Dataset Open Access

Scripts and Models for "Predicting electronic structures at any length scale with machine learning"

Fiedler, Lenz; Schmerler, Steve; Modine, Normand; Vogel, Dayton J.; Popoola, Gabriel A.; Thompson, Aidan; Rajamanickam, Sivasankaran; Cangi, Attila

Scripts and Models for "Predicting the Electronic Structure of Matter on Ultra-Large Scales"

This data set contains scripts and models to reproduce the results of our manuscript "Physics-informed Machine Learning 
Models for Scalable Density Functional Theory Calculations". The scripts are supposed to be used in conjunction
with the ab-initio data sets also published alongside our research article. 

Requirements

python>=3.7.x
mala>=1.1.0
ase
numpy

Contents

| Folder name      | Description                                      |
|------------------|--------------------------------------------------|
| data_analysis/   | Run script for RDF calculations        |
| model_inference/ | Run script to run inference based on MALA models |
| model_training/  | Run script to train MALA models                  |
| trained_models/  | Trained models for beryllium and aluminium       |

Files (6.0 MB)
Name Size
size_transfer_cleaned.zip
md5:d7e8a25ec24f5273042c1c469c7caae0
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