Data for: “Machine Learning Approach to the Prediction of Powder Flow Behaviour of Pharmaceutical Materials from Physical Properties”

Laura Pereira-Diaz (Creator)
Alastair Florence (Supervisor)
Cameron Brown (Supervisor)

Dataset

Description

The dataset includes particle size distribution, particle shape distribution, bulk density, and flow function coefficient of 113 pharmaceutical powders, including single compounds and pharmaceutical mixtures.

Date made available	27 Sept 2022
Publisher	University of Strathclyde
Date of data production	20 Feb 2020 - 12 Oct 2021

Contact

[email protected]

DOI
10.15129/3005493b-a125-4a5d-8599-525ce952facf

Access Dataset

2022_03_04_ParticleAndBulkPropertiesCharacterisationDataset_LauraPereiraDiaz.xlsx
File: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, 24.7 KB
Type: Dataset
Licence: CC BY 4.0

Doctoral Training Partnership 2018-19 University of Strathclyde | Pereira Diaz, Laura
Florence, A. (Principal Investigator), Brown, C. (Co-investigator) & Pereira Diaz, L. (Research Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/10/19 → 27/07/23
Project: Research Studentship - Internally Allocated

Pharmtech bin blender
Florence, A.
Strathclyde Institute Of Pharmacy And Biomedical Sciences
Facility/equipment: Equipment

Cite this

Pereira-Diaz, L. (Creator), Florence, A. (Supervisor), Brown, C. (Supervisor) (27 Sept 2022). Data for: “Machine Learning Approach to the Prediction of Powder Flow Behaviour of Pharmaceutical Materials from Physical Properties” . University of Strathclyde. 2022_03_04_ParticleAndBulkPropertiesCharacterisationDataset_LauraPereiraDiaz(.xlsx). 10.15129/3005493b-a125-4a5d-8599-525ce952facf

Data for: “Machine Learning Approach to the Prediction of Powder Flow Behaviour of Pharmaceutical Materials from Physical Properties”

Description

Contact

DOI

Access Dataset

Projects

Doctoral Training Partnership 2018-19 University of Strathclyde | Pereira Diaz, Laura

Equipment

Pharmtech bin blender

Cite this