Dataset Restricted Access

Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks

Ellis, J. A.; Cangi, A.; Modine, N. A.; Stephens, J. A.; Thompson, A. P.; Rajamanickam, S.

GeoJSON Export

{
  "features": [], 
  "type": "FeatureCollection"
}
804
1
views
downloads
All versions This version
Views 804804
Downloads 11
Data volume 3.1 MB3.1 MB
Unique views 497497
Unique downloads 11
More info on how stats are collected.
Publication date:
December 11, 2020
DOI:
10.14278/rodare.646

RODARE DOI Badge

DOI 

10.14278/rodare.646

Markdown 

[![DOI](https://rodare.hzdr.de/badge/DOI/10.14278/rodare.646.svg)](https://doi.org/10.14278/rodare.646)

reStructedText 

.. image:: https://rodare.hzdr.de/badge/DOI/10.14278/rodare.646.svg
   :target: https://doi.org/10.14278/rodare.646

HTML 

<a href="https://doi.org/10.14278/rodare.646"><img src="https://rodare.hzdr.de/badge/DOI/10.14278/rodare.646.svg" alt="DOI"></a>

Image URL 

https://rodare.hzdr.de/badge/DOI/10.14278/rodare.646.svg

Target URL 

https://doi.org/10.14278/rodare.646

Keyword(s):
machine learning neural networks materials science density functional theory
Related identifiers:
Identical to:
https://www.hzdr.de/publications/Publ-31857
Referenced by:
https://www.hzdr.de/publications/Publ-31603
Supplement to:
https://arxiv.org/abs/2010.04905
Communities:

Versions

Version 1 10.14278/rodare.646 Dec 11, 2020
Cite all versions? You can cite all versions by using the DOI 10.14278/rodare.645. This DOI represents all versions, and will always resolve to the latest one. Read more.

Share

Cite as

Export