav Slesarenko
- Cluster of Excellence livMatS, FIT-Freiburg Center for Interactive Materials and Bioinspired Technologies, University of Freiburg, Freiburg im Breisgau, Germany
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Mofatteh H, Shahryari B, Mirabolghasemi A, Seyedkanani A, Shirzadkhani R, Desharnais G, Akbarzadeh A. Programming Multistable Metamaterials to Discover Latent Functionalities. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2202883. [PMID: 36253119 PMCID: PMC9685460 DOI: 10.1002/advs.202202883] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/25/2022] [Indexed: 05/15/2023]
Abstract
Using multistable mechanical metamaterials to develop deployable structures, electrical devices, and mechanical memories raises two unanswered questions. First, can mechanical instability be programmed to design sensors and memory devices? Second, how can mechanical properties be tuned at the post-fabrication stage via external stimuli? Answering these questions requires a thorough understanding of the snapping sequences and variations of the elastic energy in multistable metamaterials. The mechanics of deformation sequences and continuous force/energy-displacement curves are comprehensively unveiled here. A 1D array, that is chain, of bistable cells is studied to explore instability-induced energy release and snapping sequences under one external mechanical stimulus. This method offers an insight into the programmability of multistable chains, which is exploited to fabricate a mechanical sensor/memory with sampling (analog to digital-A/D) and data reconstruction (digital to analog-D/A) functionalities operating based on the correlation between the deformation sequence and the mechanical input. The findings offer a new paradigm for developing programmable high-capacity read-write mechanical memories regardless of thei size scale. Furthermore, exotic mechanical properties can be tuned by harnessing the attained programmability of multistable chains. In this respect, a transversely multistable mechanical metamaterial with tensegrity-like bistable cells is designed to showcase the tunability of chirality.
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Affiliation(s)
- Hossein Mofatteh
- Department of Bioresource EngineeringMcGill UniversityMontrealQCH9X 3V9Canada
| | - Benyamin Shahryari
- Department of Bioresource EngineeringMcGill UniversityMontrealQCH9X 3V9Canada
| | | | - Alireza Seyedkanani
- Department of Bioresource EngineeringMcGill UniversityMontrealQCH9X 3V9Canada
| | - Razieh Shirzadkhani
- Department of Bioresource EngineeringMcGill UniversityMontrealQCH9X 3V9Canada
| | | | - Abdolhamid Akbarzadeh
- Department of Bioresource EngineeringMcGill UniversityMontrealQCH9X 3V9Canada
- Department of Mechanical EngineeringMcGill UniversityMontrealQCH3A 0C3Canada
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Liu K, Pratapa PP, Misseroni D, Tachi T, Paulino GH. Triclinic Metamaterials by Tristable Origami with Reprogrammable Frustration. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2107998. [PMID: 35790039 DOI: 10.1002/adma.202107998] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 06/22/2022] [Indexed: 06/15/2023]
Abstract
Geometrical-frustration-induced anisotropy and inhomogeneity are explored to achieve unique properties of metamaterials that set them apart from conventional materials. According to Neumann's principle, to achieve anisotropic responses, the material unit cell should possess less symmetry. Based on such guidelines, a triclinic metamaterial system of minimal symmetry is presented, which originates from a Trimorph origami pattern with a simple and insightful geometry: a basic unit cell with four tilted panels and four corresponding creases. The intrinsic geometry of the Trimorph origami, with its changing tilting angles, dictates a folding motion that varies the primitive vectors of the unit cell, couples the shear and normal strains of its extrinsic bulk, and leads to an unusual Poisson effect. Such an effect, associated with reversible auxeticity in the changing triclinic frame, is observed experimentally, and predicted theoretically by elegant mathematical formulae. The nonlinearities of the folding motions allow the unit cell to display three robust stable states, connected through snapping instabilities. When the tristable unit cells are tessellated, phenomena that resemble linear and point defects emerge as a result of geometric frustration. The frustration is reprogrammable into distinct stable and inhomogeneous states by arbitrarily selecting the location of a single or multiple point defects. The Trimorph origami demonstrates the possibility of creating origami metamaterials with symmetries that are hitherto nonexistent, leading to triclinic metamaterials with tunable anisotropy for potential applications such as wave propagation control and compliant microrobots.
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Affiliation(s)
- Ke Liu
- Department of Advanced Manufacturing and Robotics, Peking University, Beijing, 100871, China
| | - Phanisri P Pratapa
- Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, TN, 600036, India
| | - Diego Misseroni
- Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, 38123, Italy
| | - Tomohiro Tachi
- Graduate School of Arts and Sciences, University of Tokyo, Tokyo, 153-8902, Japan
| | - Glaucio H Paulino
- Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, 08544, USA
- Princeton Institute for the Science and Technology of Materials (PRISM), Princeton University, Princeton, NJ, 08544, USA
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48
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Berry M, Kim Y, Limberg D, Hayward RC, Santangelo CD. Mechanical signaling cascades. Phys Rev E 2022; 106:044212. [PMID: 36397529 DOI: 10.1103/physreve.106.044212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 08/08/2022] [Indexed: 06/16/2023]
Abstract
Mechanical computing has seen resurgent interest recently owing to the potential to embed sensing and computation into new classes of programmable metamaterials. To realize this, however, one must push signals from one part of a device to another and do so in a way that can be reset robustly. We investigate the propagation of signals in a bistable mechanical cascade uphill in energy. By identifying a penetration length for perturbations, we show that signals can propagate uphill for finite distances and map out parameters for this to occur. Experiments on soft elastomers corroborate our results.
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Affiliation(s)
- Michelle Berry
- Department of Physics, Syracuse University, Syracuse, New York 13244, USA
| | - Yongjae Kim
- Department of Polymer Science and Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - David Limberg
- Department of Polymer Science and Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - Ryan C Hayward
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, Colorado 80303, USA
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Abstract
Textiles hold great promise as a soft yet durable material for building comfortable robotic wearables and assistive devices at low cost. Nevertheless, the development of smart wearables composed entirely of textiles has been hindered by the lack of a viable sheet-based logic architecture that can be implemented using conventional fabric materials and textile manufacturing processes. Here, we develop a fully textile platform for embedding pneumatic digital logic in wearable devices. Our logic-enabled textiles support combinational and sequential logic functions, onboard memory storage, user interaction, and direct interfacing with pneumatic actuators. In addition, they are designed to be lightweight, easily integrable into regular clothing, made using scalable fabrication techniques, and durable enough to withstand everyday use. We demonstrate a textile computer capable of input-driven digital logic for controlling untethered wearable robots that assist users with functional limitations. Our logic platform will facilitate the emergence of future wearables powered by embedded fluidic logic that fully leverage the innate advantages of their textile construction.
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50
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Kos Ž, Dunkel J. Nematic bits and universal logic gates. SCIENCE ADVANCES 2022; 8:eabp8371. [PMID: 35984880 PMCID: PMC9390992 DOI: 10.1126/sciadv.abp8371] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 07/05/2022] [Indexed: 05/25/2023]
Abstract
Liquid crystals (LCs) can host robust topological defect structures that essentially determine their optical and elastic properties. Although recent experimental progress enables precise control over nematic LC defects, their practical potential for information storage and processing has yet to be explored. Here, we introduce the concept of nematic bits (nbits) by exploiting a quaternionic mapping from LC defects to the Poincaré-Bloch sphere. Through theory and simulations, we demonstrate how single-nbit operations can be implemented using electric fields, to construct LC analogs of Pauli, Hadamard, and other elementary logic gates. Using nematoelastic interactions, we show how four-nbit configurations can realize universal classical NOR and NAND gates. Last, we demonstrate the implementation of generalized logical functions that take values on the Poincaré-Bloch sphere. These results open a route toward the implementation of classical digital and nonclassical continuous computation strategies in topological soft matter systems.
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Affiliation(s)
- Žiga Kos
- Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
- Faculty of Mathematics and Physics, University of Ljubljana, Jadranska 19, 1000 Ljubljana, Slovenia
- Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
| | - Jörn Dunkel
- Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
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