Results 131 to 140 of about 201 (184)

Orbital Magnetic Moment Controlled Converse Magnetoelectric Effect in bcc‐Co3Mn/Fe/V/PMN‐PT Multiferroic Heterostructures

Advanced Science, EarlyView.
Based on orbital magnetic moment control, a material design strategy is proposed for a giant converse magnetoelectric effect in multiferroic heterostructures. This study will pioneer a promising route toward low‐power spintronic devices with an electric field.
Takamasa Usami, Yuichi Murakami, Ryota Watarai, Yu Shiratsuchi, Yoshihiro Gohda, Kohei Hamaya   +5 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Type‐II Dirac Fermions in Monolayer In2O: Interplay of Magnetotransport, Spin Hall Effect, and Superconductivity

Advanced Science, EarlyView.
First‐principles calculations reveal that monolayer In2O${\rm In}_2{\rm O}$ hosts type‐II Dirac fermions near the Fermi level, which split into Weyl points under spin‐orbit coupling. The material exhibits negative and giant magnetoresistance, a pronounced spin Hall effect, and phonon‐mediated superconductivity at 1.5 K, establishing it as a unique ...
Qing‐Bo Liu, De‐Ming Feng, Wen‐Neng Zhao, Yu‐Yang Zhao, Lun Xiong, Xing‐Yi Tan, Hua‐Hua Fu   +6 more
wiley   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Symmetry‐Driven Unconventional Magnetoelectric Coupling in Perovskite Altermagnets: From Bulk to the Two‐Dimensional Limit

Advanced Science, EarlyView.
The symmetry‐driven coexistence of altermagnetism and (anti)ferroelectricity in perovskites shows a strong dimensional dependence. Upon reducing the system from bulk to the two‐dimensional limit, only C‐type antiferromagnetic order retains ferroelectrically switchable altermagnetism, whereas A‐ and G‐type orders become conventional antiferromagnets ...
Zhou Cui, Ziye Zhu, Xunkai Duan, Bowen Hao, Xianzhang Chen, Jiayong Zhang, Tong Zhou   +6 more
wiley   +1 more source

Single‐Cell Dissection of Microglial Dysfunction in Diabetes‐Associated Neurodegenerative Vulnerability

Advanced Science, EarlyView.
Using single‐cell transcriptomic and epigenomic profiling, researchers mapped microglial dysfunction across the lifespan of db/db mice. The authors uncovered a nonlinear microglial remodeling featuring early inflammatory priming, a mid‐stage transcriptional inflection, and late dysfunction.
Jizhou Zhang, Tsz Kwan Yau, Joyce Tse, Tsz Ho Li, Dongjie Hu, Yong Juan Zhao, Ting‐Fung Chan   +6 more
wiley   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami

Advanced Science, EarlyView.
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning, Lu Lu, Sophie Leanza, Ruike Renee Zhao   +3 more
wiley   +1 more source