Rapid and accurate predictions of perfect and defective material properties in atomistic simulation using the power of 3D CNN-based trained artificial neural networks
Abstract This article introduces an innovative approach that utilizes machine learning (ML) to address the computational challenges of accurate atomistic simulations in materials science. Focusing on the field of molecular dynamics (MD), which offers insight into material behavior at the atomic leve...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2024-01-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-50893-9 |