Results 51 to 60 of about 1,594 (169)
Scan‐Path‐ and Initial‐State‐Dependent Superdomain Switching in (111)‐Oriented PZT
Scan trajectory and initial superdomain topology govern polarization switching in (111)‐oriented PZT. Automated AFM writing, pulsing experiments, and interferometric 3D‐PFM show that raster scans reproducibly stabilize ordered Type‐I stripe superdomains with constrained variant selection, whereas spiral trajectories generate frustrated mixed‐variant ...
Rama Vasudevan +11 more
wiley +1 more source
Pulse‐protocol optimization in an Au/MoO3/TiO2/FTO bilayer memristor enables linear analog synaptic conductance modulation along with digital resistive switching for memory. Controlled filament evolution produces stable learning‐forgetting characteristics with low nonlinearity, resulting in significantly enhanced neural network inference accuracy for ...
Girish Chandrashekar +2 more
wiley +1 more source
Design Principles of Electrocatalysts for Industrial‐Scale Water Electrolysis
This Review distills electrocatalyst design for industrial‐scale water electrolysis into integrated principles linking active‐site engineering, phase and lattice modulation, interfacial microenvironment regulation and mass‐transport control. By connecting catalyst families with HER/OER mechanisms and practical operating demands, it outlines pathways ...
Hong Tang, Cui Ce, John Wang
wiley +1 more source
Return and Volatility Spillovers Among Major Cotton Markets
ABSTRACT This study explores return and volatility transmission among major cotton markets. Several events have disrupted cotton supply and demand in recent years, leading to heightened price volatility and significant shifts in market interconnections.
Susmitha Kalli +3 more
wiley +1 more source
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source
Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira +13 more
wiley +1 more source
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo +5 more
wiley +1 more source
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source

