Results 121 to 130 of about 15,495,898 (198)

Transferable Deep Learning Potential Reveals Intermediate-Range Ordering Effects in LiF-NaF-ZrF₄ Molten Salt. [PDF]

JACS Au, 2022
Chahal R, Roy S, Brehm M, Banerjee S, Bryantsev V, Lam ST.   +5 more
europepmc   +1 more source

Benchmarking Deep Learning for Agricultural Potential Estimation from Multispectral Satellite Time Series

Mohammad El Sakka, Lotfi Chaâri, Josiane Mothe   +2 more
openalex   +2 more sources

A foundation machine learning potential with polarizable long-range interactions for materials modelling. [PDF]

Nat Commun
Gao R, Yam C, Mao J, Chen S, Chen G, Hu Z.   +5 more
europepmc   +1 more source

Adsorption Sites on Pd Nanoparticles Unraveled by Machine-Learning Potential with Adaptive Sampling. [PDF]

Molecules, 2022
Tereshchenko A, Pashkov D, Guda A, Guda S, Rusalev Y, Soldatov A.   +5 more
europepmc   +1 more source

Hybrid sampling approach to machine-learning potentials for gas adsorption: Hydrogen adsorption in MOF-303

Kartik Sau, Ikutaro Hamada, Tamio Ikeshoji, Yiming Lu, Susmita Roy, Shohichi Furukawa, Linda Zhang, Hung Ba Tran, Takahiro Kondo, Hui Li, Shin‐ichi Orimo   +10 more
openalex   +1 more source

Domain oriented universal machine learning potential enables fast exploration of chemical space of battery electrolytes. [PDF]

Nat Commun
Wang F, Tang YH, Ma ZB, Jin YC, Cheng J.
europepmc   +1 more source

Distilling universal machine-learning potentials for moiré lattices across one million atoms [PDF]

Thomas Huang, Yueyao Fan, Kaichen Xie, Bolun Li, Kaijie Yang, Jenna A. Bilbrey, Eric Bylaska, Peter V. Sushko, Di Xiao, Ting Cao   +9 more
openalex   +1 more source

Harnessing the potential of AI in lifelong learning for medical undergraduates

The Asia Pacific Scholar
Nathasha Luke, Shing Chuan Hooi, Celestial T. Yap   +2 more
doaj   +1 more source

Construction of PANoptosis-Inhibiting Carbonized Polymer Dots via Machine Learning Potential for Mitigating Chemodrug-Induced Nephrotoxicity. [PDF]

Adv Sci (Weinh)
Liu X, Zhang J, Yan X, Li N, Dong YC, Wang Z, Li D, Du Y, Wang H.   +8 more
europepmc   +1 more source

Well-posed by Design: Learning Constitutive Laws from Velocity Data using Convex Neural Network Potentials

Gonzalo Gonzalez de Diego, Georg Stadler
openalex   +1 more source