DFT data used in training MolE8 chemical ML models
dc.contributor.author | Ermanis, Kristaps | |
dc.contributor.author | Goodman, Jonathan M. | |
dc.contributor.other | Lee, Sanha | |
dc.date.accessioned | 2021-11-09T15:17:58Z | |
dc.date.available | 2021-11-09T15:17:58Z | |
dc.date.issued | 2021-11-09 | |
dc.identifier.uri | https://rdmc.nottingham.ac.uk/handle/internal/9356 | |
dc.description.abstract | =============================================================== Data for paper "MolE8: Finding DFT Potential Energy Surface Minima Values from Force-Field Optimised Organic Molecules with New Machine Learning Representations" Sanha Lee, Kristaps Ermanis* and Jonathan M. Goodman* Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW and School of Chemistry, University of Nottingham, University Park Nottingham, Nottingham, NG7 2RD =============================================================== This dataset contains Gaussian DFT optimization and frequency calculation output files for all of the molecules used in the training of the MolE8 representations and machine learning methods. The dataset is divided in 7 parts to keep the archive file sizes manageable. Each folder contains data for around 8000 molecules. The data includes the geometry optimization *a.out files, frequency calculation *f.out files and *sdf files of the optimized structures for wider compatibility with visualization software. Part 1 contains structure files up to 009999A1* Part 2 contains structure files up to 019999A1* Part 3 contains structure files up to 021988A1* Part 4 contains structure files up to 39997A1* Part 5 contains structure files up to 49999A1* Part 6 contains structure files up to 59999A1* Part 6 contains structure files up to 69125A1* All structures in these folders have been optimized and frequencies calculated at B3LYP/6-31g(2df,p) level in gas phase. All of the files can be opened in any text editor. Gaussian output structures can be viewed and the frequency modes visualised in GausView, Avogadro, jmol and in most other molecular viewers/editors. *.sdf files can be viewed in essentially all 3D molecular editors and viewers. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | The University of Nottingham | en_UK |
dc.rights | CC-BY | * |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
dc.subject.lcsh | Machine learning | en_UK |
dc.subject.lcsh | Chemistry, Organic | en_UK |
dc.subject.lcsh | Density functionals | en_UK |
dc.subject.lcsh | Computational chemistry | en_UK |
dc.title | DFT data used in training MolE8 chemical ML models | en_UK |
dc.identifier.doi | http://doi.org/10.17639/nott.7159 | |
dc.subject.free | DFT, Gaussian, organic chemistry, machine learning, MolE8, neural networks, kernel ridge regression | en_UK |
dc.subject.jacs | Physical sciences::Chemistry::Organic chemistry | en_UK |
dc.subject.lc | Q Science::QD Chemistry::QD241 Organic chemistry | en_UK |
dc.subject.lc | Q Science::QD Chemistry::QD450 Physical and theoretical chemistry | en_UK |
uon.division | University of Nottingham, UK Campus::Faculty of Science::School of Chemistry | en_UK |
uon.funder.controlled | Other | en_UK |
uon.datatype | Gaussian 16 DFT software output files | en_UK |
uon.funder.free | Leverhulme Trust | en_UK |
uon.funder.free | Isaac Newton Trust | en_UK |
uon.funder.free | Trinity College, University of Cambridge | en_UK |
uon.grant | ECF-2017-255 | en_UK |
uon.grant | 17.08(d) | en_UK |
uon.collectionmethod | Gaussian 16 DFT software | en_UK |
uon.preservation.rarelyaccessed | true |
Files in this item
This item appears in the following Collection(s)
-
Public Research Data
A collection of research data, held in this repository, that is publicly available, except where individual embargoes apply