Perspectives: Past, Present, and Future Developments in Particle Science and Technology

Members of the American Editorial Board of the KONA Powder and Particle Journal recently convened to consider current and future perspectives in the fields of particle science and technology. This brief overview presents their observations regarding current and emerging areas of interest in select domains of particle and powder technologies. The major areas of practical significance identified were particle characterization, milling, granular material handling, scale-up considerations, and particle design strategies for environmental and pharmaceutical applications. An attempt has been made to highlight the role of artificial intelligence (AI)/machine learning (ML) in generating robust modeling and simulations for designing particle and powder systems for future process and product innovations.

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Publication Details

Journal
UNC Libraries
Published
2025-08-07
DOI
https://doi.org/10.17615/qrnz-tw29
Primary Topic
Granular flow and fluidized beds
Type
article
Field-Weighted Citation Impact
0.00
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Perspectives: Past, Present, and Future Developments in Particle Science and Technology

Luís Marcelo Tavares, Anil Misra, Qiang Zhang, Wei‐Ning Wang et al.
UNC Libraries
Granular flow and fluidized beds
article

Perspectives: Past, Present, and Future Developments in Particle Science and Technology

Luís Marcelo Tavares, Anil Misra, Qiang Zhang, Wei‐Ning Wang, Anthony D. Rosato, Anthony J. Hickey, Vasanthakumar Balasubramanian, Brij M. Moudgil, C. C. Huang
article en

Abstract

Members of the American Editorial Board of the KONA Powder and Particle Journal recently convened to consider current and future perspectives in the fields of particle science and technology. This brief overview presents their observations regarding current and emerging areas of interest in select domains of particle and powder technologies. The major areas of practical significance identified were particle characterization, milling, granular material handling, scale-up considerations, and particle design strategies for environmental and pharmaceutical applications. An attempt has been made to highlight the role of artificial intelligence (AI)/machine learning (ML) in generating robust modeling and simulations for designing particle and powder systems for future process and product innovations.

UNC Libraries
University of North Carolina at Chapel Hill (US)
Openalex Percentile: Top 64%
Granular flow and fluidized beds
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Perspectives: Past, Present, and Future Developments in Particle Science and Technology — Luís Marcelo Tavares, Anil Misra, et al. · UNC Libraries (2025) | TGRS Research Map | TGRS