<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-17T11:34:07Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2072/450537" metadataPrefix="oai_dc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2072/450537</identifier><datestamp>2024-12-20T19:19:02Z</datestamp><setSpec>com_2072_300912</setSpec><setSpec>com_2072_4427</setSpec><setSpec>col_2072_301309</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
   <dc:title>Turning chemistry into information for heterogeneous catalysis</dc:title>
   <dc:creator>Pablo-García, Sergio</dc:creator>
   <dc:creator>Álvarez-Moreno, Moises</dc:creator>
   <dc:creator>López, Núria</dc:creator>
   <dc:subject>54</dc:subject>
   <dc:description>The growing generation of data and their wide availability has led to the development
of tools to produce, analyze, and store this information. Computational chemistry
studies, especially catalytic applications, often yield a vast amount of chemical information
that can be analyzed and stored using these tools. In this manuscript, we present
a framework that automatically performs a fully automated procedure consisting
of the transfer of an adsorbate from a known metal slab to a new metal slab with similar
packing. Our method generates the new geometry and also performs the required
calculations and analysis to finally upload the processed data to an online database
(ioChem-BD). Two different implementations have been built, one to relocate minimum
energy point structures and the second to transfer transition states. Our framework
shows good performance for the minimum point location and a decent
performance for the transition state identification. Most of the failures occurred during
the transition state searches and needed additional steps to fully complete the
process. Further improvements of our framework are required to increase the performance
of both implementations. These results point to the avoidhuman path as a feasible
solution for studies on very large systems that require a significant amount of
human resources and, in consequence, are prone to human errors.</dc:description>
   <dc:date>2020-07-09</dc:date>
   <dc:type>info:eu-repo/semantics/article</dc:type>
   <dc:type>info:eu-repo/semantics/acceptedVersion</dc:type>
   <dc:identifier>http://hdl.handle.net/2072/450537</dc:identifier>
   <dc:identifier>https://doi.org/10.1002/qua.26382</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>RTI2018-101394-B-I00</dc:relation>
   <dc:rights>L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons:http://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:format>26382 p.</dc:format>
   <dc:format>application/pdf</dc:format>
   <dc:source>RECERCAT (Dipòsit de la Recerca de Catalunya)</dc:source>
</oai_dc:dc></metadata></record></GetRecord></OAI-PMH>