Journals
2026 EN
Chen Yuanhe · Xu Zichen · Sun Yu
+1 more
Microfluidics permits fluid operations at the microscale. Conventional microfluidic devices have fixed structural configurations, which restrict their adaptability for different applications. A new approach is proposed by integrating magnetic miniature robotic systems into microfluidic platforms, thereby enabling dynamic reconfiguration of the microfluidic chip. As a demonstration, the study presents four types of magnetic miniature robots, i.e., magnetic sorting robot, magnetic variable channel robot, magnetic gyroscope robot, and magnetic rotating flow channel robot, to achieve on‐chip sorting, dynamic regulation of fluid velocity, on‐chip flow regulation, and rapid mixing and bubble manipulation. This work presents a versatile and scalable solution for reconfigurable microfluidic systems, opening new avenues for real‐time control in biological and chemical processes.
Journals
2026 EN
Lu HongLin · Chen YuChi · Chen JuiYuan
The potential application of phosphate semiconductor glass in the interlayer of resistive random access memory (RRAM) is investigated. Glasses based on (50–x)% V 2 O 5 −50% P 2 O 5 are synthesized, which are doped with x% MO (where MO = ZnO, CaO, or Na 2 O). X‐ray diffraction analysis reveals that the ZnO and CaO series are amorphous, while the Na 2 O series is crystalline. Differential scanning calorimetry analysis reveals that the glass transition temperature ( T g ) is around 200 °C. X‐ray photoelectron spectroscopy analysis reveals that the internal V elements are primarily +4 and +5. Initial electrical measurements indicate that the ZnO series glass exhibits semiconductor electrical properties. Additionally, nanodevices are fabricated and measured to demonstrate the resistive switching characteristics, with conduction mechanisms such as trap‐assisted tunneling, space‐charge limiting current, or Ohmic conduction. This study demonstrates the potential of phosphate semiconductor glass for application in RRAM and paves the way for the future development of all‐glass RRAM components.
Journals
2026 EN
Yuan Zihao · Ji Huangwei · Huang Kai
+2 more
Inspired by organisms that utilize multimodal locomotion strategies to adapt to diverse environments, the development of analogous capabilities in soft robots has garnered growing attention. This review comprehensively surveys recent advances in multimodal locomotion within soft robotics. Typical locomotion modes are summarized and categorized. Furthermore, the underlying mechanisms enabling multimodal locomotion, encompassing both the integration of distinct locomotion modes and transitions between them, are discussed in detail and classified into three primary categories: active control‐based, reconfiguration‐based, and environment‐responsive strategies. Leveraging these mechanisms, soft robots demonstrate enhanced adaptability for applications such as cross‐domain transition, surface adaptation, and obstacle negotiation. Finally, key challenges in advancing the capabilities of multimodal locomotion to address real‐world applications are discussed.
Journals
2026 EN
Hu An · Sun Yu
Continuum robots enable safe and adaptive interaction with complex, unstructured, or constrained environments through continuous deformation, making them particularly suitable for medical and industrial applications. Accurate contact force sensing is essential to ensure safe and effective physical interaction in such scenarios. Although various embedded force sensors have been developed, sensor‐free approaches offer advantages in miniaturization, cost‐effectiveness, and biocompatibility. This review provides a comprehensive overview of sensor‐free contact force estimation methods for continuum robots, with an emphasis on algorithmic principles rather than specific continuum robot designs or applications. First, contact forces reported in the literature are systematically classified according to their distribution, components, and dynamics. Next, existing force estimation methods are divided into three categories: actuation‐based, deflection‐based, and environment‐based. For each category, the underlying algorithmic principles are discussed, representative challenges are highlighted, and their typical application scenarios are outlined. Finally, emerging trends and potential directions for future research are outlined.
Journals
2026 EN
Lee JuHee · Jung Sumin · Jang Jinwoo
+7 more
As drone technology rapidly evolves, innovative designs that can change their shape or mimic natural flight mechanisms have emerged. This study systematically categorizes and analyzes these advanced strategies for drone design through a comprehensive review of literature from 2001 to 2025. Two main approaches are examined: deformable drones and nature‐inspired drones. Deformable drones are subcategorized into extendable, foldable, and tilting types based on their operational mechanisms. Extendable drones include sliding and scissor‐like mechanisms, while foldable drones are classified by folding direction and mechanism, with size variation ratios of 0.37–1.46. Tilting drones are categorized into body, rotor, and arm tilting based on degrees of freedom and weight classifications. Nature‐inspired flapping drones are analyzed by mass, wingspan, and flight duration across different actuator types. The findings reveal that deformable drones excel in maneuverability and confined space adaptability, while nature‐inspired designs offer advantages in miniaturization and energy efficiency. This study provides the first comprehensive overview of deformable drone technology, offering guidance for specialized applications in environmental monitoring, rescue operations, and urban mobility.
Journals
2026 EN
Shooshtari Mostafa · SerranoGotarredona Teresa · LinaresBarranco Bernabé
The convergence of in‐memory computing (IMC) and neuromorphic architectures offers a promising path toward energy‐efficient, scalable artificial intelligence, particularly for edge and real‐time applications. Memristors, resistive devices with nonvolatile, analog switching, uniquely enable this convergence by serving both as computational memory units for matrix‐vector multiplication and as synaptic elements for spike‐based learning. This review comprehensively explores the physical mechanisms, material classes, and integration strategies of memristors tailored for IMC and spiking neural networks, with emphasis on their implementation in crossbar arrays, synapse‐neuron emulation, and hybrid CMOS circuits. It discusses how memristors facilitate key biological learning rules like STDP and LTP/LTD and examine their deployment in edge artificial intelligence, adaptive robotics, and neuromorphic sensors. Despite their potential, device variability, noise, relaxation, scalability limits, and standardization remain pressing challenges. By synthesizing device‐level insights with architectural innovation and emerging applications, this work outlines a roadmap toward fully integrated, low‐power, and brain‐inspired computing systems.
Journals
2026 EN
Kim Sunghun · Seo HyukJun · Kim Hyeonjung
+3 more
Soft wearable robots have gained widespread interest across various disciplines; however, they remain insufficient in overcoming the physical limitations of the human body. In particular, enhancing vertical jump height, a commonly used indicator of physical capability, requires improved actuator power density, stroke length, and soft structure efficiency. To address these challenges, the Jump‐Enhancing Textile Suit is proposed, which integrates the Pneumatic Energy‐Storing Propulsion Actuator (PESPA) and the Triarticular Kinetic‐Chained Structure (TKiCS) to assist jump performance. PESPA stores elastic energy under pneumatic pressure and releases it during the propulsive phase to augment human movement. TKiCS uses the kinetic chain mechanism to reduce anchoring points and fully harness the high stiffness region, thereby improving force transmission efficiency. Controlled vertical jump experiments with healthy adult participants are conducted. The suit increases jump height by 3.74 cm on average and up to 9.04 cm maximum, while also enhancing hip, knee, and ankle torques. Under isotonic testing, PESPA achieves a power density of 2298.69 W kg −1 and outperforms conventional pneumatic actuators. A dynamic model enables accurate force prediction and precise timing for effective assistance. These findings establish a practical foundation for pneumatic wearable robotics and suggest applications in jump augmentation, rehabilitation, and athletic performance.
Journals
2026 EN
Barwig Chantal · Colaco Ruchira · Koch AlinaSophie
+11 more
Miniaturized bistable actuators are of notable relevance for applications in microfluidics or the manipulation of delicate objects. Many applications require actuators to be multistable, meaning that they can hold specific positions without continuous energy input. However, reversibly controllable soft actuators, especially those based on thermoresponsive materials, typically lack this capability. To overcome this challenge, bistable soft microactuators fabricated by two‐photon polymerization at micrometer precision are demonstrate here, allowing for arbitrary 3D shapes. The bistability is given by material composition, that is, poly( N ‐isopropylacrylamide) (pNIPAM) and a light‐responsive azobenzene compound. The incorporation of an azobenzene into pNIPAM photoresin enables the modification of its lower critical solution temperature (LCST) through the ( E )–( Z )‐isomerization, allowing for two states: a swollen and shrunken state. Hereby, actuation, in terms of shrinking and swelling, is controlled by photoswitching, allowing for the actuation of Azo_pNIPAM microactuators within a constant ambient temperature regime. Moreover, the pNIPAM moiety also allows thermal actuation when it contains either isomer, (( E ) or ( Z )), when the ambient temperature exceeds the LCST. Temperature and light changes are applied to characterize the bistable nature of the microactuators and an application of those bistable microactuators in a lab‐on‐a‐chip device is shown.
Journals
2026 EN
Kim Minu · Ahn Juhyung · Seo Jieun
+2 more
A novel approach to wearable motion tracking that redefines sensor placement strategies is presented. While strain sensors offer compelling advantages over camera‐based systems, most existing methods still rely on intuition‐driven placement and complex machine‐learning models that require extensive data and often generalize poorly. Recent sensor placement optimization studies have attempted to address these limitations using feature selection or search‐based methods, yet they remain constrained to fixed sensor arrays or task‐specific models that do not evaluate placement quality within an end‐to‐end motion tracking framework. This approach overcomes these limitations by leveraging computational strain mapping of joint motion and a genetic algorithm guided directly by model performance to identify optimal sensor configurations that traditional heuristics overlook. The method reveals counterintuitive yet highly effective placements, achieving a 32% reduction in tracking error compared to heuristic layouts. Moreover, this computational framework automatically determines optimal prestrain values, resolving a well‐known limitation in strain sensor deployment. This data‐driven framework not only delivers superior tracking performance but also dramatically accelerates the sensor configuration process, completing in hours what would traditionally require extensive manual testing, thereby enhancing wearable‐sensor design by improving accuracy, efficiency, and practicality for applications in rehabilitation, sports science, and human–computer interaction.
Journals
2026 EN
Park Taeho · Shin Yunwoo · Heo Hyojoo
+2 more
Physically unclonable functions (PUFs) have emerged as candidates for compact hardware security. In this study, PUFs of reconfigurable feedback field‐effect transistors (R‐FBFETs) with polycrystalline silicon channels are designed for dual entropy sources; the channels have inherent random grain boundary‐induced variabilities. Dual entropy source schemes offer a strategic advantage for resource‐constrained platforms by improving the entropy density, area efficiency, and robustness against cyberattacks within a minimized device footprint. An R‐FBFET operates with two‐channel types in a single device through p‐ and n ‐channel modes controlled by the gate bias; hence, two random bits are extracted from a single device. The uniqueness and high reliability of the dual entropy source PUF are confirmed by an inter‐Hamming distance of 49.13% and an intra‐Hamming distance of 3.47%. The PUF passed the U.S. National Institute of Standards and Technology statistical tests. Moreover, the PUF is used to implement XOR (exclusive‐OR)‐based text encryption and decryption, demonstrating its feasibility for Internet‐of‐things and edge applications.