Journal article Open Access

Unfolding the prospects of computational (bio)materials modeling

G. J. Agur Sevink; Jozef Adam Liwo; Pietro Asinari; Donal MacKernan; Giuseppe Milano; Ignacio Pagonabarraga


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  <identifier identifierType="URL">https://zenodo.org/record/4046053</identifier>
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    <creator>
      <creatorName>G. J. Agur Sevink</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-8005-0697</nameIdentifier>
      <affiliation>Leiden University</affiliation>
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    <creator>
      <creatorName>Jozef Adam Liwo</creatorName>
      <affiliation>University of Gdansk</affiliation>
    </creator>
    <creator>
      <creatorName>Pietro Asinari</creatorName>
      <affiliation>Politecnico di Torino</affiliation>
    </creator>
    <creator>
      <creatorName>Donal MacKernan</creatorName>
      <affiliation>University College Dublin</affiliation>
    </creator>
    <creator>
      <creatorName>Giuseppe Milano</creatorName>
      <affiliation>Yamagata University</affiliation>
    </creator>
    <creator>
      <creatorName>Ignacio Pagonabarraga</creatorName>
      <affiliation>CECAM, EPFL</affiliation>
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  <titles>
    <title>Unfolding the prospects of computational (bio)materials modeling</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <dates>
    <date dateType="Issued">2020-09-08</date>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1063/5.0019773</relatedIdentifier>
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  <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">&lt;p&gt;In this perspective communication, we briefly sketch the current state of computational (bio)material research and discuss possible solutions for the four challenges that have been increasingly identified within this community: (i) the desire to develop a unified framework for testing the consistency of implementation and physical accuracy for newly developed methodologies, (ii) the selection of a standard format that can deal with the diversity of simulation data and at the same time simplifies data storage, data exchange, and data reproduction, (iii) how to deal with the generation, storage, and analysis of massive data, and (iv) the benefits of efficient &amp;ldquo;core&amp;rdquo; engines. Expressed viewpoints are the result of discussions between computational stakeholders during a Lorentz center workshop with the prosaic title&amp;nbsp;&lt;em&gt;Workshop on Multi-scale Modeling&lt;/em&gt;&amp;nbsp;and are aimed at (i) improving validation, reporting and reproducibility of computational results, (ii) improving data migration between simulation packages and with analysis tools, (iii) popularizing the use of coarse-grained and multi-scale computational tools among non-experts and opening up these modern computational developments to an extended user community.&amp;nbsp;&lt;/p&gt;</description>
    <description descriptionType="Other">This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in (J. Chem. Phys. 153, 100901 (2020)) and may be found at (https://doi.org/10.1063/5.0019773).</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/676531/">676531</awardNumber>
      <awardTitle>An e-infrastructure for software, training and consultancy in simulation and modelling</awardTitle>
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