Dataset Open Access
Fiedler, Lenz; Schmerler, Steve; Modine, Normand; Vogel, Dayton J.; Popoola, Gabriel A.; Thompson, Aidan; Rajamanickam, Sivasankaran; Cangi, Attila
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.14278/rodare.1851</identifier> <creators> <creator> <creatorName>Fiedler, Lenz</creatorName> <givenName>Lenz</givenName> <familyName>Fiedler</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-8311-0613</nameIdentifier> <affiliation>HZDR / CASUS</affiliation> </creator> <creator> <creatorName>Schmerler, Steve</creatorName> <givenName>Steve</givenName> <familyName>Schmerler</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-1354-0578</nameIdentifier> <affiliation>HZDR</affiliation> </creator> <creator> <creatorName>Modine, Normand</creatorName> <givenName>Normand</givenName> <familyName>Modine</familyName> <affiliation>Sandia National Laboratories</affiliation> </creator> <creator> <creatorName>Vogel, Dayton J.</creatorName> <givenName>Dayton J.</givenName> <familyName>Vogel</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3612-0699</nameIdentifier> <affiliation>Sandia National Laboratories</affiliation> </creator> <creator> <creatorName>Popoola, Gabriel A.</creatorName> <givenName>Gabriel A.</givenName> <familyName>Popoola</familyName> <affiliation>Elder Research, Inc.</affiliation> </creator> <creator> <creatorName>Thompson, Aidan</creatorName> <givenName>Aidan</givenName> <familyName>Thompson</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-0324-9114</nameIdentifier> <affiliation>Sandia National Laboratories</affiliation> </creator> <creator> <creatorName>Rajamanickam, Sivasankaran</creatorName> <givenName>Sivasankaran</givenName> <familyName>Rajamanickam</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-5854-409X</nameIdentifier> <affiliation>Sandia National Laboratories</affiliation> </creator> <creator> <creatorName>Cangi, Attila</creatorName> <givenName>Attila</givenName> <familyName>Cangi</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-9162-262X</nameIdentifier> <affiliation>HZDR / CASUS</affiliation> </creator> </creators> <titles> <title>Scripts and Models for "Predicting electronic structures at any length scale with machine learning"</title> </titles> <publisher>Rodare</publisher> <publicationYear>2022</publicationYear> <dates> <date dateType="Issued">2022-09-30</date> </dates> <resourceType resourceTypeGeneral="Dataset"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/1851</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-35305</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-39797</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsReferencedBy">https://www.hzdr.de/publications/Publ-35418</relatedIdentifier> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.1850</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier> </relatedIdentifiers> <version>1.0.0</version> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><pre><strong>Scripts and Models for &quot;Predicting the Electronic Structure of Matter on Ultra-Large Scales&quot;</strong> This data set contains scripts and models to reproduce the results of our manuscript &quot;Physics-informed Machine Learning Models for Scalable Density Functional Theory Calculations&quot;. The scripts are supposed to be used in conjunction with the ab-initio data sets also published alongside our research article. <em>Requirements</em> <em> </em>python&gt;=3.7.x mala&gt;=1.1.0 ase numpy <em>Contents</em> | 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 | </pre></description> </descriptions> </resource>
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