Supplementary data for the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions"
| dc.contributor.author | Hyttinen, Noora | |
| dc.date.accessioned | 2022-10-19T07:03:31Z | |
| dc.date.available | 2022-10-19T07:03:31Z | |
| dc.date.issued | 2022 | |
| dc.identifier.citation | Hyttinen, Noora. Supplementary data for the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions". 10.17011/jyx/dataset/83604 | |
| dc.identifier.other | jyu-resd.155935998 | |
| dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/83604 | |
| dc.description.abstract | The data set contains the supplementary data of the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions" published in J. Phys. Chem. Lett., https://doi.org/10.1021/acs.jpclett.2c02612. The data includes: - A machine learning (EMLM) model for predicting chemical potentials of individual conformers of multifunctional organic compounds calculated by the COSMOtherm program - COSMO-files used for training and testing the EMLM model - Descriptors and chemical potentials used for the training and testing the model | en |
| dc.description.abstract | Artikkelin "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions" lisäaineisto. | fi |
| dc.language.iso | eng | |
| dc.relation.uri | https://nextcloud.jyu.fi/index.php/s/Sa2H5Teycxw9z9Q/download | |
| dc.rights | Creative Commons Attribution 4.0 International | en |
| dc.title | Supplementary data for the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions" | en |
| dc.type | dataset | |
| dc.identifier.urn | URN:NBN:fi:jyu-202210194924 | |
| dc.contributor.yliopisto | Jyväskylän yliopisto | fi |
| dc.contributor.yliopisto | University of Jyväskylä | en |
| dc.type.uri | http://purl.org/coar/resource_type/c_ddb1 | |
| dc.identifier.doi | 10.17011/jyx/dataset/83604 | |
| dc.rights.copyright | Hyttinen, Noora and University of Jyväskylä | |
| dc.rights.accesslevel | openAccess | |
| dc.relation.grantnumber | 338171 | |
| dc.subject.yso | koneoppiminen | fi |
| dc.subject.yso | atmospheric sciences | en |
| dc.subject.yso | machine learning | en |
| dc.subject.yso | ilmakehätieteet | fi |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p21846 | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p26208 | |
| dc.rights.url | https://creativecommons.org/licenses/by/4.0/ | |
| dc.relation.funder | Academy of Finland | |
| dc.relation.funder | Suomen Akatemia | |
| jyx.fundingprogram | Postdoctoral Researcher, AoF | |
| jyx.fundingprogram | Tutkijatohtori, SA |
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