Machine learning workflows to predict crystallisability, glass forming ability, mechanical properties of small organic compounds

Srirambhatla, Vijay K and Johnston, Blair and Florence, Alastair (2022) Machine learning workflows to predict crystallisability, glass forming ability, mechanical properties of small organic compounds. In: CMAC Annual Open Day 2022, 2022-05-16 - 2022-05-18.

[thumbnail of Srirambhatla-etal-CMAC-2022-Machine-learning-workflows-to-predict-crystallisability]
Preview
 Text. Filename: Srirambhatla_etal_CMAC_2022_Machine_learning_workflows_to_predict_crystallisability.pdf
Final Published Version
License: Strathprints license 1.0
Download (1MB)| Preview

ORCID iDs

Srirambhatla, Vijay K ORCID logoORCID: https://orcid.org/0000-0002-4492-7567, Johnston, Blair ORCID logoORCID: https://orcid.org/0000-0001-9785-6822 and Florence, Alastair ORCID logoORCID: https://orcid.org/0000-0002-9706-8364;

Persistent Identifier

https://doi.org/10.17868/strath.00081660
CORE (COnnecting REpositories)