Search Results (307)

To address prevalent industrial challenges, including the high cost of fabricating microstructures via photolithography and 3D printing, impurity residues easily generated by conventional physical/chemical pore-forming techniques, and the limited sensitivity of regular capacitive sensors, this paper innovatively proposes an integrated low-temperature in situ gas foaming strategy using ammonium bicarbonate for the fabrication of porous TPU-based ionic gels. Relying on the complete gaseous decomposition property of ammonium bicarbonate upon heating, a three-dimensionally interconnected continuous porous network is spontaneously constructed inside the polymer matrix. Thermoplastic polyurethane (TPU) is selected as the continuous polymer phase, and [EMIM][TFSI] imidazolium ionic liquid is blended as the ion source to synthesize composite ionic gel substrates. A PDMS composite slurry filled with graphene is employed to prepare flexible substrates, followed by low-temperature oxygen plasma surface modification to introduce polar functional groups such as hydroxyl and carboxyl onto electrode surfaces. A standard sandwich-structured ionic pressure sensor with the configuration of “top modified electrode—porous ionic gel dielectric layer—bottom modified electrode” is finally assembled. The porous framework and modified electrodes constitute a dual synergistic enhancement system: the porous structure markedly reduces the equivalent elastic modulus of the gel and improves its compressive deformation capacity; polar-modified electrodes optimize the interfacial compatibility between electrodes and gels, shorten ion migration paths and lower interfacial contact resistance. Systematic calibration of multiple batches of parallel samples reveals that the as-fabricated sensor achieves a high sensitivity of 25.3 kPa⁻¹ across the full measuring range from 0 to 1000 kPa with a linear fitting coefficient R² = 0.992. The loading response time and unloading recovery time of the device are 60 ms and 80 ms respectively, with a performance degradation of less than 3% after 1000 consecutive loading–unloading cycles, featuring low hysteresis error and excellent signal repeatability. Multi-scenario in vivo wearable tests on human subjects verify that the device can precisely capture subtle fluctuations of radial artery pulse and periodic laryngeal deformation during swallowing, distinguish characteristic waveform patterns of various English words according to differences in vocal cord vibration, and accurately detect bending motions when attached to finger joints. The entire fabrication process adopts common chemical raw materials and standard laboratory equipment without expensive micro-nano processing facilities, featuring convenient raw material procurement and high process fault tolerance, which enables large-area coating-based mass production. This work delivers a novel technical route for the low-cost large-scale production of high-performance ionic flexible sensors and bears significant industrialization reference value for applications in wearable medical monitoring, bionic robotic electronic skin, flexible human–machine interactive touch panels and other related fields. Full article

The high penetration of renewable energy has exposed integrated energy systems (IES) to stronger source-load uncertainties. Traditional scheduling methods that primarily pursue economic optimality often fail to account for system regulation margins, which may lead to excessive charging and discharging of energy storage systems, frequent fluctuations in unit output, and insufficient supply–demand matching capability under uncertain operating scenarios. To address these issues, this paper proposes a Flex-TD3 optimal scheduling method for IESs with embedded flexibility rules. First, a regional IES model incorporating photovoltaic generation, wind power, micro-gas turbines, gas boilers, electric chillers, waste heat recovery units, heat exchangers, and battery energy storage systems is established to describe the coupling relationships among electricity, heat, cooling, and gas flows, as well as the operational constraints of key devices. Second, active regulation flexibility indicators are constructed from the perspectives of system upward regulation capability, downward regulation capability, energy storage state health, and electro-thermal decoupling regulation margin. A comprehensive flexibility score is then formulated to characterize the system’s capability to cope with renewable energy fluctuations and load disturbances under the current operating state. Third, the flexibility indicators are embedded into the state space and reward function of the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, and a rule-based physical feasibility mapping mechanism is introduced to modify the raw scheduling actions generated by the agent according to device operational constraints, thereby enhancing the physical consistency and operational safety of the scheduling strategy. Case study results show that, compared with traditional optimal scheduling methods, the proposed method achieves better overall performance in terms of training convergence speed, operational economy, and scheduling stability. It can effectively reduce system operating costs, improve renewable energy accommodation capability, and decrease renewable energy curtailment, supply shortages, and constraint violations. Under uncertain scenarios involving renewable energy prediction errors, load disturbances, and high renewable energy penetration, the proposed method still maintains favorable scheduling performance, demonstrating its effectiveness and robustness. Full article

Resource-constrained wearable systems often need to be able to execute signal processing and AI workloads. There are many trade-offs to consider for this type of application. This paper presents a lightweight convolution-aware soft processor for embedded signal-processing on resource-constrained wearable devices. This architecture represents a middle ground for signal-processing applications between dedicated accelerators and lightweight soft processors. The proposed architecture integrates a two-lane SIMD integer datapath with a split-stage IEEE-754 floating-point accumulation pipeline. The split-stage design enables overlap between multiplication, accumulation, and operand fetch, improving arithmetic utilization while maintaining low resource costs. The processor was implemented on the Artix-7-based Basys3 platform and evaluated using one-dimensional convolution workloads. The experimental results demonstrate a $6\times$ speedup over MicroBlaze-class soft processors while maintaining the same static power usage (0.073 W), and only requiring 44% higher dynamic power consumption. The architecture achieves this with significantly fewer FPGA resources than accelerator-based solutions such as DPU overlays. The proposed architecture provides a practical alternative for wearable and resource-constrained FPGA systems requiring deterministic convolution performance, demonstrating a balanced design point for embedded wearable platforms where software-defined flexibility and convolution acceleration are both required. Full article

High penetration of wind and photovoltaic (PV) generation increases renewable uncertainty and real-time balancing pressure in active distribution networks. To address this problem, this paper proposes a two-stage robust optimization method for day-ahead and real-time scheduling of a flexibly interconnected multi-microgrid (MMG) system enabled by a flexible interconnection device (FID). The proposed framework jointly optimizes power purchase from the upper-level distribution network, micro-gas turbine output, energy storage system (ESS) operation, and FID-based bidirectional power exchange, thereby coordinating local temporal flexibility and inter-microgrid spatial flexibility. A polyhedral uncertainty set is used to model wind and PV forecast errors, and the problem is solved by the column-and-constraint generation (C&CG) algorithm. Case studies on a two-microgrid system show that, compared with independent operation under traditional robust optimization, the proposed method reduces real-time balancing cost, wind and PV curtailment, and total operating cost by 98.96%, 95.84%, and 0.59%, respectively. Sensitivity analysis further verifies the economy–robustness trade-off under different uncertainty budgets and forecast deviation levels. Full article

Nanofiber-based structures have shown considerable potential in semiconductor-related applications, including ultra-thin dielectric layers and flexible electronic devices, owing to their tunable micro-/nanoscale morphology. However, the manufacturing of these structures is often hindered by the complex multiparameter coupling and poor reproducibility inherent in conventional electrospinning processes. To address these challenges, this study develops an intelligent optimization framework for gas-assisted electrospinning by integrating Large Language Models (LLMs) with Bayesian Optimization (BO). A Gaussian Process Regression (GPR) surrogate model was established to navigate the high-dimensional parameter space efficiently. Comparative studies demonstrate that the proposed BO+LLM strategy not only outperforms pure data-driven BO and pure knowledge-driven LLM approaches but also surpasses the conventional Response Surface Methodology (RSM) baseline, successfully locating a verified minimum fiber diameter of 239 nm. Furthermore, through response-surface analysis, this work identifies a specific multiphysics collaborative window where electrostatic stretching and aerodynamic assistance are balanced. These findings provide a robust pathway for the reproducible fabrication of nanofiber-based electronic devices. Full article

Against the backdrop of global energy structure decarbonization, distributed transformation, and the rapid development of low-power electronic devices and sensor networks, micro-energy supply and intelligent sensing have emerged as critical bottlenecks limiting their large-scale application. Triboelectric nanogenerators (TENGs), leveraging advantages such as compatibility with diverse materials and adaptability to flexible and miniaturized fabrication, can efficiently harvest widely available low-frequency, low-amplitude distributed mechanical energy in the environment. Additionally, they exhibit self-powered sensing characteristics, where output signals are directly correlated with external physical quantities, demonstrating unique strengths in the fields of micro-/nano-energy and intelligent monitoring. This article systematically reviews the research progress in TENGs; elucidates their working modes and power generation principles; summarizes material design, structural optimization, and performance enhancement strategies for efficient energy harvesting; and outlines the current state of self-powered sensing technologies. It highlights their engineering applications in intelligent monitoring scenarios such as drones, marine environments, infrastructure, and wearable devices. Addressing the existing technical bottlenecks and theoretical challenges in integrated energy harvesting–sensing–monitoring systems, the paper envisions future trends toward high performance, integration, and intelligence, providing valuable insights for fundamental research on and engineering applications of TENGs in micro-energy supply and intelligent monitoring. Full article

Broadband antireflective surface technology constitutes a crucial technique in optoelectronic devices, playing a key role in reducing optical losses. Ultrafast laser processing provides a flexible route for fabricating micro-nano structures on metallic surfaces because it enables efficient fabrication, high spatial resolution, and minimal chemical consumption. This study uses a variable-angle scanning strategy to texture the copper surface, produce a series of antireflection arrayed micro-nano structures, and study the spectral reflectance characteristics of the copper surface. The results exhibit that 90° orthogonal scanning favors the formation of an arrayed microcone structure, which shows lower reflectance than the non-orthogonal scanning strategies in the 200–1300 nm band, with a minimum reflectance of 0.94%. The 60° and 45° cross-scanning based on the non-orthogonal strategy favors the formation of microcavity structures, and shows low reflectance in the 1300–2500 nm band, with the maximum reflectance remaining below 5%. Laser-induced periodic surface structures (LIPSS) are observed on the structures fabricated by all strategies. This work demonstrates that the scanning angle itself can be used to switch the dominant surface morphology and thereby tailor the spectral antireflection response, and lies in establishing a clear processing–structure–spectral response relationship for copper surfaces, which provides a designable route for wavelength-selective optical absorption in photothermal conversion, infrared detection, and sensing applications. Full article

The precise fabrication and controllable actuation of magnetic microspheres hold significant application value in biomedicine, microfluidic chips and other fields. Based on femtosecond laser two-photon polymerization technology (FLTPP), two methods are adopted to prepare magnetic microspheres in this study. Magnetic microspheres are fabricated via photoresist modification and post-treatment processes. Meanwhile, a 3D magnetic actuation system composed of a three-axis movable magnetic drive module and a real-time imaging system is constructed, enabling the flexible 3D actuation and real-time dynamic monitoring and visualized observation of magnetic microspheres. The results demonstrate that the magnetic microspheres exhibit sensitive magnetic response characteristics. The constructed magnetic actuation system features large travel range (XY: ±6.5 mm, Z: 10 mm), high precision (20 μm) and flexible manipulation, enabling stable locomotion of the microrobots in straight channels, L-shaped channels, and square channels. This study provides a technical reference for the fabrication and manipulation of magnetic micro/nano devices, and lays a foundation for their subsequent integrated applications in microfluidic systems. Full article

Flexible acceleration sensors demonstrate revolutionary potential in healthcare, structural vibration monitoring, and consumer electronics owing to their unique conformal adhesion capability and mechanical adaptability. However, current academic research presents two distinct paradigms for realizing flexibility: one is the hybridly flexible sensor, which incorporates traditional micro-electro-mechanical System (MEMS) acceleration sensor chips with flexible packaging/substrates; the other is the intrinsically flexible sensor, whose sensing unit and substrate are entirely composed of flexible materials enabled by microstructural design. This review first analyzes the fundamental differences and design challenges between these two flexible architectures. It then systematically elucidates five core sensing mechanisms—capacitive, piezoresistive, triboelectric, piezoelectric, and electromagnetic—comparing their working principles, material systems, structural designs, and performance metrics. Among these, piezoelectric and triboelectric types exhibit distinctive advantages in self-powering capability, whereas resistive and capacitive approaches offer greater ease of integration. Furthermore, the applications of intrinsically flexible acceleration sensors in structural health monitoring, wearable devices, automotive safety, and other fields are discussed, with particular emphasis on their unique strengths in real-time vibration monitoring. Finally, the review summarizes existing challenges, such as the trade-off between sensitivity and flexibility, and provides theoretical insights to guide future innovations in intrinsically flexible acceleration sensor technology. Full article

Benefiting from their outstanding porosity, considerable specific surface area, and natural flexibility, cellulose nanofibers (CNFs)/MOF materials have emerged as competitive candidates for advanced flexible energy storage devices. However, conventional CNFs/MOFs aerogels or films often suffer from poor recoverability under compression, bending, and folding, accompanied by severe plastic deformation that compromises the cycling and structural stability of devices. To address this issue, we report a rationally designed flexible PU/CNFs/ZIF-8/PANI composite foam with an interconnected micro-mesoporous structure. Using polyurethane foam as a soft substrate and CNFs/ZIF-8 as building blocks, the composite was fabricated through a combined strategy of impregnation, in situ ZIF-8 growth, hot-pressing, and in situ aniline polymerization with simultaneous etching of the ZIF-8. The incorporation of carboxylated CNFs enhances the hydrophilicity of the PU skeleton. This, in combination with the hot-pressed framework, establishes an interconnected 3D network, thereby effectively preventing the agglomeration of active materials. Meanwhile, the hierarchical pores derived from the sacrificial ZIF-8 template provide abundant electroactive sites, accelerate ion transport, and facilitate high PANI loading. By virtue of this synergistic architectural effect, the resultant electrode achieves a high specific capacitance of 449 F/g at 0.2 A/g, with 97% capacitance retention after 2000 cycles at 5 A/g. Furthermore, the composite foam demonstrates excellent mechanical flexibility, with a tensile strength of 0.87 MPa and an elongation at break of 230%. This work offers a feasible approach for developing high-performance flexible supercapacitors and provides novel perspectives for the rational design of portable energy storage devices. Full article

Myogenic mechanobiology governs how mechanical cues regulate myocyte organization, alignment, and functional maturation; however, in vitro platforms that enable quantitative control and real-time readout of myogenic mechanical microenvironments remain limited. Here, we engineered a pneumatic-driven organ-on-a-chip platform integrating six parallel culture units and a bead-embedded flexible PDMS membrane to deliver cyclic mechanical strain and enable quantitative stress–strain mapping in cardiomyocytes and skeletal muscle cells. Finite element-guided optimization ensured effective membrane deformation, and the platform generated stable and tunable cyclic strain with a strong linear relationship between applied negative pressure (50–700 mbar) and membrane stress and strain. Plasma treatment combined with type I collagen coating restored myogenic cell adhesion and growth on PDMS to levels comparable to standard culture conditions. Under 13% cyclic strain, both cardiomyocytes and skeletal muscle cells exhibited pronounced and highly uniform alignment, with cellular polarity oriented perpendicular to the stretch axis. Moreover, cyclic loading significantly enhanced the expression of contractile maturation markers, including MYH7 in cardiomyocytes and MYH6 in skeletal muscle cells (all p < 0.05), whereas expression of the differentiation regulator MyoG remained unchanged, indicating that mechanical stimulation preferentially promotes structural organization and contractile maturation rather than lineage commitment. Collectively, this quantitatively programmable organ-on-a-chip represents a bioengineered microdevice for studying myogenic mechanobiology, revealing conserved mechanosensitive alignment and maturation responses across myogenic lineages and providing a versatile framework for biomedical engineering research, disease modeling, and mechanotherapeutic screening. Full article

In micro-opto-electro-mechanical systems (MOEMS), the micro-optical cavity plays a pivotal role. As performance requirements for MOEMS devices continue to rise, these cavities must achieve higher performance levels while simultaneously reducing their physical footprint. However, existing high-precision micro-optical cavities face challenges such as high process sensitivity and conflicting trade-offs between dynamic range and precision. To address these issues, piezoelectric thin-film actuators present a viable solution due to their high precision, stroke flexibility, electromagnetic interference resistance, and structural scalability. This study proposes a piezoelectric thin-film actuator based on the $d_{33}$ mode. The device adopts an island-circular structure that integrates a lead zirconate titanate (PZT) piezoelectric film with metal electrodes. By employing particle swarm optimization (PSO) to enhance displacement output and anti-gravity capabilities, the actuator achieves displacement outputs below 100 nm within a compact form factor while maintaining nanometer-level resolution. Simulation and experimental results confirm a first-order natural frequency of approximately 5.8 kHz, along with a reasonable linear displacement response across a 4–6 V drive voltage range. Furthermore, the device demonstrates functionality within a Fabry–Pérot (F-P) microcavity system, enabling active optical path length modulation through precise cavity tuning. This research provides an effective approach to enhancing the dynamic performance and process compatibility of micro-optical cavity devices, advancing the development of next-generation MOEMS systems. Full article

High-resolution, multi-modal neural interfaces are essential for advancing systems neuroscience and brain–computer interface technologies. This study designed and fabricated a 128-channel comb-shaped flexible micro-electrode array. The device integrates a biocompatible Parylene substrate with a flexible thin-film microprobe array, enabling simultaneous recording of electrocorticography (ECoG), intracortical local field potentials (LFP), and neuronal action potentials (spikes) from the cortical surface and superficial layers. Microelectrode sites were modified with platinum black nanoparticles, significantly reducing impedance. In vivo experiments in rats demonstrated the array’s ability to capture high-fidelity signals across different recording depths. Key findings included the acquisition of opposing LFP trends and polarity reversals between adjacent channels, reflecting local microcircuit dynamics. The array also reliably recorded neural activity during audiovisual cross-modal sensory stimulation. These results validate the device as an effective tool for multi-scale electrophysiology, successfully balancing high spatial resolution and signal quality with minimal tissue invasiveness, thereby offering significant potential for fundamental research and neural engineering applications. Full article

Microfluidics provides precise control of microscale fluid transport and has become central to biomedical, pharmaceutical, and industrial technologies. However, conventional fabrication methods such as photolithography and soft lithography require cleanroom facilities, use costly materials, and offer limited capability for constructing complex or multi-material architectures. This review highlights emerging manufacturing strategies, focusing on polymer-based micro-milling as an accessible and cost-effective alternative for microfluidic device production. Advances in micro-milling now enable the fabrication of microchannels and functional features with improved dimensional accuracy and surface quality, while additive manufacturing offers complementary rapid prototyping and design flexibility. Micro-milling is particularly promising for rapid prototyping of polymeric biosensor chips designed for point-of-care diagnostics. The technique supports diverse materials and eliminates reliance on cleanroom processing. Critical parameters, including tool geometry, spindle speed, and feeding rate, strongly influence fidelity and surface roughness, which directly affect biosensor sensitivity. Despite its advantages, challenges such as tool wear, burr formation, and limits on minimum feature size continue to hinder reproducibility. Recent progress in toolpath optimization, hybrid additive–subtractive methods, and real-time process monitoring shows the potential to overcome these barriers. Overall, micro-milling offers a scalable and economical route for fabricating accessible microfluidic and biosensing platforms, with future work needed to standardize processes and improve integration with surface functionalization methods. Full article

Microcontact stamping is a promising microfabrication technique for producing functional patterned thin films on flexible substrates; however, systematic optimization of its process parameters for thermochromic applications remains limited. In this study, we present a comprehensive parametric optimization of the microcontact stamping process to fabricate thermochromic pigment-coated thin films with rapid and reversible color responses. The effects of liquid resin type, SU-8 mold thickness, polydimethylsiloxane (PDMS) mixing ratio, and pattern size on pattern fidelity and thermochromic performance were systematically investigated. The optimal conditions were identified as a UV-curable resin, a 600 µm-thick SU-8 mold, a PDMS base-to-curing-agent ratio of 5:1, and a pattern size of 125 × 125 µm². Under these conditions, the stamped thermochromic films exhibited uniform micro-patterns, rapid response and recovery behavior, and stable reversible color changes over 20 consecutive thermal cycles. This work provides practical guidelines for parameter-controlled microcontact stamping of functional thin films and demonstrates its potential for scalable fabrication of thermochromic micro-patterns. The proposed approach is expected to contribute to the development of flexible and wearable electronic devices, smart displays, and thermally responsive sensing platforms. Full article