High-throughput screening of nano-hybrid metal–organic-frameworks for photocatalytic CO₂ reduction

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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Khwaja, Moin</dc:creator>
  <dc:creator>Harada, Takuya</dc:creator>
  <dc:date>2024-09-19</dc:date>
  <dc:description>Photocatalytic conversion of CO₂ into fuel feed stocks is a promising method for sustainable fuel production. A highly attractive class of materials, inorganic-core@metal–organic-framework heterogeneous catalysts, boasts a significant increase in catalytic performance when compared to the individual materials. However, due to the ever-expanding chemical space of inorganic-core catalysts and metal–organic frameworks (MOFs), identification of these optimal heterojunctions is difficult without appropriate computational screening. In this work, a novel high-throughput screening method of nano-hybrid photocatalysts is presented by screening 65'784 inorganic-core materials and 20'375 MOF-shells for their ability to reduce CO₂ based on their synthesizability, aqueous stability, visible light absorption, and electronic structure; the passing materials were then paired based on their electronic structure to create novel heterojunctions. The results showed 58 suitable inorganic-core materials and 204 suitable MOFs ranging from never-beforesynthesized catalysts to catalysts that have been overlooked for their photocatalytic ability. These materials lay a new foundation of photocatalysts that have passed theoretical requirements and can significantly increase the rate of catalyst discovery.</dc:description>
  <dc:identifier>https://materialscloud-archive-failover.cineca.it/record/2024.139</dc:identifier>
  <dc:identifier>doi:10.24435/materialscloud:46-31</dc:identifier>
  <dc:identifier>mcid:2024.139</dc:identifier>
  <dc:identifier>oai:materialscloud.org:2336</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Materials Cloud</dc:publisher>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>core@shell</dc:subject>
  <dc:subject>metal-organic frameworks</dc:subject>
  <dc:subject>photocatalyst</dc:subject>
  <dc:title>High-throughput screening of nano-hybrid metal–organic-frameworks for photocatalytic CO₂ reduction</dc:title>
  <dc:type>Dataset</dc:type>
</oai_dc:dc>