1 to 6 of 6 Results
Mar 8, 2024
Advanced Learning Strategies for Machine Learned Interatomic Potentials |
Oct 16, 2023
Materials 4.0 |
Jun 12, 2023
We aim to use first-principles calculations at finite temperatures in combination with machine learning (ML) techniques to derive an accurate picture of hydrogen embrittlement in Ni-based superalloys. The ML-based interatomic potential will allow for the determination of the temp... |
Feb 28, 2023
Biological Molecular Dynamics Simulations |
Jul 5, 2022
Use of physically-based surrogate models to accelerate the optimization of classical force fields and development of new reduced order models for transport properties based on entropy scaling. Machine-learned models for transport properties will be developed with an increasing da... |
Feb 15, 2021
Processing Uncertain Microstructural Data: The projects objective is to relate image-based data of stochastic microstructures to their quantities of interest. The data consists mainly of microstructure images, corresponding material properties and features deployed in machine lea... |