- Reliable machine learning potentials based on artificial neural ...🔍
- Exploring Phononic Properties of Two|Dimensional Materials Using ...🔍
- Benchmarking machine learning interatomic potentials via phonon ...🔍
- Development of Interatomic Potential of High Entropy Diborides With ...🔍
- Daniel Schwalbe Koda🔍
- Spin|dependent graph neural network potential for magnetic materials🔍
- Lattice dynamics and thermal transport in crystalline solids from ...🔍
- Learning inter|atomic forces with an SE🔍
Lattice dynamics simulation using machine learning interatomic ...
(PDF) Exploring phononic properties of two-dimensional materials ...
Exploring phononic properties of two-dimensional materials using machine learning interatomic potentials. ... dynamics simulation. downloadDownload free PDF
Reliable machine learning potentials based on artificial neural ...
Lattice parameter, coefficient of thermal expansion (CTE), Young's modulus and yield strength are estimated using machine learning accelerated MD simulations ( ...
Exploring Phononic Properties of Two-Dimensional Materials Using ...
Phonon dispersion relations (PDRs) are key components to study the lattice dynamics and ... simulation using machine learning interatomic potentials. Comput.
Benchmarking machine learning interatomic potentials via phonon ...
While not directly formulated as a MLIP, several potential energy surface fitting approaches, such as compressive sensing lattice dynamics (CSLD) ...
Development of Interatomic Potential of High Entropy Diborides With ...
The machine learning interatomic potential and the utility of this molecular dynamics ... 2)B2: Molecular Dynamics Simulation by Deep Learning Potential, Journal ...
Daniel Schwalbe Koda: Machine learning for interatomic potentials
This video was recorded as part of the 4th IKZ - FAIRmat winter school, a hybrid event, online and on-site in Berlin, January 23 -25, 2023.
Spin-dependent graph neural network potential for magnetic materials
... machine-learning interatomic potentials has immensely contributed to the accuracy of simulations of molecules and crystals ... lattice dynamic simulations in ...
Lattice dynamics and thermal transport in crystalline solids from ...
Online Colloquium: Lattice dynamics and thermal transport in crystalline solids from machine learning interatomic potentials ... and molecular dynamics simulation ...
Learning inter-atomic forces with an SE(3)-Transformer Bryce E ...
Yanilkin, and A. Shapeev, “Lattice dynamics simulation using machine learning interatomic potentials,” Computational Materials Science 172, 109333. (2020).
Ta - Interatomic Potentials Repository
... and applied to molecular dynamics simulations of wetting and ... through atomistic simulations with a highly accurate machine learning interatomic potential.
... and time scales significantly larger than first principle molecular dynamics simulations. The deep potential (DP) model, an end-to-end deep neural network ...
Evaluation of Machine Learning Interatomic Potentials for the ... - MDPI
Benchmarking was carried out on Au20 nanoclusters against ab-initio molecular dynamics simulations and show we can achieve similar accuracy with the machine ...
Accelerated computation of lattice thermal conductivity using neural ...
interatomic potential developed for molecular simulations ... molecular dynamics simulations with a machine-learning-based interatomic potential, ...
Development of a machine learning potential for graphene
Simulations were run for each lattice parameter and each potential in the NVT ensemble using. Langevin dynamics. Configurations were first ...
Interatomic Potential Model Development: Finite‐Temperature ...
For developing an unbiased potential, a finite‐temperature dynamics machine learning (FTD‐ML) approach is proposed, and its processes and ...
Benchmarking of machine learning interatomic potentials for ...
Simulations of chemical reaction probabilities in gas surface dynamics require the calculation of ensemble averages over many tens of thousands of reaction ...
Machine Learning Interatomic Potentials and Long-Range Physics
Molecular dynamics simulation results using a Gaussian approximation potential (GAP) to model the interactions of condensed-phase phosphorus. (a) ...
... machine-learning interatomic potential for aluminum by the physically informed neural network method. GPP Pun and V Yamakov and J Hickman and EH Glaessgen ...
Machine-learning interatomic potentials enable first-principles ...
... dynamics simulations but also with the full ... simulation using machine learning interatomic ... parameters for lattice dynamics and phonon thermal transport in ...
Convenient and efficient development of Machine Learning ...
Convenient and efficient development of Machine Learning Interatomic ... Advances in Machine Learned Potentials for Molecular Dynamics Simulation.