Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation Phenomena

In this manuscript, a method that utilizes classical image techniques to assess particle aggregation and segregation, with the primary goal of validating particle size distribution determined by conventional methods, is presented. This approach can represent a supplementary tool in quality control s...

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Main Authors: Giuseppe Bonifazi, Paolo Barontini, Riccardo Gasbarrone, Davide Gattabria, Silvia Serranti
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Journal of Imaging
Subjects:
Online Access:https://www.mdpi.com/2313-433X/10/3/53
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author Giuseppe Bonifazi
Paolo Barontini
Riccardo Gasbarrone
Davide Gattabria
Silvia Serranti
author_facet Giuseppe Bonifazi
Paolo Barontini
Riccardo Gasbarrone
Davide Gattabria
Silvia Serranti
author_sort Giuseppe Bonifazi
collection DOAJ
description In this manuscript, a method that utilizes classical image techniques to assess particle aggregation and segregation, with the primary goal of validating particle size distribution determined by conventional methods, is presented. This approach can represent a supplementary tool in quality control systems for powder production processes in industries such as manufacturing and pharmaceuticals. The methodology involves the acquisition of high-resolution images, followed by their fractal and textural analysis. Fractal analysis plays a crucial role by quantitatively measuring the complexity and self-similarity of particle structures. This approach allows for the numerical evaluation of aggregation and segregation phenomena, providing valuable insights into the underlying mechanisms at play. Textural analysis contributes to the characterization of patterns and spatial correlations observed in particle images. The examination of textural features offers an additional understanding of particle arrangement and organization. Consequently, it aids in validating the accuracy of particle size distribution measurements. To this end, by incorporating fractal and structural analysis, a methodology that enhances the reliability and accuracy of particle size distribution validation is obtained. It enables the identification of irregularities, anomalies, and subtle variations in particle arrangements that might not be detected by traditional measurement techniques alone.
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spelling doaj.art-bd6fc0b7ce2649bbad776445e1a89cc92024-03-27T13:48:50ZengMDPI AGJournal of Imaging2313-433X2024-02-011035310.3390/jimaging10030053Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation PhenomenaGiuseppe Bonifazi0Paolo Barontini1Riccardo Gasbarrone2Davide Gattabria3Silvia Serranti4Department of Chemical Engineering, Materials and Environment, Sapienza University of Rome, via Eudossiana 18, 00184 Rome, ItalyCHEMI S.p.A., Via Vadisi 5, 03010 Patrica, ItalyResearch and Service Center for Sustainable Technological Innovation (Ce.R.S.I.Te.S.), Sapienza University of Rome, 04100 Latina, ItalyDepartment of Chemical Engineering, Materials and Environment, Sapienza University of Rome, via Eudossiana 18, 00184 Rome, ItalyDepartment of Chemical Engineering, Materials and Environment, Sapienza University of Rome, via Eudossiana 18, 00184 Rome, ItalyIn this manuscript, a method that utilizes classical image techniques to assess particle aggregation and segregation, with the primary goal of validating particle size distribution determined by conventional methods, is presented. This approach can represent a supplementary tool in quality control systems for powder production processes in industries such as manufacturing and pharmaceuticals. The methodology involves the acquisition of high-resolution images, followed by their fractal and textural analysis. Fractal analysis plays a crucial role by quantitatively measuring the complexity and self-similarity of particle structures. This approach allows for the numerical evaluation of aggregation and segregation phenomena, providing valuable insights into the underlying mechanisms at play. Textural analysis contributes to the characterization of patterns and spatial correlations observed in particle images. The examination of textural features offers an additional understanding of particle arrangement and organization. Consequently, it aids in validating the accuracy of particle size distribution measurements. To this end, by incorporating fractal and structural analysis, a methodology that enhances the reliability and accuracy of particle size distribution validation is obtained. It enables the identification of irregularities, anomalies, and subtle variations in particle arrangements that might not be detected by traditional measurement techniques alone.https://www.mdpi.com/2313-433X/10/3/53powderimage analysisfractal dimensionsegregationaggregationparticles
spellingShingle Giuseppe Bonifazi
Paolo Barontini
Riccardo Gasbarrone
Davide Gattabria
Silvia Serranti
Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation Phenomena
Journal of Imaging
powder
image analysis
fractal dimension
segregation
aggregation
particles
title Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation Phenomena
title_full Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation Phenomena
title_fullStr Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation Phenomena
title_full_unstemmed Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation Phenomena
title_short Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation Phenomena
title_sort development of a powder analysis procedure based on imaging techniques for examining aggregation and segregation phenomena
topic powder
image analysis
fractal dimension
segregation
aggregation
particles
url https://www.mdpi.com/2313-433X/10/3/53
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