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Development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds
The development of robust computational protocols capable of accurately predicting the dielectric strengths of eco-friendly insulating gas candidates is crucial; however, it lacks relevant efforts significantly. Consequently, a series of computational protocols are employed in this study to enable t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9055060/ https://www.ncbi.nlm.nih.gov/pubmed/35487965 http://dx.doi.org/10.1038/s41598-022-10946-x |
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author | Jang, Joonho Jung, Ku Hyun Kim, Ki Chul |
author_facet | Jang, Joonho Jung, Ku Hyun Kim, Ki Chul |
author_sort | Jang, Joonho |
collection | PubMed |
description | The development of robust computational protocols capable of accurately predicting the dielectric strengths of eco-friendly insulating gas candidates is crucial; however, it lacks relevant efforts significantly. Consequently, a series of computational protocols are employed in this study to enable the computational prediction of polarizability and ionization energy of eco-friendly, perfluorinated carbon-based candidates, followed by the equation-based prediction of their dielectric strength. The validation process associated with the prediction of the afore-mentioned variables for selected datasets confirms the suitability of the B3LYP-based prediction protocol for reproducing experimental values. Subsequently, the validation of dielectric strength prediction outlines the following three conclusions. (1) The referenced equation adopted from a previous study is incapable of predicting the dielectric strengths of 137 organic compounds present in our database. (2) Parameterization of the coefficients in the referenced equation leads to the accurate prediction of the dielectric strengths. (3) Incorporation of a novel variable, viz. molecular weight, into the referenced equation combined with the parameterization of the coefficients leads to a robust protocol capable of predicting dielectric strengths with high efficiencies even with a significantly smaller fitting dataset. This implies the development of a comprehensive solution capable of accurately predicting the dielectric strengths of a substantially large dataset. |
format | Online Article Text |
id | pubmed-9055060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90550602022-05-01 Development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds Jang, Joonho Jung, Ku Hyun Kim, Ki Chul Sci Rep Article The development of robust computational protocols capable of accurately predicting the dielectric strengths of eco-friendly insulating gas candidates is crucial; however, it lacks relevant efforts significantly. Consequently, a series of computational protocols are employed in this study to enable the computational prediction of polarizability and ionization energy of eco-friendly, perfluorinated carbon-based candidates, followed by the equation-based prediction of their dielectric strength. The validation process associated with the prediction of the afore-mentioned variables for selected datasets confirms the suitability of the B3LYP-based prediction protocol for reproducing experimental values. Subsequently, the validation of dielectric strength prediction outlines the following three conclusions. (1) The referenced equation adopted from a previous study is incapable of predicting the dielectric strengths of 137 organic compounds present in our database. (2) Parameterization of the coefficients in the referenced equation leads to the accurate prediction of the dielectric strengths. (3) Incorporation of a novel variable, viz. molecular weight, into the referenced equation combined with the parameterization of the coefficients leads to a robust protocol capable of predicting dielectric strengths with high efficiencies even with a significantly smaller fitting dataset. This implies the development of a comprehensive solution capable of accurately predicting the dielectric strengths of a substantially large dataset. Nature Publishing Group UK 2022-04-29 /pmc/articles/PMC9055060/ /pubmed/35487965 http://dx.doi.org/10.1038/s41598-022-10946-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jang, Joonho Jung, Ku Hyun Kim, Ki Chul Development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds |
title | Development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds |
title_full | Development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds |
title_fullStr | Development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds |
title_full_unstemmed | Development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds |
title_short | Development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds |
title_sort | development of computational design for reliable prediction of dielectric strengths of perfluorocarbon compounds |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9055060/ https://www.ncbi.nlm.nih.gov/pubmed/35487965 http://dx.doi.org/10.1038/s41598-022-10946-x |
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