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Thermal transport of glasses via machine learning driven simulations

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Thermal transport of glasses via machine learning driven simulations

Graph Chatbot

Chattez avec Graph Search

Transferable machine-learning models of complex materials: the case of GaAs

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Transferable machine-learning models of complex materials: the case of GaAs

Atomistic modeling of the solid-liquid interface of metals and alloys

Machine learning for metallurgy I. A neural-network potential for Al-Cu

Development of microdevices for the in-plane thermoelectric characterization of deposited films

Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Computational Organic Chemistry

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems

Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics

Machine learning for metallurgy II. A neural-network potential for magnesium

i-PI 2.0: A universal force engine for advanced molecular simulations