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QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules

In the research field of material science, quantum chemistry database plays an indispensable role in determining the structure and properties of new material molecules and in deep learning in this field. A new quantum chemistry database, the QM-sym, has been set up in our previous work. The QM-sym i...

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Autores principales: Liang, Jiechun, Ye, Shuqian, Dai, Tianshu, Zha, Ziyue, Gao, Yuechen, Zhu, Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7675965/
https://www.ncbi.nlm.nih.gov/pubmed/33208742
http://dx.doi.org/10.1038/s41597-020-00746-1
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author Liang, Jiechun
Ye, Shuqian
Dai, Tianshu
Zha, Ziyue
Gao, Yuechen
Zhu, Xi
author_facet Liang, Jiechun
Ye, Shuqian
Dai, Tianshu
Zha, Ziyue
Gao, Yuechen
Zhu, Xi
author_sort Liang, Jiechun
collection PubMed
description In the research field of material science, quantum chemistry database plays an indispensable role in determining the structure and properties of new material molecules and in deep learning in this field. A new quantum chemistry database, the QM-sym, has been set up in our previous work. The QM-sym is an open-access database focusing on transition states, energy, and orbital symmetry. In this work, we put forward the QM-symex with 173-kilo molecules. Each organic molecular in the QM-symex combines with the C(n)h symmetry composite and contains the information of the first ten singlet and triplet transitions, including energy, wavelength, orbital symmetry, oscillator strength, and other quasi-molecular properties. QM-symex serves as a benchmark for quantum chemical machine learning models that can be effectively used to train new models of excited states in the quantum chemistry region as well as contribute to further development of the green energy revolution and materials discovery.
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spelling pubmed-76759652020-11-20 QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules Liang, Jiechun Ye, Shuqian Dai, Tianshu Zha, Ziyue Gao, Yuechen Zhu, Xi Sci Data Data Descriptor In the research field of material science, quantum chemistry database plays an indispensable role in determining the structure and properties of new material molecules and in deep learning in this field. A new quantum chemistry database, the QM-sym, has been set up in our previous work. The QM-sym is an open-access database focusing on transition states, energy, and orbital symmetry. In this work, we put forward the QM-symex with 173-kilo molecules. Each organic molecular in the QM-symex combines with the C(n)h symmetry composite and contains the information of the first ten singlet and triplet transitions, including energy, wavelength, orbital symmetry, oscillator strength, and other quasi-molecular properties. QM-symex serves as a benchmark for quantum chemical machine learning models that can be effectively used to train new models of excited states in the quantum chemistry region as well as contribute to further development of the green energy revolution and materials discovery. Nature Publishing Group UK 2020-11-18 /pmc/articles/PMC7675965/ /pubmed/33208742 http://dx.doi.org/10.1038/s41597-020-00746-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Liang, Jiechun
Ye, Shuqian
Dai, Tianshu
Zha, Ziyue
Gao, Yuechen
Zhu, Xi
QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules
title QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules
title_full QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules
title_fullStr QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules
title_full_unstemmed QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules
title_short QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules
title_sort qm-symex, update of the qm-sym database with excited state information for 173 kilo molecules
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7675965/
https://www.ncbi.nlm.nih.gov/pubmed/33208742
http://dx.doi.org/10.1038/s41597-020-00746-1
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