Crossmark

Machine learning approaches to understand and predict rate constants for organic processes in mixtures containing ionic liquids

Crossref DOI link: https://doi.org/10.1039/D0CP04227G

Published Online: 2021

Update policy: https://doi.org/10.1039/rsc_crossmark_policy

Authors

Greaves, Tamar L. https://orcid.org/0000-0002-0298-0183
Schaffarczyk McHale, Karin S.

Burkart-Radke, Raphael F.

Harper, Jason B. https://orcid.org/0000-0003-2722-8534
Le, Tu C.
Funding

Funding for this research was provided by:

Australian Research Council (DP180103682)

University of New South Wales
License Information

Accepted Manuscript valid from 2022-01-14
More Information

SIMILARITY CHECK

: This document is Similarity Check deposited

RELATED DATA

: Supplementary Information

IDENTIFIERS

: Tamar L. Greaves (ORCID)

: Jason B. Harper (ORCID)

PEER REVIEW METHOD

: Single-blind

PUBLICATION HISTORY

: Received 10 August 2020; Accepted 14 January 2021; Accepted Manuscript published 14 January 2021; Advance Article published 26 January 2021; Version of Record published 4 February 2021