Garg, Vivek ORCID: 0000-0002-8515-4759 , Deng, Tong ORCID: 0000-0003-4117-4317 and Bradley, Michael (2021) A new method for assessing powder flowability based on physical properties and cohesiveness of particles using a small quantity of samples. Powder Technology. ISSN 0032-5910 (Print), 1873-328X (Online) (doi:https://doi.org/10.1016/j.powtec.2021.10.027)

Preview

PDF (Author's accepted manuscript (AAM)) 34205_GARG_A_New_method_for_assessing_powder.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (11MB) | Preview

Abstract

Characterising powder flowability can be a challenge if only a small quantity of samples is available, e.g. pharmaceutical formulations. The paper focuses on a new method for assessing powder flowability based on physical properties and cohesiveness of particles using a few grams of powders. The technique applies Bond number to represent powder cohesiveness, which detects particle adhesion at median particle size using a mechanical surface energy tester developed at the Wolfson Centre. To establish the method, correlations between the Bond numbers and the flow functions of several powders measured on a shear cell tester have been explored empirically. With the correlations, a prediction model has been developed not only for powder flow functions but also for other flow properties such as compressibility, internal friction angles and true friction angles. This investigation has been undertaken using a wide range of materials from free-flowing to very cohesive for the method establishment and a group of different types of materials for a blind validation of the method. The methodology shows promising results for powder flowability prediction and other flow properties such as compressibility and internal friction angles. The validation results show a good agreement against the results measured using a shear cell tester.

Item Type:	Article
Uncontrolled Keywords:	Powder flowability, particle properties, bond number, cohesive powders, prediction model
Subjects:	Q Science > QD Chemistry
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Wolfson Centre for Bulk Solids Handling Technology
Related URLs:	Publisher
Last Modified:	21 Oct 2022 01:38
URI:	http://gala.gre.ac.uk/id/eprint/34205

Actions (login required)

View Item

Downloads