Results 101 to 110 of about 14,108,597 (163)
A magneto‐ionic security‐by‐materials‐design strategy exploits voltage‐driven N3– migration in selectively contacted FeCoN dots, creating reconfigurable sub‐15 nm ferromagnetic sublayers with deterministic and/or probabilistic (single‐domain↔vortex) states, voltage‐tunable probabilities and fully stochastic orientation/chirality.
Irena Spasojevic +4 more
wiley +1 more source
Physics‐Aware Machine‐Learning‐Driven Inverse Design of Broadband Ultra‐Open Acoustic Metamaterials
A physics‐aware machine‐learning framework enables inverse design of ultra‐open acoustic silencers by decoupling spectral and radial design spaces. The approach rapidly identifies broadband, compact, and highly ventilated architectures, while revealing hidden linear design rules that link geometry, impedance matching, and acoustic performance.
Zhiwei Yang +5 more
wiley +1 more source
Spatially Encoded Protocell Network for Non‐Cascaded Parallel Biocomputation
A non‐cascaded, hydrogel‐based proteinosome computational platform is developed, in which redox‐responsive proteinosomes serve as local computing units within a shared reaction–diffusion field. Reductant inputs, countered by an auxiliary glucose gradient, regulate spatially patterned proteinosome disruption, and generate population‐level boundaries ...
Shuqi Wu, Liangfei Tian
wiley +1 more source
Machine Learning of Temperature‐Dependent Chemical Kinetics Using Parallel Droplet Microreactors
An integrated droplet microfluidics and machine learning framework enables high‐throughput characterization of temperature‐dependent reaction kinetics. Time‐resolved measurements from thousands of droplets train Neural ODE models that accurately predict nonlinear reaction dynamics across diverse thermal environments, bridging large‐scale ...
Mamoru Saita, Yutaka Hori
wiley +1 more source
Battery‐Inspired Electrochemical Synapses for Neuromorphic Applications
Battery‐ion‐inspired synaptic devices integrate diverse electrolyte systems (solid, ion‐gel, liquid) with transition metal oxides, two‐dimensional materials, and organic channels to regulate ion‐electron coupling. By tailoring ion transport and host interactions, these platforms enable controllable plasticity and energy‐efficient implementations for ...
Won Woo Lee +6 more
wiley +1 more source
MetaboSense is a first‐of‐its‐kind microfluidic platform enabling continuous, in‐line monitoring of glucose and lactate during ex vivo lung perfusion. Combining a quantum dot–mediated aptamer assay with mixing, depletion, and optofluidic detection modules, it achieves 60–s temporal resolution and shows strong agreement with standard blood gas analyzers,
Sanjana Srikant +14 more
wiley +1 more source
Inverse Design of Pre‐Strain via a Predictive Electromechanical Model for Enhanced Strain Sensing
An analytical electromechanical model rooted in microcrack evolution mechanics is globally calibrated from only eight pre‐strain datasets, enabling prediction of the complete sensing response at untested pre‐strain values within the calibrated design space (R2 > 0.99).
Jia‐Chen Shang +10 more
wiley +1 more source
Electric‐field‐controlled antiferroelectric switching offers a ferroic pathway for reversible interconversion between symmetry‐distinct antiferromagnetic states in a two‐dimensional halide perovskite. A spin‐split altermagnet transforms into a spin‐degenerate type‐IV antiferromagnet through field‐driven structural symmetry reconstruction, enabling ...
Wan Zhao +7 more
wiley +1 more source
Programmable Topological Magnetic Textures in Above‐Room‐Temperature 2D Ferromagnet Fe3GaTe2
This work demonstrates the programmable generation and deterministic modulation of magnetic skyrmion bags with high‐order topological numbers in the above‐room‐temperature 2D ferromagnet Fe3GaTe2 (FGaT) via current‐pulse control. Furthermore, highly efficient electrical manipulation and current‐driven parallel motion of these high‐order topological ...
Hanqing Shi +8 more
wiley +1 more source
Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley +1 more source

