{"conceptdoi":"10.14278/rodare.1850","conceptrecid":"1850","created":"2022-10-21T13:18:19.669348+00:00","doi":"10.14278/rodare.1851","files":[{"bucket":"a7d766b9-2422-4f12-8062-91d64d6f6b97","checksum":"md5:d7e8a25ec24f5273042c1c469c7caae0","key":"size_transfer_cleaned.zip","links":{"self":"https://rodare.hzdr.de/api/files/a7d766b9-2422-4f12-8062-91d64d6f6b97/size_transfer_cleaned.zip"},"size":5992336,"type":"zip"}],"id":1851,"links":{"badge":"https://rodare.hzdr.de/badge/doi/10.14278/rodare.1851.svg","bucket":"https://rodare.hzdr.de/api/files/a7d766b9-2422-4f12-8062-91d64d6f6b97","conceptbadge":"https://rodare.hzdr.de/badge/doi/10.14278/rodare.1850.svg","conceptdoi":"https://doi.org/10.14278/rodare.1850","doi":"https://doi.org/10.14278/rodare.1851","html":"https://rodare.hzdr.de/record/1851","latest":"https://rodare.hzdr.de/api/records/1851","latest_html":"https://rodare.hzdr.de/record/1851","self":"https://rodare.hzdr.de/api/records/1851"},"metadata":{"access_right":"open","access_right_category":"success","communities":[{"id":"rodare"}],"creators":[{"affiliation":"HZDR / CASUS","name":"Fiedler, Lenz","orcid":"0000-0002-8311-0613"},{"affiliation":"HZDR","name":"Schmerler, Steve","orcid":"0000-0003-1354-0578"},{"affiliation":"Sandia National Laboratories","name":"Modine, Normand"},{"affiliation":"Sandia National Laboratories","name":"Vogel, Dayton J.","orcid":"0000-0003-3612-0699"},{"affiliation":"Elder Research, Inc.","name":"Popoola, Gabriel A."},{"affiliation":"Sandia National Laboratories","name":"Thompson, Aidan","orcid":"0000-0002-0324-9114"},{"affiliation":"Sandia National Laboratories","name":"Rajamanickam, Sivasankaran","orcid":"0000-0002-5854-409X"},{"affiliation":"HZDR / CASUS","name":"Cangi, Attila","orcid":"0000-0001-9162-262X"}],"description":"<pre><strong>Scripts and Models for &quot;Predicting the Electronic Structure of Matter on Ultra-Large Scales&quot;</strong>\n\nThis data set contains scripts and models to reproduce the results of our manuscript &quot;Physics-informed Machine Learning \nModels for Scalable Density Functional Theory Calculations&quot;. The scripts are supposed to be used in conjunction\nwith the ab-initio data sets also published alongside our research article. \n\n<em>Requirements</em>\n<em>\n</em>python&gt;=3.7.x\nmala&gt;=1.1.0\nase\nnumpy\n\n<em>Contents</em>\n\n| Folder name      | Description                                      |\n|------------------|--------------------------------------------------|\n| data_analysis/   | Run script for RDF calculations        |\n| model_inference/ | Run script to run inference based on MALA models |\n| model_training/  | Run script to train MALA models                  |\n| trained_models/  | Trained models for beryllium and aluminium       |\n</pre>","doc_id":"1","doi":"10.14278/rodare.1851","keywords":[],"license":{"id":"CC-BY-4.0"},"pub_id":"35305","publication_date":"2022-09-30","related_identifiers":[{"identifier":"https://www.hzdr.de/publications/Publ-35305","relation":"isIdenticalTo","scheme":"url"},{"identifier":"https://www.hzdr.de/publications/Publ-39797","relation":"isReferencedBy","scheme":"url"},{"identifier":"https://www.hzdr.de/publications/Publ-35418","relation":"isReferencedBy","scheme":"url"},{"identifier":"10.14278/rodare.1850","relation":"isVersionOf","scheme":"doi"}],"relations":{"version":[{"count":1,"index":0,"is_last":true,"last_child":{"pid_type":"recid","pid_value":"1851"},"parent":{"pid_type":"recid","pid_value":"1850"}}]},"resource_type":{"title":"Dataset","type":"dataset"},"title":"Scripts and Models for \"Predicting electronic structures at any length scale with machine learning\"","version":"1.0.0"},"owners":[354],"revision":7,"stats":{"downloads":578.0,"unique_downloads":165.0,"unique_views":1309.0,"version_downloads":578.0,"version_unique_downloads":165.0,"version_unique_views":1309.0,"version_views":1938.0,"version_volume":3463570208.0,"views":1938.0,"volume":3463570208.0},"updated":"2024-10-24T14:58:15.692641+00:00"}