The University of Southampton
University of Southampton Institutional Repository

Machine learning methods for analysis of organic molecular crystal structure prediction landscapes - associated data

Machine learning methods for analysis of organic molecular crystal structure prediction landscapes - associated data
Machine learning methods for analysis of organic molecular crystal structure prediction landscapes - associated data
This dataset contains the key data associated with PhD project 'Machine learning methods for analysis of organic molecular crystal structure prediction landscapes - associated data'
crystal structure predictioniction, GCH, Machine Learning, stability, materials discovery, computational chemistry
University of Southampton
Martin, Jennifer
979d288f-9864-4c69-aad6-226a9ad70ca0
Day, Graeme
e3be79ba-ad12-4461-b735-74d5c4355636
Martin, Jennifer
979d288f-9864-4c69-aad6-226a9ad70ca0
Day, Graeme
e3be79ba-ad12-4461-b735-74d5c4355636

Martin, Jennifer (2025) Machine learning methods for analysis of organic molecular crystal structure prediction landscapes - associated data. University of Southampton doi:10.5258/SOTON/D3723 [Dataset]

Record type: Dataset

Abstract

This dataset contains the key data associated with PhD project 'Machine learning methods for analysis of organic molecular crystal structure prediction landscapes - associated data'

Archive
Chapter_6.zip - Dataset
Available under License Creative Commons Attribution.
Download (33MB)
Archive
Chapter_7.zip - Dataset
Available under License Creative Commons Attribution.
Download (895kB)
Archive
Chapter_5.zip - Dataset
Available under License Creative Commons Attribution.
Download (1MB)
Archive
Chapter_8.zip - Dataset
Available under License Creative Commons Attribution.
Download (182MB)
Archive
Chapter_3.zip - Dataset
Available under License Creative Commons GNU GPL (Software).
Download (21kB)
Archive
Chapter_4.zip - Dataset
Available under License Creative Commons Attribution.
Download (617MB)
Text
README.txt - Dataset
Download (4kB)

Show all 7 downloads.

More information

Published date: October 2025
Keywords: crystal structure predictioniction, GCH, Machine Learning, stability, materials discovery, computational chemistry

Identifiers

Local EPrints ID: 505998
URI: http://eprints.soton.ac.uk/id/eprint/505998
PURE UUID: 58dbe7e9-c965-453d-9261-d26ce04b5151
ORCID for Jennifer Martin: ORCID iD orcid.org/0009-0004-0343-6309
ORCID for Graeme Day: ORCID iD orcid.org/0000-0001-8396-2771

Catalogue record

Date deposited: 27 Oct 2025 17:48
Last modified: 28 Oct 2025 03:09

Export record

Altmetrics

Contributors

Creator: Jennifer Martin ORCID iD
Research team head: Graeme Day ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×