Results 181 to 190 of about 65,604 (247)

Improving Reliability of Machine Learning Interatomic Potentials with Physics-Informed Pretraining. [PDF]

J Chem Inf Model
Zheng Q, Fung V.
europepmc   +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

Physics-Informed Machine Learning Correction of Variational Quantum Eigensolver Energies for Molecular Ground States. [PDF]

ACS Omega
Sree KCS, Shankar V.
europepmc   +1 more source

Construction of Sabatier Volcanoes for CO2 Hydrogenation to C1‐2 Oxygenates Using Data‐Efficient Machine Learning

Advanced Science, EarlyView.
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
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

A twin delayed deep deterministic-based control method for a full vehicle semi-active suspension system. [PDF]

PLoS One
Wan Y, Wang X, Zhi G, Yang L, Wang J, Zhang X, Zhang Y.   +6 more
europepmc   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Anomaly Detection and Data Repair for Smart Meter Data in Smart Cities: A Comprehensive Review and Future Perspectives. [PDF]

Sensors (Basel)
Zhang B, Lin G, Zheng K, Du J.
europepmc   +1 more source

Halide Perovskite: A Rich Source of Thermal Insulator

Advanced Science, EarlyView.
Halide perovskites exhibit ultralow thermal conductivity driven by intrinsic lattice softness and strong anharmonicity, falling below conventional defect‐engineering limits. Weak metavalent bonding, A‐site rattling, and dynamic octahedral tilting drive phonon scattering to the Ioffe–Regel limit, where wave‐like tunneling replaces particle‐like ...
Haolin Ye, Bangzhi Ge, Yuan Yu, Chongjian Zhou   +3 more
wiley   +1 more source

Associations between curriculum-based outdoor education and school-aged children's physical activity throughout the week. [PDF]

Health Promot Int
Wackström N, Engberg E, Aaltonen S, Ray J, Kailaheimo-Björkqvist J, Simonsen N.   +5 more
europepmc   +1 more source