Replicating biological systems using non-living materials, from the foundational molecular level to complex tissue structures, is central to abiotic mimicry. Enzymes play a vital role in these systems; however, replicating their enzymatic power with minimal components remains a key challenge. Here we show that gallium in the liquid state exhibits nuclease-like activity with preferred cleaving sites. The mechanism involves nucleotide-biased adsorption and hydroxyl radical-assisted phosphodiester hydrolysis. Compared with previously reported artificial metallonucleases, the liquid gallium uniquely integrates its oxide layer for substrate adsorption and its metallic core with electrons as a cleavage active center, forming a ligand- and cofactor-free artificial nuclease platform. Moreover, their activity is tunable through synthesis parameters and external stimuli, enabling programmable control with spatial or temporal precision. This work presents a minimalistic yet functional approach to enzyme mimicry, expanding the design space for abiotic enzymatic systems and offering potential opportunities in therapeutic applications, synthetic biology, and biomaterials.

ABSTRACT Polymer nanocomposites are widely explored to enhance the electrocaloric effect (ECE) through various interfacial modulation. While many prior works focused on all‐solid nanocomposites, in which the both matrix and fillers are solid‐state materials, the role of interfacial mechanical modulus in regulating local dipolar responses and macroscopic entropy changes remains unexplored. Here, we develop ferroelectric polymer nanocomposites incorporating liquid metals as modulus‐tunable fillers to elucidate how the interfacial mechanical properties regulate EC behavior. Mechanically soft and rigid interfaces are constructed by embedding eutectic gallium–indium (EGaIn) alloy and gallium (Ga) nanoparticles, respectively, into a P(VDF‐TrFE‐CFE) matrix. Despite similar surface oxidation and functionalization, structural characterizations reveal that relatively soft interfaces have a stronger effect on the dipolar responses under the external electric field than that of the rigid interfaces. Phase‐field simulations reveal that mechanically compliant interfaces promote enhanced local dielectric permittivity and polarization over an extended interfacial region, whereas mechanically rigid interfaces, although still beneficial relative to the neat matrix, generate a relatively restricted dipolar reorientation. Consistently, the EGaIn‐based nanocomposite exhibits facilitated polarization switching and an enhanced EC response, achieving entropy changes up to 50 J kg −1 K −1 . This work establishes interfacial mechanical modulus as a critical parameter for high‐performance EC polymer nanocomposites.

Droplet-based microfluidics has transformed high-throughput screening by compartmentalizing biochemical reactions into nanoliter-to-picoliter soft microenvironments. However, precise on-demand reagent addition after droplet formation remains challenging due to interfacial tension barriers. This review comprehensively summarizes recent advances in reagent addition technologies from the perspectives of soft matter physics and interfacial engineering. Strategies are categorized into passive hydrodynamic merging and active injection approaches, highlighting the mechanisms used to disrupt surfactant-stabilized interfaces for reagent delivery. The broad impact of these spatiotemporally decoupled addition strategies is further discussed in applications including multistep synthesis of soft functional materials, drug screening, single-cell multi-omics, and directed enzyme evolution. Finally, current challenges limiting industrial translation are critically assessed. Continued advances in this field are expected to drive the development of intelligent droplet microreactor systems for next-generation biomedical and materials applications.

Liquid metal (LM) polymer composites are made to be soft and deformable but usually require post-synthesis sintering to rupture the insulating gallium oxide shell around droplets to become conductive. Here, we introduce sintering-free Janus composite made of eutectic gallium-indium (EGaIn) dispersed into poly(vinylidene fluoride) matrix, achieving high conductivity (>10(5) S m(-1)) through spontaneous fluorination of the Ga2O3 shell during synthesis. Fluorine doping converts the oxide layer into a highly doped n-type semiconductor, enabling inter-particle electron tunneling. A percolation transition is observed at similar to 52 vol % EGaIn, where charge transport shifts from thermal emission near the threshold to field emission at higher loadings. The material's Janus architecture and multifunctionality are demonstrated through motion sensors, bioelectronic interfaces for cellular stimulation, and orientation-dependent thermal management. This reactive-composite strategy recasts the native oxide shell as a tunable semiconductor rather than a barrier, offering a new route to robust, multifunctional soft electronics.

Abstract Biomarkers reflect physiological states and disease progression in the human body. Their precise detection is crucial for accurate and effective diagnosis. Functional hybrid microbeads (FHMBs) with electrical, magnetic, and/or optical responsiveness have emerged as versatile platforms for signal amplification, transduction, and conversion. This review summarizes recent advances in microfluidic strategies for producing FHMBs, with emphasis on incorporating functional nanoparticles (NPs) into microdroplets. We discuss the advantages of microfluidics in generating monodisperse droplets, controlling composition, encapsulating functional NPs, and forming FHMBs through solidification processes. Key droplet‐generation strategies are summarized, encompassing passive and active mechanisms, as well as both on‐chip and off‐chip approaches, followed by an overview of solidification methods driven by physical or chemical processes. We classify FHMBs into four functional categories: electrical, optical, magnetic, and mixed response, based on their material composition, fabrication methods, and practical applications. Finally, we discuss the current challenges and suggest future research directions to advance the development of improved platforms for FHMBs production.

Traditional rotary motors have been developed using a variety of technologies. Electrochemically fluidic motors based on liquid metals offer unique potential advantages to the field of rotary motors. Current designs, however, are limited in rotational speed due to suboptimal extraction of mechanical motion from the liquid metal. Here, we present an electrochemically driven liquid metal rotary motor that is conceptually distinct from previous approaches by incorporating a paddle directly inserted inside the liquid metal droplet. This design, driven by pulsed electric signals, takes advantage of the internal vortices of the droplet to directly generate rotation, achieving maximum rotational speeds of 320 rpm. By directly coupling the paddle to the internal flow dynamics, this work demonstrates a more efficient and practical method for liquid metal-based actuation in an electrochemical setting. Such a system has potential applications in microfluidics and soft systems and introduces a new conceptual approach to rotary motor design.

Liquid gallium (Ga) has emerged as a promising phase change material (PCM) for additive manufacturing, enhanced heat transfer, and energy storage due to its low melting point, high thermal conductivity and latent heat. However, the applications of liquid Ga in thermal management systems are hampered by their pronounced supercooling and delayed phase transition processes. Here, we propose a hybrid strategy by applying modulated mechanical vibration to liquid Ga to achieve rapid phase transition. A tailored needle with mechanical vibration of 1 mm amplitude and 20 Hz frequency is applied to the liquid Ga, facilitating heat transfer uniformity and dynamically surface renewal, accelerating the phase transition. Moreover, the introduction of Cu microparticles, serving as heterogeneous nucleation sites inside, effectively reduces interfacial energy and suppresses supercooling. This novel approach reduces supercooling to below 2 degrees C and decreases the complete phase transition time to less than 2 s. Harnessing the outstanding performance of this strategy, a heat dissipation module and an adaptable gripper are further developed, realising rapid thermal cycling, dynamic stiffness control and desired grasping performance. This work provides a strong pathway for the development of efficient thermal management systems in electronics, robotics, and energy storage applications.

Strain-induced signal interference is a critical challenge limiting the reliability and functionality of electronic textiles in real-world, deformable environments. Mechanical deformation during motion or wear can distort signal fidelity, compromise sensing accuracy, and disrupt energy or data transmission-hindering the advancement of smart, adaptive wearables. Here, we introduce a strain-programmable fiber platform that turns mechanical strain from a liability into a tunable design feature. By embedding liquid metal (LM) particles within a polyurethane elastomer via coaxial wet spinning, we create composite fibers whose electromechanical responses can be precisely programmed-through pre-strain and composition-to exhibit negative, hybrid, or positive strain-resistance behaviors. This tunability arises from strain-induced LM particle reconfiguration, driven by a balance of geometric deformation and conductive network evolution, and captured through a hybrid parallel-series model. Leveraging this functionality, we demonstrate bidirectional strain sensors with polarity-based digital encoding and strain-invariant circuits for robust energy harvesting, wireless communication and thermal management. This programmable approach offers a scalable, material-level solution to strain interference, enabling high-performance, multifunctional e-textiles for next-generation wearable electronics.

Multimodal tactile sensing is crucial for next-generation robotics and human-machine interaction, but conventional solutions based on discrete sensor arrays suffer from complexity, limited flexibility, and high fabrication costs. Here, we introduce a continuum sensing paradigm based on a continuous liquid metal enabled flexible tactile sensing (CLiMETS) platform. This approach eliminates the need for sensor arrays by decoding tactile information from a single, unstructured liquid metal (LM) surface. We reveal a key mechanism where the deformation-induced voltage of the LM's electric double layer (EDL) is synergistically amplified by over two orders of magnitude upon contact with a conductive rod. Our geometrically encoded, dual-channel scheme enables precise 5 by 5 localization and eight-directional sliding recognition. We further demonstrate the platform's feasibility by realizing postprocessing visual feedback of an LED array, effectively translating complex tactile inputs into corresponding optical outputs. The CLiMETS platform offers a minimalist yet highly versatile proof-of-concept sensing modality, laying a strong foundation for more adaptive and interactive tactile technologies.

Electro-responsive hydrogel actuators (ERHAs) are promising candidates for soft robotics due to their capability for exhibiting large, reversible deformations. However, their application potential is constrained by the requirement for high driving electric field strength (E), insufficient mechanical robustness, and slow actuation response. Here, to simultaneously address these limitations, we design an ionic hydrogel with integrated liquid metal (LM) and thermoresponsive LCST behavior. The porous architecture is readily constructed by the LCST-induced phase separation process. LM inclusion not only enables sensitivity to low E but also reinforces mechanical properties of the otherwise weakened porous hydrogel. The resulting actuator achieves a large bending angle of 88.1° within 32 seconds under a low electric field of 0.25 V mm-1. This represents the fastest electro-response reported to date among ERHAs operating below 1 V mm-1, a threshold widely recognized as safe for human exposure. Furthermore, we demonstrate its versatility in executing diverse underwater tasks, including object manipulation, encapsulation, and directional locomotion. This facile yet effective strategy for constructing mechanically robust, fast-response hydrogel composites offers new avenues for the development of next-generation soft robotic systems.

Conductive microneedles (CMNs) combine the minimally invasive characteristics of microneedles with the electrical functionality required for sensing, recording, stimulation, and controlled drug delivery. By penetrating the stratum corneum with reduced pain and tissue damage, they provide efficient access to the skin microenvironment and have shown strong potential in wearable healthcare, precision diagnostics, and intelligent therapeutics. Despite these advantages, challenges remain in balancing mechanical robustness with electrical functionality, improving fabrication precision and reproducibility, maintaining interfacial stability, and achieving scalable manufacturing. In this review, the major fabrication routes for CMNs are summarized and compared in terms of forming principles, material compatibility, and conductivity-introduction strategies. Secondly, research on the key performances of CMNs is discussed. After that, the applications of CMNs in electrochemical sensing, bioelectrical signal acquisition, electrostimulation therapy, and drug delivery are overviewed, followed by a brief discussion of current challenges and future perspectives.

Electrochemical aptamer-based (E-AB) sensors have experienced remarkable growth across a broad range of applications, such as precision medicine, chronic disease management, food safety, and environmental monitoring, due to their exceptional capability for real-time and continuous monitoring of biomarkers. However, biofouling in complex biological environments remains a critical challenge for the E-AB sensors, compromising signal strength, operational stability, and biosensing specificity. Here, we present a zwitterionic coating strategy that integrates poly-sulfobetaine methacrylate (SBMA) and polydopamine (PDA) to enhance the antifouling properties of the E-AB sensors, thereby enabling sensitive, stable, and accurate detection of a model antibiotic drug, vancomycin. The durable and hydrophilic antifouling layer was grafted onto the electrode surface to minimize signal drift while preserving sufficient signal on the E-AB sensors. The SBMA@PDA coating was systematically optimized and demonstrated superior resistance to biofouling under various environmental conditions, including pH, temperature, and mechanical stress. Furthermore, the coating was incorporated into a wearable microneedle patch for monitoring vancomycin dynamics in artificial interstitial fluids, achieving robust stability and performance. These findings establish a reliable and effective antifouling approach, advancing the practical application of E-AB sensors for continuous therapeutic drug monitoring in clinical and wearable healthcare settings.

Droplet‐based microfluidics has revolutionized the lab‐on‐a‐chip field by enabling precise generation and manipulation of monodisperse droplets that act as independent microreactors. Over two decades, innovations in passive geometries and active control methods have facilitated a wide range of droplet operations, driving applications in molecular diagnostics, single‐cell analysis, drug discovery, and material synthesis. Despite these advances, challenges remain in reproducibility, scalability, and detection, alongside the growing need to manage complex experimental datasets. Parallel to these developments, artificial intelligence (AI) has evolved from early neural models to powerful deep learning and foundation architectures, offering transformative opportunities for droplet‐based platforms. Supervised, unsupervised, and reinforcement learning approaches enhance droplet detection, sorting, and adaptive control, while deep learning architectures enable high‐dimensional image analysis, time‐dependent modeling, and multimodal data integration. Transfer learning and meta learning further address data scarcity, and emerging explainable AI frameworks provide interpretability critical for clinical and diagnostic applications. This review highlights the convergence of droplet‐based microfluidics and AI, examining applications across droplet generation, detection, screening, and material synthesis and offering perspectives on challenges and future directions. Together, these fields promise to accelerate discovery and expand the clinical and industrial impact of microfluidics.

The amoeba can flow like liquid to change its morphology to effectively capture and excrete various prey. Inspired by the amoeba, we present a liquid metal universal gripper capable of effective grasping and active releasing of targets with various shapes, sizes, and stiffnesses in liquid and air. We unveil a surface tension induced active release mechanism enabling tunable active release of micro-objects. The gripper operates across 14 orders of magnitude in weight (from 10-12 g to 200 g) and achieves a low gripping contact pressure of ~10 Pa for handling delicate items. It can capture and release moving objects within milliseconds without precise alignment. An environment-agnostic surface activity design extends its functionality to a non-electrolyte environment. The gripper offers notable performance metrics over existing robotic grippers in multiscale operation, low contact pressure, and tunable releasing speed, representing a notable solution for living organisms and microscale objects.

CRISPR-based biosensors are emerging as powerful tools in precision medicine, enabling rapid and highly specific molecular detection for personalized interventions. Their performance depends on interconnected components. Guide RNA (gRNA) design and optimization improve on-target activity and reduce off-target effects, while Cas protein engineering and structure prediction reveal functional determinants for programmable modification. Meanwhile, biosensor design and signal readout strategies enable portable, quantitative, and multiplexed detection. Recent advances in artificial intelligence (AI) have created new opportunities to optimize these components. AI bridges molecular design and analytical performance, enhancing sensitivity, specificity, quantitative readout, and automation in CRISPR-based biosensing. This paper provides a systematic review and comparative analysis of recent progress in AI-enabled gRNA design and optimization, Cas protein engineering and structure prediction, and biosensor readout and automation for CRISPR-based biosensing. It further discusses the opportunities and challenges associated with integrating these advances into multifunctional, standardized platforms for point-of-care testing and clinical translation.

Stretchable electronics have progressed rapidly, with many academic prototypes frequently demonstrating elongations exceeding 100

Harnessing the surface tension of liquids to perform mechanical work is commonly seen in nature. Effectively utilising liquid surface energy requires dynamic surface tension tuning; however, for common liquids like water and oil, existing tuning methods are inefficient, irreversible, or limited in range. Gallium-based liquid metals possess the highest surface tension (≈600 mN·m⁻¹) at room temperature and, uniquely, can be reversibly tuned to near-zero via electrochemical control. Here, we present capillary liquid metal muscles (CLMMs), which harness the confinement of liquid metal in microchannels to maximise surface energy. CLMMs deliver high force output (can lift 1 kg), fast response times (<25 ms), and low operating voltages (<10 V), while offering precise control over both output force and position. CLMMs offer the highest pressure-per-volt performance among all electro-driven liquid actuators.

Robotic systems have become indispensable across various domains, enhancing efficiency, safety, and convenience in everyday life. While rigid robots excel in precision and load‐bearing tasks, their lack of adaptability poses challenges in human interaction and unstructured environments. Soft robots, constructed from flexible materials, offer safer and more adaptive solutions but often lack the rigidity needed for high‐force applications. To bridge this gap, stiffness‐tunable robotic systems have emerged, with phase‐change materials (PCMs) gaining significant attention due to their ability to transition between soft and rigid phases, enabling dynamic stiffness modulation. Unlike conventional stiffness‐tuning methods that require bulky external components, PCM‐based soft robots provide a lightweight and compact alternative, making them highly suitable for applications that demand both adaptability and load‐bearing capabilities. However, slow phase transition rates remain a key limitation, prompting research into advanced thermal management and phase control strategies to enhance responsiveness. This review explores recent advancements in PCM‐enabled robotics, focusing on their underlying mechanisms, key applications in gripping, minimally invasive surgery, shape morphing, and locomotion, and the challenges that must be addressed to unlock their full potential. By summarizing the latest developments, this review highlights the promising role of PCMs in the evolution of multifunctional, adaptable soft robotic systems.

A liquid metal microparticle-enabled humidity sensor (referred to as LM 2 H) is passive, low-cost, highly sensitive, and ultra-compact.

Liquid biopsies have emerged as a key tool that enables personalized medicine, enabling precise detection of biochemical parameters to tailor treatments to individual needs. Modern biosensors enable real-time detection, precise diagnosis, and dynamic monitoring by rapidly analyzing biomarkers such as nucleic acids, proteins, and metabolites in bodily fluids like blood, saliva, and urine. Despite their potential, many biosensors are still constrained by mono-functionality, sub-optimal sensitivity, bulky designs, and complex operation requirements. Recent advances in stimuli-responsive smart materials present a promising pathway to overcome these limitations. These materials enhance biomarker signal transduction, release, or amplification, leading to improved sensitivity, simplified workflows, and multi-target detection capabilities. Further exploration of the integration of these smart materials into biosensing is therefore essential. To this end, this review critically examines and compares recent progress in the development and application of physical, chemical, and biochemical stimuli-responsive smart materials in biosensing. Emphasis is placed on their responsiveness mechanisms, operational principles, and their role in advancing biosensor performance for biomarker detection in bodily fluids. Additionally, future perspectives and challenges in developing versatile, accurate, and user-friendly biosensors for point-of-care and clinical applications using these smart materials are discussed.