Multifunctional triple-network ionic hydrogel sensors engineered by Al/Zn bimetallic salt solution: From cellulose solvent to conductive network architecture.

Ionic conductive hydrogels show promise for flexible sensors in wearables and e-skins, but balancing mechanical strength with high conductivity remains challenging. Herein, a triple-network ionic conductive hydrogel based on poly(acrylic acid) (PAA) was developed, synergistically reinforced by dissolved cellulose (dCel) and aramid nanofibers (ANF), with Al/Zn bimetallic ions serving as the conductive medium. Intriguingly, dCel was in-situ generated using the concentrated Al/Zn bimetallic salt solutions as the cellulose solvent, following the complete dissolution of the pulp fibers driven by the intensive ionic hydration of Al/Zn ions.

On-Demand Nanoliter Delivering Platform via Electrical-Activated Microdroplet Assembling.

Precise delivery of nanoliter-scale reagents is essential for high-throughput biochemical assays, yet existing platforms often lack real-time control and selective content fusion. Conventional methods rely on passive encapsulation or stochastic pairing, limiting both throughput and biochemical specificity. Here, we introduce an on-demand nanoliter delivery platform that seamlessly integrates electrical sensing, triggered droplet merging, and passive sorting in a single continuous flow.

Formulating cathode materials based on high-entropy strategies for sodium-ion batteries.

Sodium-ion batteries (SIBs) are promising alternatives to lithium-ion batteries (LIBs) owing to abundant resources and cost-effectiveness. However, cathode materials face persistent challenges in structural stability, ion kinetics, and cycle life. This review highlights the transformative potential of high-entropy (HE) strategies that leveraging multi-principal element synergies to address these limitations entropy-driven mechanisms.

Ultrahigh Sensitive Human Inspired Neurons for Artificial Nociceptor Systems.

Mimicking human brain functionalities with neuromorphic devices represents a pivotal breakthrough in developing bioinspired electronic systems. The human somatosensory system provides critical environmental information and facilitates responses to harmful stimuli, endowing us with good adaptive capabilities. However, current sensing technologies often struggle with insufficient sensitivity, dynamic response, and integration challenges.

Diverse Perovskite Solar Cells: Progress, Challenges, and Perspectives.

Perovskite materials have revolutionized optoelectronics by virtue of their tunable bandgaps, exceptional optoelectronic properties, and structural flexibility. Notably, the state-of-the-art performance of perovskite solar cells has reached 27%, making perovskite materials a promising candidate for next-generation photovoltaic technology. Although numerous reviews regarding perovskite materials have been published, the existing reviews generally focus on individual material systems (e.

Advanced Architectures and Emerging Materials for High-Operating-Temperature Infrared Photodiodes.

High-operating-temperature (HOT) mid-wavelength and long-wavelength infrared photodetectors have emerged as critical enablers for eliminating bulky cryogenic cooling systems, offering transfromative potential in developing compact, energy-efficient infrared technologies with reduced size, weight, power, and cost. Focusing on infrared photodiodes, this review first discusses the fundamental mechanisms limiting performance at elevated operating temperatures. Subsequently, the progress in conventional epitaxial semiconductors, such as HgCdTe, InAsSb, and III-V type-II superlattice is reviewed, highlighting the evolution of device architectures designed to effectively suppress dark currents and approach background-limited performance.

Tunable Superlinear Gallium Oxide Gate-All-Around Deep-Ultraviolet Phototransistor for Near-Field Imaging.

Superlinear photodetectors hold significant potential in intelligent optical detection systems, such as near-field imaging. However, their current realization imposes stringent requirements on photosensitive materials, thereby limiting the flexibility of the device integration for practical applications. Herein, a tunable superlinear GaO deep-ultraviolet gate-all-around (GAA) phototransistor based on a p-n heterojunction has been proposed.

Study of Ultranarrowband Silicon Nanowire Array Photodetector with Peak Spectral Responsivity at 1120 nm.

Near-infrared (NIR) narrowband photodetectors, featuring high sensitivity, excellent wavelength selectivity, and narrow full width at half-maximum (fwhm), enable efficient detection of specific NIR wavelengths and are widely used in optical communication, environmental monitoring, spectroscopy, and scientific research. In this study, we present a self-powered NIR photodetector based on a silicon nanowire (SiNW) array, exhibiting an ultranarrowband response centered at 1120 nm. The device employs a simple Schottky junction architecture.

CDLR-net: a ECG classification network based on deep residual shrinkage networks and LSTM.

Many traditional classification networks directly use the limb two-lead signal (MLII) ECG signals as input for training. However, this method suffers from reduced accuracy when ECG features are not obvious, especially for premature heartbeats. To solve the issue, this paper proposed a novel network, namely CDLR-Net, that combines a Deep Residual Shrinkage Network (DRSN) with a Long Short-Term Memory (LSTM).

GaN/PDMS-based opto-electro-mechanical tactile sensors.

Tactile sensors are crucial in robotics and medical diagnostics, requiring precise real-time detection. However, the development of a compact sensor that can measure force across a wide range, with high resolution and rapid response along three axes, remains extremely limited. Herein, an opto-electro-mechanical tactile sensor is reported, utilizing a monolithically integrated GaN-based optochip with a fingerprint-patterned polydimethylsiloxane (PDMS) film.

Enhanced Surface Pseudocapacitance in 3D Hierarchical FeSe Rod-Clusters Enabling High-Rate and Long-Term Sodium Storage.

FeSe is highly prone to structural degradation during repeated (de)sodiation reactions, leading to inferior rate performance and poor cycling stability, which significantly limits its application. Herein, 3D hierarchical rod-clusters assembled from FeSe submicron rods are successfully synthesized through seleniumization with dissolution-reassembly and the subsequent annealing process. The submicron rods can facilitate rapid sodium-ion diffusion and release structural stress, which is conducive to maintaining structural integrity during prolonged cycling.

GIMS: Image matching system based on adaptive graph construction and graph neural network.

Feature-based image matching has extensive applications in computer vision. Keypoints detected in images can be naturally represented as graph structures, and Graph Neural Networks (GNNs) have been shown to outperform traditional deep learning techniques. Consequently, the paradigm of image matching via GNNs has gained significant prominence in recent academic research.

Heart failure diagnosis and ejection fraction classification via feature fusion model using non-contact vital sign signals.

Background And Objectives: Ballistocardiography (BCG) has emerged as a promising modality for home-based heart failure (HF) monitoring, yet existing single-dimensional manual feature analyses fail to adequately characterize left ventricular ejection fraction (LVEF < 40%) dynamics. We address this limitation by developing a hybrid feature fusion framework that synergizes manual feature engineering with deep learning for improved HF diagnosis and LVEF classification.

Methods: 83 participants were recruited from a hospital, with their samples categorized into two (healthy and HF) and three classes (healthy, LVEF ≥ 40% HF, and LVEF < 40% HF) based on clinical diagnosis.

3D-Printed KVPOF/rGO Aerogel Electrodes as High-Performance 5V-Class Cathode for Advanced Potassium-Ion Battery.

A porous KVPOF/reduced graphene oxide (KVPF/rGO) microgrid aerogel electrode is designed and fabricated using direct ink writing 3D printing for high-performance potassium-ion battery cathodes. This 3D-printed KVPF/rGO aerogel electrode, which integrates well-dispersed KVPOF microspheres in the reduced graphene oxide matrix, shows enhanced structural integrity and electrical conductivity, thereby facilitating efficient ion and electron transport. The KVPF/rGO electrode achieves a reversible discharge capacity of 99.

Synergistic Dual-Anchor Passivation at Buried Interfaces Enabling High-Efficiency and Stable Perovskite Solar Cells.

The buried interfacial nonradiative recombination and carrier transport losses in perovskite solar cells, particularly caused by oxygen and iodide vacancy defects at the SnO/perovskite interface, critically limit their efficiency and stability. Herein, we propose a bifunctional passivation strategy using guanidinium phosphate (GAP), which spatially separates phosphate and guanidine groups to synergistically anchor SnO and perovskite interfaces. We systematically demonstrate the multifunctional synergistic roles of GAP molecules at the SnO/perovskite buried interface, where phosphate groups establish robust coordination bonds with the SnO surface to passivate oxygen vacancy defects while optimizing interfacial energy level alignment.

Solar-Driven Redox Reactions with Metal Halide Perovskites Heterogeneous Structures.

Metal halide perovskites (MHPs) with striking electrical and optical properties have appeared at the forefront of semiconductor materials for photocatalytic redox reactions but still suffer from some intrinsic drawbacks such as inferior stability, severe charge-carrier recombination, and limited active sites. Heterojunctions have recently been widely constructed to improve light absorption, passivate surface for enhanced stability, and promote charge-carrier dynamics of MHPs. However, little attention has been paid to the review of MHPs-based heterojunctions for photocatalytic redox reactions.

Ultrathin Gallium Nitride Quantum-Disk-in-Nanowire-Enabled Reconfigurable Bioinspired Sensor for High-Accuracy Human Action Recognition.

Human action recognition (HAR) is crucial for the development of efficient computer vision, where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks across sensor-processor interfaces. However, the absence of interactions among versatile biomimicking functionalities within a single device, which was developed for specific vision tasks, restricts the computational capacity, practicality, and scalability of in-sensor vision computing. Here, we propose a bioinspired vision sensor composed of a GaN/AlN-based ultrathin quantum-disks-in-nanowires (QD-NWs) array to mimic not only Parvo cells for high-contrast vision and Magno cells for dynamic vision in the human retina but also the synergistic activity between the two cells for in-sensor vision computing.

Dual-Modal Ex Vivo Vascular Culture and Imaging System Facilitates Research on Vascular Changes under Hyperglycemic and Hypoxic Conditions.

Diabetic microvascular complications result from complex vascular remodeling influenced by hyperglycemia and hypoxia. However, there is currently no comprehensive method for systematically studying their combined effects on overall vascular morphology and perfusion function. To address this, a dual-modal ex vivo vascular culture and imaging system is developed.

Supramolecular surface modification of ceria nanoparticles for enhanced chemical mechanical planarization performance in shallow trench isolation.

Chemical mechanical planarization (CMP) is an indispensable technique for achieving global planarization in shallow trench isolation (STI) structures, a critical component in modern integrated circuits. With the continuous advancement of technology and increasing demands for chip performance, the critical metrics of STI CMP processes have become increasingly stringent, placing higher requirements on the performance of polishing slurries. In particular, SiO/SiN removal rate selectivity (RRS) and surface flatness directly impact product quality and yield.

Solvent engineering enables tin-lead perovskite films with long carrier diffusion lengths and reduced tin segregation.

All-perovskite tandem solar cells offer great promise for achieving low levelized cost of electricity, but their performance remains limited by insufficient near-infrared photon absorption in narrow bandgap tin-lead (Sn-Pb) subcells. Micron-thick Sn-Pb layers are essential for maximizing absorption, yet high-concentration precursor solutions often cause non-uniform crystallization, stoichiometric imbalance and limited carrier diffusion lengths. Here we identify the root cause of these limitations as the insufficient coordination of tin(II) iodide (SnI) in conventional dimethylformamide (DMF)/dimethyl sulfoxide (DMSO) binary solvent system at high precursor concentrations, resulting in Sn-rich colloids that nucleate detrimental Sn-rich phases in final films.

Ambipolar ohmic contact to silicon for high-performance brain-inspired image sensors.

Recently, ambipolar semiconductor devices have excelled in developing programmable photodiodes for brain-inspired image sensors, offering energy, speed, and security gains. However, the lack of mature processing techniques makes their manufacture challenging, and the often-adopted Schottky contacts limit their performance. Although CMOS technology is successful in integrated circuits, the employed ohmic contacts can only transport one type of carriers, failing to meet the requirement of electrons and holes working simultaneously in ambipolar devices.

Total Ionizing Dose Effect Simulation Modeling and Analysis for a DCAP Power Chip.

In this paper, a systematic study on performance degradation of a 0.18 μm BCD-process DCAP (Direct connection to the output CAPacitor) power chip under a total-dose radiation environment is carried out. The effects of total-dose radiation on the electrical characteristics of an MOS device are analyzed through device-level simulation.

Research on Switching Current Model of GaN HEMT Based on Neural Network.

The switching characteristics of GaN HEMT devices exhibit a very complex dynamic nonlinear behavior and multi-physics coupling characteristics, and traditional switching current models based on physical mechanisms have significant limitations. This article adopts a hybrid architecture of convolutional neural network and long short-term memory network (CNN-LSTM). In the 1D-CNN layer, the one-dimensional convolutional neural network can automatically learn and extract local transient features of time series data by sliding convolution operations on time series data through its convolution kernel, making these local transient features present a specific form in the local time window.

Design and Fabrication of Embedded Microchannel Cooling Solutions for High-Power-Density Semiconductor Devices.

The rapid development of high-power-density semiconductor devices has rendered conventional thermal management techniques inadequate for handling their extreme heat fluxes. This manuscript presents and implements an embedded microchannel cooling solution for such devices. By directly integrating micropillar arrays within the near-junction region of the substrate, efficient forced convection and flow boiling mechanisms are achieved.

A 0.049 mm 0.5-to-5.8 GHz LNA Achieving a Flat High Gain Based on an Active Inductor and Low Capacitive ESD Protection.

This paper introduces a 0.5-5.8 GHz low-noise amplifier (LNA) incorporating a gyrator-C-based active inductor (AI) and an enhanced deep trench isolation (DTI) electrostatic discharge (ESD) diode.