Results 71 to 80 of about 1,424,413 (197)

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +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

Molecular Editing Reveals a Bilobalide Chemotype that Attenuates Prolyl Endopeptidase (PREP)‐Linked Neuroinflammation

Advanced Science, EarlyView.
Molecular editing of bilobalide uncovers BB56, a PREP‐engaging chemotype with enhanced anti‐inflammatory activity in microglia. Integrated CETSA‐MS, SAR, and pathway analyses link BB56 to attenuation of p38 MAPK/NF‐κB and NLRP3‐associated inflammatory signaling, highlighting bilobalide editing as a strategy for developing neuroinflammation‐modulating ...
Chanin Sillapachaiyaporn, Wenjing Wang, Yao Qin, Lili Yan, Stephan Scheeff, Xu He, Qiong Wu, Yue Lin, Jinsai Shang, Xin Ye, Jing Liu, Kailei Sun, Chun Wai Yeung, Junzhe Huang, Zhenghui Chen, Xiaodong Liu, Yiqun Geng, Shannon Wing Ngor Au, Bonaventure Y. Ip, Ho Ko, Billy Wai‐Lung Ng   +20 more
wiley   +1 more source

Remote Magnetomechanical Neuromodulation Uncovers Therapeutic Mechanisms for Alleviating Parkinsonian Symptoms in Freely Moving Mice

Advanced Science, EarlyView.
Magnetomechanical neuromodulation using magnetic nanodiscs enables remote activation of neurons. In a hemiparkinsonian mouse model, alternating magnetic fields actuate the nanodiscs to generate torque that opens mechanosensitive ion channels within the subthalamic nucleus, thereby modulating basal ganglia motor circuitry.
Anouk Wolters, Lorenzo Signorelli, Christian Herff, Sophia Gimple, Renzo Riemens, Gunter Kenis, Kim Rijkers, Hamed Shabani, Jyh‐Jang Sun, Yasin Temel, Hans Clusmann, Danijela Gregurec, Sarah‐Anna Hescham   +12 more
wiley   +1 more source

Palatable‐Food–Driven Top‐Down Circuit Inhibits PVNCRF Activity to Mitigate Stress Via Peri‐PVNCRFR1 Neurons

Advanced Science, EarlyView.
Palatable food alleviates stress and prevents anxiety. This study uncovers a dedicated neural pathway: dopamine release in the PFC activates D1R neurons, whose projections to the peri‐PVN engage a population of anxiolytic CRFR1 neurons. These neurons then inhibit stress‐induced hyperactivity of PVNCRF neurons, providing a circuit‐level explanation for ...
Yuchuan Hong, Shirui Jun, Tianjiao Deng, Gaojie Shao, Dan Liu, Yi Sun, Yan Chen, Qian Xiao, Jie Shao, Sheng Wang, Tianwen Huang, Fan Yang, Jie Tu   +12 more
wiley   +1 more source

Flexoelectricity in Photoconversion: Fundamentals, Materials, and Outlooks

Advanced Science, EarlyView.
Mechanical bending of a flexible cantilever induces a strain gradient in the photoactive material. The resulting flexoelectric field couples with photovoltaic and photoconductive effects, modulating charge generation, separation, and collection. A comparative analysis of oxide perovskites, halide perovskites, and two‐dimensional materials is presented,
Xiang Huang, Feng Li, Rongkun Zheng
wiley   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

Advanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su, Yanda Zhu, Hao Peng, Manman Li, Xuzihan Zhang, Meixiao Wu, Siyuan Zhang, Yuhan Zeng, Jiwen Liao, Ming Luo, Hetaishan Huang, Yutong Wang, Sean Li, Wenxian Li   +13 more
wiley   +1 more source

Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors

Advanced Science, EarlyView.
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu, Fumiaki Iwane, Minsu Zhang, Leonardo G. Cohen, José del R. Millán   +4 more
wiley   +1 more source