Results 171 to 180 of about 640,129 (261)

Optoelectronic‐Driven van der Waals Ferroelectric Materials‐Based Memory Devices for Retinomorphic and In‐Sensory Hardware

open access: yesAdvanced Science, EarlyView.
2D ferroelectrics materials enabling non‐volatile polarization memory, optical excitability, and neuromorphic processing within a unified material and provides a mechanistic analysis of polarization‐induced band modulation, including photon‐assisted domain reorientation, switching kinetics, and interfacial dipole coupling that governs resistive ...
Parthasarathi Pal   +3 more
wiley   +1 more source

Distinct Biotypes of Visual Perception in Major Depressive Disorder

open access: yesAdvanced Science, EarlyView.
In a discover dataset (272 acute MDD patients), this work identifies a novel depression biotype characterized by impaired visual motion perception, using machine learning clustering. An independent dataset confirms the robustness of this biotype through cross‐validation and demonstrates its generalizability.
Zhuoran Cai   +13 more
wiley   +1 more source

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

open access: yesAdvanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang   +6 more
wiley   +1 more source

Enhanced High Dimensionality and the Information Processing Capacity in Interfered Spin Wave‐Based Reservoir Computing, Achieved With Eight Detectors

open access: yesAdvanced Electronic Materials, EarlyView.
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa   +6 more
wiley   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin   +7 more
wiley   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

open access: yesAdvanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu   +6 more
wiley   +1 more source

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