QUAM-AFM Lite

<p>QUAM–AFM Lite is the scaled-down version of QUAM-AFM, the largest dataset of simulated Atomic Force Microscopy (AFM) images. This reduced version was generated from a selection of 1,755 molecules that span the most relevant bonding structures and chemical species in organic chemistry. Simil...

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Detalles Bibliográficos
Autores: Carracedo-Cosme, Jaime, Romero-Muñíz, Carlos, Pou, Pablo, Pérez, Rubén
Tipo de recurso: conjunto de datos
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Consorcio Madroño
Repositorio:e-cienciaDatos, Repositorio de Datos del Consorcio Madroño
OAI Identifier:doi:10.21950/BFAU11
Acceso en línea:https://doi.org/10.21950/BFAU11
Access Level:acceso abierto
Palabra clave:Physics
Condensed Matter Physics
Machine learning
Organic Chemistry
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spelling QUAM-AFM LiteCarracedo-Cosme, JaimeRomero-Muñíz, CarlosPou, PabloPérez, RubénPhysicsCondensed Matter PhysicsMachine learningOrganic Chemistry<p>QUAM–AFM Lite is the scaled-down version of QUAM-AFM, the largest dataset of simulated Atomic Force Microscopy (AFM) images. This reduced version was generated from a selection of 1,755 molecules that span the most relevant bonding structures and chemical species in organic chemistry. Similar to the extended version, QUAM-AFM Lite contains, for each molecule, 24 3D image stacks, each consisting of constant-height images simulated for 10 tip-sample distances (in the relevant imaging range and spanning a variation of 1 Å (0.1 nanometers)) with one of the 24 different combination of AFM operational parameters, resulting in a total of 421,200 images with a resolution of 256x256 pixels.</p> <p>The operational parameters include six different values for the cantilever oscillation amplitude (0.40, 0.60, 0.80, 1.00, 1.20, 1.40Å), 4 values of the elastic constant describing the tilting of the CO tip (0.40, 0.60, 0.80 and 1.00 N/m). The first parameter is freely chosen in the experiments in order to enhance different features of the image, while the last one reflects differences in the attachment of the CO molecule to the metal tip that are routinely observed and has been characterized in the experiments.</p> <p>The data provided for each molecule includes, besides a set of AFM images, the ball–and–stick depiction, the IUPAC name, the chemical formula, the atomic coordinates, and the map of atom heights. In order to simplify the use of the collection as a source of information, we have developed a Graphical User Interface (GUI) that allows the search for structures by CID number, IUPAC name or chemical formula.</p> <p>This dataset arises as a product of the research carried out in collaboration between Quasar Science Resources S.L. (https://quasarsr.com) and the Scanning Probe Microscopy Theory & Nanomechanics Research Group (SPMTH) (http://www.uam.es/spmth) at the Universidad Autónoma de Madrid (UAM), funded by the Comunidad de Madrid under the Industrial Doctorate Programme 2017 (project reference IND2017/IND-7793).</p> <p>The main goal of this dataset is to provide a simplified version of QUAM-AFM that allows to analyse the distribution of information and/or the graphical interface without the need for a full download. The extended version, QUAM-AFM, supports the development of deep learning methods for molecular identification through AFM imaging. Once this project has concluded, this dataset is made freely accessible in order to facilitate and to promote research in a range of fields including Atomic Force Microscopy, on-surface synthesis and deep learning applications.</p>e-cienciaDatosCarracedo-Cosme, Jaime2021info:eu-repo/semantics/datasetinfo:eu-repo/semantics/publishedVersiontext/plainapplication/x-gziphttps://doi.org/10.21950/BFAU11reponame:e-cienciaDatos, Repositorio de Datos del Consorcio Madroñoinstname:Consorcio MadroñoInglésQUAM-AFM, https://doi.org/10.21950/UTGMZ7info:eu-repo/grantAgreement/Community of Madrid/IND2017%2FIND-7793/info:eu-repo/grantAgreement/Ministry of Economy, Industry and Competitiveness/MAT2017-83273-R/info:eu-repo/grantAgreement/MICINN//PID2020-115864RB-I00info:eu-repo/grantAgreement/Ministry of Science, Innovation and Universities/CEX2018-000805-M/info:eu-repo/semantics/openAccessCC-BY-NC-SA-4.0doi:10.21950/BFAU112026-05-29T06:25:11Z
dc.title.none.fl_str_mv QUAM-AFM Lite
title QUAM-AFM Lite
spellingShingle QUAM-AFM Lite
Carracedo-Cosme, Jaime
Physics
Condensed Matter Physics
Machine learning
Organic Chemistry
title_short QUAM-AFM Lite
title_full QUAM-AFM Lite
title_fullStr QUAM-AFM Lite
title_full_unstemmed QUAM-AFM Lite
title_sort QUAM-AFM Lite
dc.creator.none.fl_str_mv Carracedo-Cosme, Jaime
Romero-Muñíz, Carlos
Pou, Pablo
Pérez, Rubén
author Carracedo-Cosme, Jaime
author_facet Carracedo-Cosme, Jaime
Romero-Muñíz, Carlos
Pou, Pablo
Pérez, Rubén
author_role author
author2 Romero-Muñíz, Carlos
Pou, Pablo
Pérez, Rubén
author2_role author
author
author
dc.contributor.none.fl_str_mv Carracedo-Cosme, Jaime
dc.subject.none.fl_str_mv Physics
Condensed Matter Physics
Machine learning
Organic Chemistry
topic Physics
Condensed Matter Physics
Machine learning
Organic Chemistry
description <p>QUAM–AFM Lite is the scaled-down version of QUAM-AFM, the largest dataset of simulated Atomic Force Microscopy (AFM) images. This reduced version was generated from a selection of 1,755 molecules that span the most relevant bonding structures and chemical species in organic chemistry. Similar to the extended version, QUAM-AFM Lite contains, for each molecule, 24 3D image stacks, each consisting of constant-height images simulated for 10 tip-sample distances (in the relevant imaging range and spanning a variation of 1 Å (0.1 nanometers)) with one of the 24 different combination of AFM operational parameters, resulting in a total of 421,200 images with a resolution of 256x256 pixels.</p> <p>The operational parameters include six different values for the cantilever oscillation amplitude (0.40, 0.60, 0.80, 1.00, 1.20, 1.40Å), 4 values of the elastic constant describing the tilting of the CO tip (0.40, 0.60, 0.80 and 1.00 N/m). The first parameter is freely chosen in the experiments in order to enhance different features of the image, while the last one reflects differences in the attachment of the CO molecule to the metal tip that are routinely observed and has been characterized in the experiments.</p> <p>The data provided for each molecule includes, besides a set of AFM images, the ball–and–stick depiction, the IUPAC name, the chemical formula, the atomic coordinates, and the map of atom heights. In order to simplify the use of the collection as a source of information, we have developed a Graphical User Interface (GUI) that allows the search for structures by CID number, IUPAC name or chemical formula.</p> <p>This dataset arises as a product of the research carried out in collaboration between Quasar Science Resources S.L. (https://quasarsr.com) and the Scanning Probe Microscopy Theory & Nanomechanics Research Group (SPMTH) (http://www.uam.es/spmth) at the Universidad Autónoma de Madrid (UAM), funded by the Comunidad de Madrid under the Industrial Doctorate Programme 2017 (project reference IND2017/IND-7793).</p> <p>The main goal of this dataset is to provide a simplified version of QUAM-AFM that allows to analyse the distribution of information and/or the graphical interface without the need for a full download. The extended version, QUAM-AFM, supports the development of deep learning methods for molecular identification through AFM imaging. Once this project has concluded, this dataset is made freely accessible in order to facilitate and to promote research in a range of fields including Atomic Force Microscopy, on-surface synthesis and deep learning applications.</p>
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/dataset
info:eu-repo/semantics/publishedVersion
format dataset
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.21950/BFAU11
url https://doi.org/10.21950/BFAU11
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv QUAM-AFM, https://doi.org/10.21950/UTGMZ7
info:eu-repo/grantAgreement/Community of Madrid/IND2017%2FIND-7793/
info:eu-repo/grantAgreement/Ministry of Economy, Industry and Competitiveness/MAT2017-83273-R/
info:eu-repo/grantAgreement/MICINN//PID2020-115864RB-I00
info:eu-repo/grantAgreement/Ministry of Science, Innovation and Universities/CEX2018-000805-M/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
CC-BY-NC-SA-4.0
eu_rights_str_mv openAccess
rights_invalid_str_mv CC-BY-NC-SA-4.0
dc.format.none.fl_str_mv text/plain
application/x-gzip
dc.publisher.none.fl_str_mv e-cienciaDatos
publisher.none.fl_str_mv e-cienciaDatos
dc.source.none.fl_str_mv reponame:e-cienciaDatos, Repositorio de Datos del Consorcio Madroño
instname:Consorcio Madroño
instname_str Consorcio Madroño
reponame_str e-cienciaDatos, Repositorio de Datos del Consorcio Madroño
collection e-cienciaDatos, Repositorio de Datos del Consorcio Madroño
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