<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>10023</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>16319</pageFirst>
    <pageLast>16326</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>129</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Efficient and Accurate Machine Learning Interatomic Potential for Graphene: Capturing Stress–Strain and Vibrational Properties</title>
    <parentTitle language="eng">The Journal of Physical Chemistry C</parentTitle>
    <identifier type="arxiv">2505.12140</identifier>
    <identifier type="doi">10.1021/acs.jpcc.5c03470</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="PeerReviewed">yes</enrichment>
    <author>Felipe Hawthorne</author>
    <submitter>Ronaldo Rodrigues Pela</submitter>
    <author>Paulo R. E. Raulino</author>
    <author>Ronaldo Rodrigues Pelá</author>
    <author>Cristiano F. Woellner</author>
    <collection role="institutes" number="vas">Distributed Algorithms and Supercomputing</collection>
    <collection role="institutes" number="scp">Supercomputing</collection>
    <collection role="persons" number="ronaldo.rodrigues">Rodrigues Pelá, Ronaldo</collection>
    <collection role="projects" number="NHR@ZIB">NHR@ZIB</collection>
  </doc>
</export-example>
