Talebi, F.A., Rabbani, A. orcid.org/0000-0001-5181-7318, Mehrabi, M. et al. (4 more authors) (2025) Dynamic adhesion measurement of powders using the drop testing method: Defining a window of operation. Powder Technology, 453. 120605. ISSN 0032-5910
Abstract
Powder adhesion often presents challenges within the pharmaceutical industry as it significantly affects powder flowability and understanding its relationship with powder flow, especially through modelling, presents a major advancement. Traditional approaches such as atomic force microscopy (AFM) and centrifuge method were previously utilised to measure the adhesive force of particles, however, these methods are both time and cost intensive necessitating the need for a more practical solution. This work endeavoured to investigate and develop a window of operation for measuring the effective work of adhesion of both regular and irregularly shaped powders using the drop test method, previously developed at the University of Leeds. For optimisation and accuracy in obtaining the critical diameter of adhesion, the drop test rig was further developed so as to ensure reliable and repeatable measurements of the impact velocity and contact time, which previously posed major challenges. The effective work of adhesion of ibuprofen powders across different sample volumes was measured, to establish a minimum number of analysed particles for ensuring the accuracy of the measured critical diameter. A minimum of 640 ibuprofen particles was required resulting into an effective work of adhesion of 19.6 ± 2.9 mJ/m². Moreover, the approach was tested on spherical particles, where effective work of adhesion of spherical aluminium-alloy powders (7.7 ± 1.8 mJ/m²) was assessed. Furthermore, artificial intelligence is incorporated in parallel to effectively determine the critical diameter and compare it to the manually calculated values allowing for an efficient image analysis.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). |
Keywords: | Particle adhesion, Effective work of adhesion, Critical diameter, Drop test method, Artificial intelligence |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Jan 2025 11:33 |
Last Modified: | 24 Jan 2025 11:33 |
Published Version: | https://www.sciencedirect.com/science/article/pii/... |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.powtec.2024.120605 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:222254 |
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