Data for: "Machine learning derived correlations for scale-up and technology transfer of primary nucleation kinetics"

Stephanie Yerdelen (Creator)
Cameron Brown (Creator)
Yihui Yang (Supervisor)
Justin L. Quon (Supervisor)
Charles D. Papageorgiou (Supervisor)
Christopher Mitchell (Supervisor)
Ian Houson (Supervisor)
Jan Sefcik (Supervisor)
Joop Ter Horst (Supervisor)
Alastair Florence (Supervisor)

Dataset

Description

Observed induction times, calculated induction time distribution parameters, calculated hydrodynamic features and machine learning model performance metrics.

Date made available	10 Jan 2023
Publisher	University of Strathclyde

Contact

researchdataproject@strath.ac.uk

DOI
10.15129/5a7908ad-2cdf-492f-a3bf-d1e96c8d80d6

Access Dataset

cg_2022_001925_data_for_article.xlsx
File: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, 61.9 KB
Type: Dataset
Licence: CC BY 4.0

1 Article

Machine learning derived correlations for scale-up and technology transfer of primary nucleation kinetics
Yerdelen, S., Yang, Y., Quon, J. L., Papageorgiou, C. D., Mitchell, C., Houson, I., Sefcik, J., ter Horst, J. H., Florence, A. J. & Brown, C. J., 18 Jan 2023, (E-pub ahead of print) In: Crystal Growth and Design. 13 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
4 Downloads (Pure)

1 Finished
1 Active

Future Continuous Manufacturing and Advanced Crystallisation Research Hub (CMAC Hub)
Florence, A., Brown, C., Halbert, G., Johnston, B., Markl, D., Nordon, A., Price, C. J., Sefcik, J. & Ter Horst, J.
EPSRC (Engineering and Physical Sciences Research Council)
1/01/17 → 31/12/23
Project: Research
Takeda 2017/18 Proprietary Project
Florence, A.
Takeda Pharmaceutical Company Ltd
1/10/18 → 30/09/20
Project: Research

Cite this

Yerdelen, S. (Creator), Brown, C. (Creator), Yang, Y. (Supervisor), Quon, J. L. (Supervisor), Papageorgiou, C. D. (Supervisor), Mitchell, C. (Supervisor), Houson, I. (Supervisor), Sefcik, J. (Supervisor), Ter Horst, J. (Supervisor), Florence, A. (Supervisor) (10 Jan 2023). Data for: "Machine learning derived correlations for scale-up and technology transfer of primary nucleation kinetics". University of Strathclyde. cg_2022_001925_data_for_article(.xlsx). 10.15129/5a7908ad-2cdf-492f-a3bf-d1e96c8d80d6

Data for: "Machine learning derived correlations for scale-up and technology transfer of primary nucleation kinetics"

Description

Contact

DOI

Access Dataset

Research output

Machine learning derived correlations for scale-up and technology transfer of primary nucleation kinetics

Projects

Future Continuous Manufacturing and Advanced Crystallisation Research Hub (CMAC Hub)

Takeda 2017/18 Proprietary Project

Cite this