AI Collection

Dataset

Data-efficient fine-tuning for reaction modelling in explicit solvent

Documentation:: Deposited data represents training datasets and scripts used in the publication. For details on different files, please see README.md file.

Actions

Email

Email this record

Send the bibliographic details of this record to your email address.

Your Email
Please enter the email address that the record information will be sent to.

-
Your message (optional)
Please add any additional information to be included within the email.
Share
Cite

Cite this record

APA Style

Holownia, J., Juraskova, V., Deringer, V., & Duarte Gonzalez, F. (2026). Data-efficient fine-tuning for reaction modelling in explicit solvent. University of Oxford.

MLA Style

Holownia, J, et al. Data-Efficient Fine-Tuning for Reaction Modelling in Explicit Solvent. University of Oxford, 2026.

Chicago Style

Holownia, J, V Juraskova, V Deringer, and F Duarte Gonzalez. 2026. Data-Efficient Fine-Tuning for Reaction Modelling in Explicit Solvent. University of Oxford.
Print

Access Document

Requestable Files:: Request a copy

README.md

(plain, 2.0KB, Terms of use)

Request a copy

CPD_MVK_DA.zip

(zip, 983.4MB, Terms of use)

Request a copy

guajadial_DA.zip

(zip, 881.1MB, Terms of use)

Request a copy

1.5_dimethoxy_anthracene_DA.zip

(bin, 1.0GB, Terms of use)

Authors/Creators

+ Holownia, J More by this author/creator

Institution:: University of Oxford
Division:: MPLS
Department:: Chemistry
Role:: Creator

+ Juraskova, V More by this author/creator

Institution:: University of Oxford
Division:: MPLS
Department:: Chemistry
Oxford college:: Reuben College
Role:: Creator
ORCID:: 0000-0002-6293-5616

+ Deringer, V More by this author/creator

Institution:: University of Oxford
Division:: MPLS
Department:: Chemistry
Sub department:: Inorganic Chemistry
Oxford college:: St Anne's College
Role:: Creator

+ Duarte Gonzalez, F More by this author/creator

Institution:: University of Oxford
Division:: MPLS
Department:: Chemistry
Sub department:: Organic Chemistry
Oxford college:: Hertford College
Role:: Creator
ORCID:: 0000-0002-6062-8209

+ Schmidt Sciences More from this funder

Funder identifier:: https://ror.org/044fk6795

Publisher:: University of Oxford
Publication date:: 2026
DOI:: 10.5287/ora-9r8dgw2vo

Language:: English
Keywords:: machine-learned interatomic potentials

fine-tuning

chemical reactions

pre-trained models

explicit solvent
Pubs id:: 2452848
Local pid:: pubs:2452848
Deposit date:: 2026-08-25
ARK identifier:: ark:/29072/ora_97dc4d3024c1473b937986935fc54350

Terms of use

Copyright date:: 2026

Licence:: Terms and Conditions of Use for Oxford University Research Archive

Views and Downloads

About views and downloads

If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP