<?xml version='1.0' encoding='utf-8'?> <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>Komissarov, Leonid</dc:creator> <dc:creator>Verstraelen, Toon</dc:creator> <dc:date>2021-10-27</dc:date> <dc:description>Fast, empirical potentials are gaining increased popularity in the computational fields of materials science, physics and chemistry. With it, there is a rising demand for high-quality reference data for the training and validation of such models. In contrast to research that is mainly focused on small organic molecules, this work presents a data set of geometry-optimized bulk phase zeolite structures. Covering a majority of framework types from the Database of Zeolite Structures, this set includes over thirty thousand geometries. Calculated properties include system energies, nuclear gradients and stress tensors at each point, making the data suitable for model development, validation or referencing applications focused on periodic silica systems.</dc:description> <dc:identifier>https://archive.materialscloud.org/record/2021.171</dc:identifier> <dc:identifier>doi:10.24435/materialscloud:cv-zd</dc:identifier> <dc:identifier>mcid:2021.171</dc:identifier> <dc:identifier>oai:materialscloud.org:1083</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>zeolite</dc:subject> <dc:subject>silica</dc:subject> <dc:subject>DFT</dc:subject> <dc:subject>bulk phase</dc:subject> <dc:subject>density-functional theory</dc:subject> <dc:subject>machine learning</dc:subject> <dc:subject>Horizon Europe</dc:subject> <dc:subject>H2020</dc:subject> <dc:subject>Marie Curie Fellowship</dc:subject> <dc:title>Zeo-1: A computational data set of zeolite structures</dc:title> <dc:type>Dataset</dc:type> </oai_dc:dc>