Software and Datasets for "Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning"

Ward, Logan; Blaiszik, Ben; Lee, Cheng-Wei; Martin, Troy; Foster, Ian; Schleife, André

simulation machine learning nuclear materials

Organizations

MDF Open

Year

2023

Source Name

rtdftplusai

Contacts

lward@anl.gov

DOI

10.18126/r7lp-z2wj View on Datacite

Get the Data

The software associated with a publication showing how to quickly assess the electronic stopping power of a material using a combination of simulation and machine learning. This publication is a snapshot of our GitHub repository including the intermediate files used to communicate between each notebook.