Results 111 to 120 of about 3,612,411 (192)
Coupled materials design enables a monolithic fiber that integrates complementary sensing regimes into a single wearable strand. By preserving informative signal features across subtle physiological deformation, large body motion, and mixed mechanical inputs, the dual‐gradient architecture generates synchronized, less redundant outputs that improve ...
Yunheum Lee +13 more
wiley +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
Closed‐Loop Solid‐State Synthesis Planning for Materials Discovery With Large Language Models
Leveraging literature data, we build a large‐language‐model‐driven workflow that extracts synthesis steps from 4407 papers, retrieves similar precedents, and generates candidate solid‐state synthesis recipes. The system benchmarks against ground‐truth and then operates in a closed loop with experiments to synthesize oxy‐selenide electrolyte materials ...
Dong Won Jeon +9 more
wiley +1 more source
Memristors offer tunable resistance and intrinsic instability, making them promising tunable noise sources. We propose a spiking‐rate‐programmable probabilistic neuron using a Ru/TaOx/Pt memristor, where resistance‐dependent noise enables frequency‐selective encoding.
Do Hoon Kim +8 more
wiley +1 more source
Using 640 curated electrolyte formulations, we apply data‐driven analysis to reveal how molecular features govern coulombic efficiency (CE) in lithium metal batteries. Fluorine content correlates positively with CE, while oxygen, carbon, and higher boiling points correlate negatively.
Minh Van Duong +6 more
wiley +1 more source
Artificial Intelligence Meets Micro/Nanorobotics
Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever +6 more
wiley +1 more source
Decoding Synergistic Pathways in Bimetallic MOFs for Advanced Oxidation Processes
This review presents a unified framework linking metal pairing and framework design with electronic structure, redox cycling, oxidant activation, reactive‐species generation, and catalytic performance across photocatalytic and oxidant‐based BMOF‐AOPs. The resulting design principles guide the development of hydrolytically stable and efficient BMOFs for
Karim El‐Naggar +2 more
wiley +1 more source
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh +5 more
wiley +1 more source
A 4‐layer Kevlar‐based composite is fabricated by combining ultrasonic spraying and electrostatic flocking. Carbon black dispersion is first deposited onto Kevlar fabric to create a conductive electrode. Nylon fibers are then electrostatically flocked onto the coated fabric, forming a dielectric layer.
Mengdi Chen +7 more
wiley +1 more source
Controlled Synthesis of Tri‐ and Multi‐Doped Graphene
This review systematically evaluates synthesis routes for tri‐ and multi‐doped graphene, from hydrothermal and pyrolysis methods to flash Joule heating, critically assessing how each governs dopant incorporation, bonding configuration, and resulting electronic properties.
Maria Hasan +4 more
wiley +1 more source

