In situ phase engineering during additive manufacturing enables high-performance soft-magnetic medium-entropy alloys

Additive manufacturing (AM) shows promise as a method for producing soft-magnetic multicomponent alloys for use in electric motors and sustainable electromobility applications. However, the simultaneous achievement of a high saturation magnetic flux density (Bs) and a low coercivity (Hc) in AM soft-magnetic materials remains challenging. Herein, we present an approach that integrates an elemental powder mixture of Fe45Co30Ni25 with Fe2O3 nano-oxides, which is then subjected to laser powder bed fusion (LPBF) followed by high-temperature annealing to achieve an FCC-structured Fe45Co30Ni25 MEA/FeO composite. The FeO nanoparticles, a byproduct of the reaction between Fe powders and Fe2O3 nano-oxides, serve as nucleation sites for the formation of a single FCC phase in the MEA matrix. The resulting LPBF MEA/FeO composite has a Bs of 2.05 T and an exceedingly low Hc of 115 A m-1, compared to those of the BCC/FCC dual phase MEA and other state-of-the-art additively manufactured soft-magnetic alloys. In situ Lorentz transmission electron microscope (TEM) revealed that the low Hc of the FCC-structured MEA/FeO composite originates from the reduced pinning effect of grain boundaries in the FCC phase on domain wall movement compared with those in the FCC/BCC dual phase.

OCTOPUS: operation control system for task optimization and job parallelization via a user-optimal scheduler

The material acceleration platform, empowered by robotics and artificial intelligence, is a transformative approach for expediting material discovery processes across diverse domains. However, the development of an operating system for material acceleration platform faces challenges in simultaneously managing diverse experiments from multiple users. Specifically, when it is utilized by multiple users, the overlapping challenges of experimental modules or devices can lead to inefficiencies in both resource utilization and safety hazards. To overcome these challenges, we present an operation control system for material acceleration platform, namely, OCTOPUS, which is an acronym for operation control system for task optimization and job parallelization via a user-optimal scheduler. OCTOPUS streamlines experiment scheduling and optimizes resource utilization through integrating its interface node, master node and module nodes. Leveraging process modularization and a network protocol, OCTOPUS ensures the homogeneity, scalability, safety and versatility of the platform. In addition, OCTOPUS embodies a user-optimal scheduler. Job parallelization and task optimization techniques mitigate delays and safety hazards within realistic operational environments, while the closed-packing schedule algorithm efficiently executes multiple jobs with minimal resource waste. Copilot of OCTOPUS is developed to promote the reusability of OCTOPUS for potential users with their own sets of lab resources, which substantially simplifies the process of code generation and customization through GPT recommendations and client feedback. This work offers a solution to the challenges encountered within the platform accessed by multiple users, and thereby will facilitate its widespread adoption in material development processes.

Evolutionary optimisation of pixelated IFA inspired antennas

As wireless communication systems increasingly require compact and efficient antennas, conventional antenna design methods are proving difficult to meet the rigorous demands of modern applications. For this purpose, this study introduces a methodology which uses pixelated Inverted-F Antenna (IFA) inspired designs optimised through genetic algorithms to enhance performance in constrained spatial environments. As pixels the antenna features the exemplary use of Einstein Hat-shaped tiles, enabling the antenna to efficiently utilize space. A with the proposed method optimised antenna is compared to traditional IFA designs and shows improved properties like enhanced antenna gain and efficiency as well as smaller reflection coefficient offering a promising solution for future compact antenna systems in the Internet of Things and beyond. Finally, a prototype was manufactured and the scattering parameters and antenna gain were measured within an anechoic chamber.

Ultraflat Cu(111) foils by surface acoustic wave-assisted annealing

Ultraflat metal foils are essential for semiconductor nanoelectronics applications and nanomaterial epitaxial growth. Numerous efforts have been devoted to metal surface engineering studies in the past decades. However, various challenges persist, including size limitations, polishing non-uniformities, and undesired contaminants. Thus, further exploration of advanced metal surface treatment techniques is essential. Here, we report a physical strategy that utilizes surface acoustic wave assisted annealing to flatten metal foils by eliminating the surface steps, eventually transforming commercial rough metal foils into ultraflat substrates. Large-area, high-quality, smooth 2D materials, including graphene and hexagonal boron nitride (hBN), were successfully grown on the resulting flat metal substrates. Further investigation into the oxidation of 2D-material-coated metal foils, both rough and flat, revealed that the hBN-coated flat metal foil exhibits enhanced anti-corrosion properties. Molecular dynamics simulations and density functional theory validate our experimental observations.

Designer bright and fast CsPbBr3 perovskite nanocrystal scintillators for high-speed X-ray imaging

Bright and fast scintillators are highly crucial for high-speed X-ray imaging in the medical diagnostic radiology including angiography and cardiac computed tomography. The CsPbBr3 nanocrystal scintillator featuring a nanosecond radioluminescence decay time is a promising candidate. However, it suffers from a substantial photon self-absorption limiting the light output, and being bright and fast simultaneously is difficult. Here we design and in-situ synthesize multi-site ZnS(Ag)-CsPbBr3 heterostructures to modulate the bright and fast features of scintillators. We find external energy from ZnS(Ag) can effectively transfer to CsPbBr3 based on the non-radiative Förster resonance energy transfer, resulting in a light yield of 40,000 photons MeV-1. By combing a radioluminescence decay time of 36 ns and a spatial resolution of 30 lp mm-1, the scintillator enables high-speed X-ray imaging at 200 frames per second. This study showcases the structure design is significant for obtaining bright and fast perovskite scintillators for the real-time X-ray imaging.

Robo-Matter towards reconfigurable multifunctional smart materials

Maximizing materials utilization efficiency via enhancing their reconfigurability and multifunctionality offers a promising avenue in addressing the global challenges in sustainability. To this end, significant efforts have been made in developing reconfigurable multifunctional smart materials, which can exhibit remarkable behaviors such as morphing and self-healing. However, the difficulty in efficiently manipulating and controlling matter at the building block level with manageable cost and complexity, which is crucial to achieving superior responsiveness to environmental clues and stimuli, has significantly hindered the further development of such smart materials. Here we introduce a concept of Robo-Matter, which can be activated and controlled through external information exchange at the building block level, to enable a high-level of controllability, mutability and versatility for reconfigurable multifunctional smart materials. Using specially designed micro-robot building blocks with symmetry-breaking active motion modes, tunable anisotropic interactions, and interactive coupling with a programmable spatial-temporal dynamic light field, we demonstrate an emergent Robot-Matter duality, which enables a spectrum of desirable behaviors spanning from matter-like properties such as ultra-fast self-assembly and adaptivity, to robot-like properties including active force output, smart healing, smart morphing and infiltration. Our work demonstrates a promising direction for designing next-generation smart materials and large-scale robotic swarms.

Dynamic interface printing

Additive manufacturing is an expanding multidisciplinary field encompassing applications including medical devices1, aerospace components2, microfabrication strategies3,4 and artificial organs5. Among additive manufacturing approaches, light-based printing technologies, including two-photon polymerization6, projection micro stereolithography7,8 and volumetric printing9-14, have garnered significant attention due to their speed, resolution or potential applications for biofabrication. Here we introduce dynamic interface printing, a new 3D printing approach that leverages an acoustically modulated, constrained air-liquid boundary to rapidly generate centimetre-scale 3D structures within tens of seconds. Unlike volumetric approaches, this process eliminates the need for intricate feedback systems, specialized chemistry or complex optics while maintaining rapid printing speeds. We demonstrate the versatility of this technique across a broad array of materials and intricate geometries, including those that would be impossible to print with conventional layer-by-layer methods. In doing so, we demonstrate the rapid fabrication of complex structures in situ, overprinting, structural parallelization and biofabrication utility. Moreover, we show that the formation of surface waves at the air-liquid boundary enables enhanced mass transport, improves material flexibility and permits 3D particle patterning. We, therefore, anticipate that this approach will be invaluable for applications where high-resolution, scalable throughput and biocompatible printing is required.

Sub-surface thermal measurement in additive manufacturing via machine learning-enabled high-resolution fiber optic sensing

Microstructures of additively manufactured metal parts are crucial since they determine the mechanical properties. The evolution of the microstructures during layer-wise printing is complex due to continuous re-melting and reheating effects. The current approach to studying this phenomenon relies on time-consuming numerical models such as finite element analysis due to the lack of effective sub-surface temperature measurement techniques. Attributed to the miniature footprint, chirped-fiber Bragg grating, a unique type of fiber optical sensor, has great potential to achieve this goal. However, using the traditional demodulation methods, its spatial resolution is limited to the millimeter level. In addition, embedding it during laser additive manufacturing is challenging since the sensor is fragile. This paper implements a machine learning-assisted approach to demodulate the optical signal to thermal distribution and significantly improve spatial resolution to 28.8 µm from the original millimeter level. A sensor embedding technique is also developed to minimize damage to the sensor and part while ensuring close contact. The case study demonstrates the excellent performance of the proposed sensor in measuring sharp thermal gradients and fast cooling rates during the laser powder bed fusion. The developed sensor has a promising potential to study the fundamental physics of metal additive manufacturing processes.

Printable, stretchable metal-vapor-desorption layers for high-fidelity patterning in soft, freeform electronics

High-fidelity patterning of thin metal films on arbitrary soft substrates promises integrated circuits and devices that can significantly augment the morphological functionalities of freeform electronics. However, existing patterning methods that decisively rely on prefabricated rigid masks are severely incompatible with myriad surfaces. Here, we report printable, stretchable metal-vapor-desorption layers (s-MVDLs) that can enable high-fidelity patterning of thin metal films on freeform polymeric surfaces. The printed rubbery matrix with highly mobile chains effectively repels various metal vapors from the surface and inhibits their condensation, thereby allowing selective metal deposition. The s-MVDLs are printed by direct ink writing techniques, enabling customizable and scalable thin metal patterns ranging from the micrometer to millimeter scale with high fidelity. Furthermore, the superior stretchability and mechanical robustness of the s-MVDLs allow highly compliant deformation along the substrates, enabling the construction of unconventional circuits and devices on multi-curvature, non-developable, and stretchable surfaces.

GEMTELLIGENCE: Accelerating gemstone classification with deep learning

The value of luxury goods, particularly investment-grade gemstones, is influenced by their origin and authenticity, often resulting in differences worth millions of dollars. Traditional methods for determining gemstone origin and detecting treatments involve subjective visual inspections and a range of advanced analytical techniques. However, these approaches can be time-consuming, prone to inconsistencies, and lack automation. Here, we propose GEMTELLIGENCE, a novel deep learning approach enabling streamlined and consistent origin determination of gemstone origin and detection of treatments. GEMTELLIGENCE leverages convolutional and attention-based neural networks that combine the multi-modal heterogeneous data collected from multiple instruments. The algorithm attains predictive performance comparable to expensive laser-ablation inductively-coupled-plasma mass-spectrometry analysis and expert visual examination, while using input data from relatively inexpensive analytical methods. Our methodology represents an advancement in gemstone analysis, greatly enhancing automation and robustness throughout the analytical process pipeline.

Filter cable design with defected conductor transmission structures

Electrical cables, as the industry's blood vessels and nervous system, require evolving distributed filtering for complex electromagnetic environment adaptability. This article introduces a filter cable design featuring an insulated cylinder coated with a defected conductor transmission structure (DCTS). The DCTS, with a well-designed etched pattern, functions as a boundary condition for transmitting specific frequency electromagnetic waves, similar to a lumped filter circuit. To validate this method, a low-pass filter cable is proposed with six-slot-ring defected structures, utilizing polytetrafluoroethylene as the inner dielectric, encased within a flexible printed circuit board (FPCB)-manufactured DCTS. The proposed cable, with precise dimensions (2.4 mm diameter, 340 mm length), demonstrates minimal insertion loss ( < 0.38 dB below 6 GHz) in the passband and rejection exceeding 23 dB at 7.7-25 GHz in the stopband. Further enhancements achieve attenuation exceeding 50 dB in the stopband (7.1 GHz to 20 GHz). Compared to traditional cables, this filter cable addresses electromagnetic compatibility (EMC) by cutting off the interference coupling path.

Holographic direct sound printing

Direct sound printing (DSP), an alternative additive manufacturing process driven by sonochemical polymerization, has traditionally been confined to a single acoustic focal region, resulting in a voxel-by-voxel printing approach. To overcome this limitation, we introduce holographic direct sound printing (HDSP), where acoustic holograms, storing cross-sectional images of the desired parts, pattern acoustic waves to induce regional cavitation bubbles and on-demand regional polymerization. HDSP outperforms DSP in terms of printing speed by one order of magnitude and yields layerless printed structures. In our HDSP implementation, the hologram remains stationary while the printing platform moves along a three-dimensional path using a robotic arm. We present sono-chemiluminescence and high-speed imaging experiments to thoroughly investigate HDSP and demonstrate its versatility in applications such as remote ex-vivo in-body printing and complex robot trajectory planning. We showcase multi-object and multi-material printing and provide a comprehensive process characterization, including the effects of hologram design and manufacturing on the HDSP process, polymerization progression tracking, porosity tuning, and robotic trajectory computation. Our HDSP method establishes the integration of acoustic holography in DSP and related applications.

Accelerated discovery of perovskite solid solutions through automated materials synthesis and characterization

Accelerating perovskite solid solution discovery and sustainable synthesis is crucial for addressing challenges in wireless communication and biosensors. However, the vast array of chemical compositions and their dependence on factors such as crystal structure, and sintering temperature require time-consuming manual processes. To overcome these constraints, we introduce an automated materials discovery approach encompassing machine learning (ML) assisted material screening, robotic synthesis, and high-throughput characterization. Our proposed platform for rapid sintering and dielectric analysis streamlines the characterization of perovskites and the discovery of disordered materials. The setup has been successfully validated, demonstrating processing materials within minutes, in stark contrast to conventional procedures that can take hours or days. Following setup validation with established samples, we showcase synthesizing single-phase solid solutions within the barium family, such as (BaxSr1-x)CeO3, identified through ML-guided chemistry.

Unequally-spaced slot strategy for radiation null reduction in single SIW-embedded antenna element

The incorporation of higher-order modes (HOMs) can substantially augment the antenna gain and bandwidth, but this improvement is typically accompanied by compromised radiation performance including radiation nulls and higher side lobe levels. In this study, an inventive strategy is introduced to reduce the radiation nulls and the side lobe levels of a single antenna element by positioning multiple slots of the radiating element at unequal spacing. Dual hybrid HOMs are analyzed inside a substrate integrated waveguide-based cavity to design a wide band, enhanced gain dual-polarized antenna. The radiating element of the antenna is designed with multiple slots positioned at unequal spacing but symmetrical along the origin. This methodology provides three-fold advantages: a reduction of side lobes, an adjustment of phase center, and a significant reduction of radiation nulls. The antenna has been fabricated, and experimentally validated. The antenna exhibits a reduction in radiation null to - 0.5 dB, a phase adjustment of the main lobe to 0°, and a reduction in side lobe level from - 14.4 dB (N = 2, equal spacing) and - 15.5 dB (N = 4, equal spacing) a maximum of - 19.7 dB (N = 4, unequal spacing) at 12.35 GHz in the phi-0 plane. Excellent agreement between measured and simulated results corroborates the efficacy of the proposed approach. The significant improvement in the radiation performance of the single-element antenna design sets the antenna design apart from the state-of-the-art solutions.

Enhanced aerosol-jet printing using annular acoustic field for high resolution and minimal overspray

Aerosol jet printing has the potential to fabricate fine features on various substrates due to its large stand-off distance. However, the presence of overspray and instability, particularly at high printing resolutions, has limited its widespread application. In this study, we introduce an efficient approach called annular acoustic focusing for aerosol jet printing. By determining the optimal focusing frequency (5.8 MHz) for silver nanoparticles using a particle ejection model, we achieve precise and stable printing. We also propose a modified print nozzle geometry, resulting in ultrafine traces (line width < 6 μm, overspray < 0.1 μm). Compared to printing without acoustic focusing, the line width of the traces decreases to 60 ± 5% while their conductivity increases to 180 ± 5%. Additionally, several 8 h experiments demonstrate excellent printing stability. This research opens up possibilities for the fabrication of conformal electronics with high precision and improved conductivity using aerosol jet printing.

Micromachined structures decoupling Joule heating and electron wind force

Microstructural changes in conductive materials induced by electric current treatments, such as electromigration and electroplasticity, are critical in semiconductor and metal processing. However, owing to the inevitable thermal effect (Joule heating), the athermal effect on microstructural modifications remains obscure. This paper presents an approach of utilizing pre-micromachined structures, which obstruct current flow but maintain a thermal history similar to that of the matrix, effectively disentangling the thermal and athermal effects. A duplex stainless-steel material is selected to validate the feasibility of this method. Microstructural characterizations show that the athermal effect, especially the electron wind force (EWF), primarily governs the element diffusion and phase transformation in this study. Moreover, many σ phases (Cr-enriched) are precipitated in the micromachined structures, whereas no precipitation occurred in the matrix, suggesting that the directional EWF disrupts the Cr aggregation caused by Joule heating. Furthermore, we present a critical formula for determining the dimensions of micromachined structures of commonly used metallic materials. The proposed method may serve as an effective and powerful tool for unveiling the athermal effect on microstructural alterations.

Reproducibility analysis of bioimpedance-based self-developed live cell assays

Bioimpedance spectrum (BIS) measurements have a great future in in vitro experiments, meeting all the requirements for non-destructive and label-free methods. Nevertheless, a real basic research can provide the necessary milestones to achieve the success of the method. In this paper a self-developed technology-based approach for in vitro assays is proposed. Authors invented a special graphene-based measuring plate in order to assess the high sensitivity and reproducibility of introduced technique. The design of the self-produced BIS plates maximizes the detection capacity of qualitative changes in cell culture and it is robust against physical effects and artifacts. The plates do not influence the viability and proliferation, however the results are robust, stable and reproducible regardless of when and where the experiments are carried out. In this study, physiological saline concentrations, two cancer and stem cell lines were utilized. All the results were statistically tested and confirmed. The findings of the assays show, that the introduced BIS technology is appropriate to be used in vitro experiments with high efficacy. The experimental results demonstrate high correlation values across the replicates, and the model parameters suggested that the characteristic differences among the various cell lines can be detected using appropriate hypothesis tests.

3D printable and biocompatible PEDOT:PSS-ionic liquid colloids with high conductivity for rapid on-demand fabrication of 3D bioelectronics

3D printing has been widely used for on-demand prototyping of complex three-dimensional structures. In biomedical applications, PEDOT:PSS has emerged as a promising material in versatile bioelectronics due to its tissue-like mechanical properties and suitable electrical properties. However, previously developed PEDOT:PSS inks have not been able to fully utilize the advantages of commercial 3D printing due to its long post treatment times, difficulty in high aspect ratio printing, and low conductivity. We propose a one-shot strategy for the fabrication of PEDOT:PSS ink that is able to simultaneously achieve on-demand biocompatibility (no post treatment), structural integrity during 3D printing for tall three-dimensional structures, and high conductivity for rapid-prototyping. By using ionic liquid-facilitated PEDOT:PSS colloidal stacking induced by a centrifugal protocol, a viscoplastic PEDOT:PSS-ionic liquid colloidal (PILC) ink was developed. PILC inks exhibit high-aspect ratio vertical stacking, omnidirectional printability for generating suspended architectures, high conductivity (~286 S/cm), and high-resolution printing (~50 µm). We demonstrate the on-demand and versatile applicability of PILC inks through the fabrication of 3D circuit boards, on-skin physiological signal monitoring e-tattoos, and implantable bioelectronics (opto-electrocorticography recording, low voltage sciatic nerve stimulation and recording from deeper brain layers via 3D vertical spike arrays).

Generation of precision microstructures based on reconfigurable photoresponsive hydrogels for high-resolution polymer replication and microoptics

Microstructured molds are essential for fabricating various components ranging from precision optics and microstructured surfaces to microfluidics. However, conventional fabrication technology such as photolithography requires expensive equipment and a large number of processing steps. Here, we report a facile method to fabricate micromolds based on a reusable photoresponsive hydrogel: Uniform micropatterns are engraved into the hydrogel surface using photo masks under UV irradiation within a few minutes. Patterns are replicated using polydimethylsiloxane with minimum feature size of 40 μm and smoothness of Rq ~ 3.4 nm. After replication, the patterns can be fully erased by light thus allowing for reuse as a new mold without notable loss in performance. Utilizing greyscale lithography, patterns with different height levels can be produced within the same exposure step. We demonstrate the versatility of this method by fabricating diffractive optical elements devices and a microlens array and microfluidic device with 100 µm wide channels.

Phasor-based analysis of a neuromorphic architecture for microwave sensing

This article presents a design procedure for implementing artificial neural networks (ANNs) using conventional microwave components at the hardware level with potential applications in radar and remote sensing. The main objective is to develop structured hardware design methods for implementing artificial neurons, utilizing microwave devices to create neuromorphic devices compatible with high-frequency electromagnetic waves. The research aims to address the challenge of encoding and modulating information in electromagnetic waves into a format suitable for the neuromorphic device by using frequency-modulated information instead of intensity-modulated information. It also proposes a method for integrating principal component analysis as a dimensionality reduction technique with the implementation of ANNs on a single hardware. As a dummy task, the process outlined here is used to implement an artificial neural network at the hardware level, with a specific emphasis on creating hardware that is capable of performing matrix multiplications in the form of dot products while also being able to extract the resulting data in an interpretable manner. The proposed implementation involves the use of directional couplers to implement weights and sample the resulting signal at specific intervals to obtain the multiplication result.

Light-driven C-H activation mediated by 2D transition metal dichalcogenides

C-H bond activation enables the facile synthesis of new chemicals. While C-H activation in short-chain alkanes has been widely investigated, it remains largely unexplored for long-chain organic molecules. Here, we report light-driven C-H activation in complex organic materials mediated by 2D transition metal dichalcogenides (TMDCs) and the resultant solid-state synthesis of luminescent carbon dots in a spatially-resolved fashion. We unravel the efficient H adsorption and a lowered energy barrier of C-C coupling mediated by 2D TMDCs to promote C-H activation and carbon dots synthesis. Our results shed light on 2D materials for C-H activation in organic compounds for applications in organic chemistry, environmental remediation, and photonic materials.

Ag-thiolate interactions to enable an ultrasensitive and stretchable MXene strain sensor with high temporospatial resolution

High-sensitivity strain sensing elements with a wide strain range, fast response, high stability, and small sensing areas are desirable for constructing strain sensor arrays with high temporospatial resolution. However, current strain sensors rely on crack-based conductive materials having an inherent tradeoff between their sensing area and performance. Here, we present a molecular-level crack modulation strategy in which we use layer-by-layer assembly to introduce strong, dynamic, and reversible coordination bonds in an MXene and silver nanowire-matrixed conductive film. We use this approach to fabricate a crack-based stretchable strain sensor with a very small sensing area (0.25 mm2). It also exhibits an ultrawide working strain range (0.001-37%), high sensitivity (gauge factor ~500 at 0.001% and >150,000 at 35%), fast response time, low hysteresis, and excellent long-term stability. Based on this high-performance sensing element and facile assembly process, a stretchable strain sensor array with a device density of 100 sensors per cm2 is realized. We demonstrate the practical use of the high-density strain sensor array as a multichannel pulse sensing system for monitoring pulses in terms of their spatiotemporal resolution.

Consecutive multimaterial printing of biomimetic ionic hydrogel power sources with high flexibility and stretchability

Electric eel is an excellent example to harness ion-concentration gradients for sustainable power generation. However, current strategies to create electric-eel-inspired power sources commonly involve manual stacking of multiple salinity-gradient power source units, resulting in low efficiency, unstable contact, and poor flexibility. Here we propose a consecutive multimaterial printing strategy to efficiently fabricate biomimetic ionic hydrogel power sources with a maximum stretchability of 137%. The consecutively-printed ionic hydrogel power source filaments showed seamless bonding interface and can maintain stable voltage outputs for 1000 stretching cycles at 100% strain. With arrayed multi-channel printhead, power sources with a maximum voltage of 208 V can be automatically printed and assembled in parallel within 30 min. The as-printed flexible power source filaments can be woven into a wristband to power a digital wristwatch. The presented strategy provides a tool to efficiently produce electric-eel-inspired ionic hydrogel power sources with great stretchability for various flexible power source applications.

A bioinspired surface tension-driven route toward programmed cellular ceramics

The intriguing biomineralization process in nature endows the mineralized biological materials with intricate microarchitected structures in a facile and orderly way, which provides an inspiration for processing ceramics. Here, we propose a simple and efficient manufacturing process to fabricate cellular ceramics in programmed cell-based 3D configurations, inspired by the biomineralization process of the diatom frustule. Our approach separates the ingredient synthesis from architecture building, enabling the programmable manufacturing of cellular ceramics with various cell sizes, geometries, densities, metastructures, and constituent elements. Our approach exploits surface tension to capture precursor solutions in the architected cellular lattices, allowing us to control the liquid geometry and manufacture cellular ceramics with high precision. We investigate the geometry parameters for the architected lattices assembled by unit cells and unit columns, both theoretically and experimentally, to guide the 3D fluid interface creation in arranged configurations. We manufacture a series of globally cellular and locally compact piezoceramics, obtaining an enhanced piezoelectric constant and a designed piezoelectric anisotropy. This bioinspired, surface tension-assisted approach has the potential to revolutionize the design and processing of multifarious ceramic materials for structural and functional applications in energy, electronics and biomedicine.