Vision-controlled jetting for composite systems and robots

Capacitive pressure sensors based on bioinspired structured electrode for human-machine interaction applications

Flexible pressure sensor is a crucial component of tactile sensors and plays an integral role in numerous significant fields. Despite the considerable effort put forth, how to further improve sensitivity with ingenious yet easy-to-manufacture structures and apply them to emerging fields such as structure/materials recognition, human motion monitoring, and human-machine interaction remains a challenge. Here, we develop a highly sensitive flexible capacitive pressure sensor featuring a structured electrode layer with embedded microcracks and a dielectric layer with micro-convex structures, which are combined with an iontronic interface. The sophisticated design endows the sensor with superior perceptual performance, showing a relatively linear sensitivity of 1613 kPa-1 in the range of 50 kPa and a detection limit of ∼6.7 Pa. Due to its excellent sensing capabilities, the sensors have been demonstrated for microstructure/material stiffness recognition and human motion monitoring. Furthermore, by integrating a single sensor with an inertial unit, the sensor gains the capability to output multiple sets of instructions. This work provides innovative design inspiration for flexible electronics.

In Situ Programmable, Active, and Interactive Crystallization by Localized Polymerization

Additive manufacturing has sought active and interactive means of creating predictable structures with diverse materials. Compared to such active manufacturing tools, current crystallization strategies remain in statistical and passive programs of crystals via macroscale thermodynamic controllers, commonly lacking active means to intervene in crystal growth in a spatiotemporal manner. Herein, a strategy toward active and interactive programming and reprogramming of crystals, realized by real-time tangible feedback on growing crystals by delicately controlling the degree of in-situ, localized photopolymerization of polymeric structures via additive manufacturing is presented. Using this strategy, crystals can be seeded, guided, and even reprogrammed in a supersaturated liquid resin. In principle, the localized formation of sparse polymeric networks within supercooled resins can induce density fluctuation to trigger seed nucleation instantaneously, whereas the formation of dense networks can lower molecules' mobilities to inhibit crystal growth. Assisted by these active triggers and deterministic procedural aspects in additive manufacturing, growing crystals can be tangibly interacted through programmed polymeric structures, strengthening deterministic characteristics in crystal growth. It is suggested that crystal growth can be programmable with deterministic hierarchies within the created crystal's morphologies within the background of inherent stochasticity in crystallization, launching an era of convolutional growth of crystals.

Upgrading and extending the life cycle of soft robots with in situ free-form liquid three-dimensional printing

Soft robotics hardware, with numerous applications ranging from health care to exploration of unstructured environments, suffers from limited life cycles, which lead to waste generation and poor sustainability. Soft robots combine soft or hybrid components via complex assembly and disassembly workflows, which complicate the repair of broken components, hinder upgradability, and ultimately reduce their life spans. In this work, an advanced extrusion-based additive manufacturing process, in situ free-form liquid three-dimensional printing (iFL3DP), was developed to facilitate functional upgrades and repairs in soft robots. A yield-stress hydrogel-a type of material that can maintain its shape until sufficient stress is applied-was first printed directly onto the robot surface, serving as a support for printing new components. This technique enabled the fabrication of advanced components with seamless integration onto already assembled robots. These components could combine multiple materials with intricate geometries, including overhangs and high-aspect ratio shapes, that are considerably challenging to manufacture and integrate via traditional methods such as casting. This approach was successfully applied to upgrade an existing soft robot by adding three advanced functionalities: whisker-like sensors for tactile feedback, a grasping mechanism, and a multifunctional passive whisker array. This study showcases the easy repairability of features, new and old, substantially extending the robot's life span. This workflow has potential to enhance the sustainable development of soft robots.

Voxel Interface Control in Multimaterial Extrusion 3D Printing

Interfaces are crucial in natural and engineered systems, dictating essential biological, ecological, and technological properties that augment performance, functionality, and user experience. Yet, achieving precise interfacial control poses significant challenges in both conventional and additive manufacturing, where scalability constraints impede the controlled deposition of quasi-2D layers within 3D objects. This paper introduces Voxel-Interface 3D Printing (VI3DP), which enables comprehensive control over extruded voxel interfaces irrespective of the printhead diameter that conventionally dictates feature size. Various optical, mechanical, and electrical functionalizations, attaining interface thicknesses up to three orders of magnitude smaller than the voxel size are reported. Notable applications include encoding data in soft matter through fluorescent interfaces, creating tight fits and movable mechanisms through non-adhesive interfaces, fabricating bio-inspired composites with tailored failure modes, and developing a single filament capacitive touch sensor. VI3DP opens new avenues for enhanced functionality and efficiency across multiple fields, including biomedical technology, electronics, optics, and nanotechnology.

Towards industry-ready additive manufacturing: AI-enabled closed-loop control for 3D melt electrowriting

Melt electrowriting (MEW) is an emerging high-resolution 3D printing technology used in biomedical engineering, regenerative medicine, and soft robotics. Its transition from academia to industry faces challenges such as slow experimentation, low printing throughput, poor reproducibility, and user-dependent operation, largely due to the nonlinear and multiparametric nature of the MEW process. To address these challenges, we applied computer vision and machine learning to monitor and analyze the process in real-time through imaging of the MEW jet between the nozzle-collector gap. To collect data for training we developed an automated data collection methodology that eases the experimental time from days to hours. A feedforward neural network, working in concert with optimization methods and a feedback loop, is used to develop closed-loop control ensuring reproducibility of the printed parts. We demonstrate that machine learning allows streamlining the MEW operation via closed-loop control of the highly nonlinear 3D printing technology.

Wearable and Implantable Soft Robots

Soft robotics presents innovative solutions across different scales. The flexibility and mechanical characteristics of soft robots make them particularly appealing for wearable and implantable applications. The scale and level of invasiveness required for soft robots depend on the extent of human interaction. This review provides a comprehensive overview of wearable and implantable soft robots, including applications in rehabilitation, assistance, organ simulation, surgical tools, and therapy. We discuss challenges such as the complexity of fabrication processes, the integration of responsive materials, and the need for robust control strategies, while focusing on advances in materials, actuation and sensing mechanisms, and fabrication techniques. Finally, we discuss the future outlook, highlighting key challenges and proposing potential solutions.

Neural network-enabled, all-electronic control of non-Newtonian fluid flow

Real-time, all-electronic control of non-Newtonian fluid flow through a microscale channel is crucial for various applications in manufacturing and healthcare. However, existing methods lack the sensitivity required for accurate measurement and the real-time responsiveness necessary for effective adjustment. Here, we demonstrate an all-electronic system that enables closed-loop, real-time, high-sensitivity control of various waveforms of non-Newtonian fluid flow (0.76 μl min-1) through a micro-sized outlet. Our approach combines a contactless, cuff-like flow sensor with a neural-network control program. This system offers a simple, miniaturized, versatile, yet high-performance solution for non-Newtonian fluid flow control, easily integrated into existing setups.

Simultaneous Color- and Dose-Controlled Thiol-Ene Resins for Multimodulus 3D Printing with Programmable Interfacial Gradients

Drawing inspiration from nature's own intricate designs, synthetic multimaterial structures have the potential to offer properties and functionality that exceed those of the individual components. However, several contemporary hurdles, from a lack of efficient chemistries to processing constraints, preclude the rapid and precise manufacturing of such materials. Herein, the development of a photocurable resin comprising color-selective initiators is reported, triggering disparate polymerization mechanisms between acrylate and thiol functionality. Exposure of the resin to UV light (365 nm) leads to the formation of a rigid, highly crosslinked network via a radical chain-growth mechanism, while violet light (405 nm) forms a soft, lightly crosslinked network via an anionic step-growth mechanism. The efficient photocurable resin is employed in multicolor digital light processing 3D printing to provide structures with moduli spanning over two orders of magnitude. Furthermore, local intensity (i.e., grayscale) control enables the formation of programmable stiffness gradients with ≈150× change in modulus occurring across sharp (≈200 µm) and shallow (≈9 mm) interfaces, mimetic of the human knee entheses and squid beaks, respectively. This study provides composition-processing-property relationships to inform advanced manufacturing of next-generation multimaterial objects having a myriad of applications from healthcare to education.

Soft robotic artificial left ventricle simulator capable of reproducing myocardial biomechanics

The heart's intricate myocardial architecture has been called the Gordian knot of anatomy, an impossible tangle of intricate muscle fibers. This complexity dictates equally complex cardiac motions that are difficult to mimic in physical systems. If these motions could be generated by a robotic system, then cardiac device testing, cardiovascular disease studies, and surgical procedure training could reduce their reliance on animal models, saving time, costs, and lives. This work introduces a bioinspired soft robotic left ventricle simulator capable of reproducing the minutiae of cardiac motion while providing physiological pressures. This device uses thin-filament artificial muscles to mimic the multilayered myocardial architecture. To demonstrate the device's ability to follow the cardiac motions observed in the literature, we used canine myocardial strain data as input signals that were subsequently applied to each artificial myocardial layer. The device's ability to reproduce physiological volume and pressure under healthy and heart failure conditions, as well as effective simulation of a cardiac support device, were experimentally demonstrated in a left-sided mock circulation loop. This work also has the potential to deliver faithful simulated cardiac motion for preclinical device and surgical procedure testing, with the potential to simulate patient-specific myocardial architecture and motion.

Additive Manufacturing Provides Infinite Possibilities for Self-Sensing Technology

Integrating sensors and other functional parts in one device can enable a new generation of integrated intelligent devices that can perform self-sensing and monitoring autonomously. Applications include buildings that detect and repair damage, robots that monitor conditions and perform real-time correction and reconstruction, aircraft capable of real-time perception of the internal and external environment, and medical devices and prosthetics with a realistic sense of touch. Although integrating sensors and other functional parts into self-sensing intelligent devices has become increasingly common, additive manufacturing has only been marginally explored. This review focuses on additive manufacturing integrated design, printing equipment, and printable materials and stuctures. The importance of the material, structure, and function of integrated manufacturing are highlighted. The study summarizes current challenges to be addressed and provides suggestions for future development directions.

4D bioprinting of programmed dynamic tissues

Setting time as the fourth dimension, 4D printing allows us to construct dynamic structures that can change their shape, property, or functionality over time under stimuli, leading to a wave of innovations in various fields. Recently, 4D printing of smart biomaterials, biological components, and living cells into dynamic living 3D constructs with 4D effects has led to an exciting field of 4D bioprinting. 4D bioprinting has gained increasing attention and is being applied to create programmed and dynamic cell-laden constructs such as bone, cartilage, and vasculature. This review presents an overview on 4D bioprinting for engineering dynamic tissues and organs, followed by a discussion on the approaches, bioprinting technologies, smart biomaterials and smart design, bioink requirements, and applications. While much progress has been achieved, 4D bioprinting as a complex process is facing challenges that need to be addressed by transdisciplinary strategies to unleash the full potential of this advanced biofabrication technology. Finally, we present future perspectives on the rapidly evolving field of 4D bioprinting, in view of its potential, increasingly important roles in the development of advanced dynamic tissues for basic research, pharmaceutics, and regenerative medicine.

Multimodal Soft Robotic Actuation and Locomotion

Diverse and adaptable modes of complex motion observed at different scales in living creatures are challenging to reproduce in robotic systems. Achieving dexterous movement in conventional robots can be difficult due to the many limitations of applying rigid materials. Robots based on soft materials are inherently deformable, compliant, adaptable, and adjustable, making soft robotics conducive to creating machines with complicated actuation and motion gaits. This review examines the mechanisms and modalities of actuation deformation in materials that respond to various stimuli. Then, strategies based on composite materials are considered to build toward actuators that combine multiple actuation modes for sophisticated movements. Examples across literature illustrate the development of soft actuators as free-moving, entirely soft-bodied robots with multiple locomotion gaits via careful manipulation of external stimuli. The review further highlights how the application of soft functional materials into robots with rigid components further enhances their locomotive abilities. Finally, taking advantage of the shape-morphing properties of soft materials, reconfigurable soft robots have shown the capacity for adaptive gaits that enable transition across environments with different locomotive modes for optimal efficiency. Overall, soft materials enable varied multimodal motion in actuators and robots, positioning soft robotics to make real-world applications for intricate and challenging tasks.

From nano- to macroarchitectures: designing and constructing MOF-derived porous materials for persulfate-based advanced oxidation processes

Persulfate-based advanced oxidation processes (PS-AOPs) have gained significant attention as an effective approach for the elimination of emerging organic contaminants (EOCs) in water treatment. Metal-organic frameworks (MOFs) and their derivatives are regarded as promising catalysts for activating peroxydisulfate (PDS) and peroxymonosulfate (PMS) due to their tunable and diverse structure and composition. By the rational nanoarchitectured design of MOF-derived nanomaterials, the excellent performance and customized functions can be achieved. However, the intrinsic fine powder form and agglomeration ability of MOF-derived nanomaterials have limited their practical engineering application. Recently, a great deal of effort has been put into shaping MOFs into macroscopic objects without sacrificing the performance. This review presents recent advances in the design and synthetic strategies of MOF-derived nano- and macroarchitectures for PS-AOPs to degrade EOCs. Firstly, the strategies of preparing MOF-derived diverse nanoarchitectures including hierarchically porous, hollow, yolk-shell, and multi-shell structures are comprehensively summarized. Subsequently, the approaches of manufacturing MOF-based macroarchitectures are introduced in detail. Moreover, the PS-AOP application and mechanisms of MOF-derived nano- and macromaterials as catalysts to eliminate EOCs are discussed. Finally, the prospects and challenges of MOF-derived materials in PS-AOPs are discussed. This work will hopefully guide the design and development of MOF-derived porous materials in SR-AOPs.