Optimized size sorting of MXene particles via centrifugal sedimentation: a practical approach using an empirical model and image processing technique

Controlling the physical, mechanical, and electrochemical properties of MXene-based materials is crucial for their effectiveness in macroscale applications and is closely tied to the particle size distribution of MXene. This study aimed to accomplish dimensional control and sorting of MXene colloids with different particle sizes using centrifugal sedimentation based on an empirical model. Centrifuge time and rotating speed were identified as key parameters and optimized using a mathematical formula generated from the model, considering particle forces in the solution. A novel image processing technique aimed at ease of use was devised to evaluate the separation process, assuring the audience of its usability. The separation efficiencies were measured individually at rotating speeds ranging from 2900 to 6000 rpm. The optimal experimental settings differed between the supernatant and sediment fractions. The maximum separation efficiency was reached at 86% for the supernatant at 3500 rpm for 49 min and 43% for the sediment at 4200 rpm for 34 min, suggesting that supernatant-based separation is more efficient than sediment-based techniques. This study offers a valuable guideline for separating the sizes of 2D materials. Image processing offers scalable particle size measurement, which improves material property control for a variety of applications.

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Publication Details

Journal
Particulate Science And Technology
Published
2025-04-03
DOI
https://doi.org/10.1080/02726351.2025.2486605
Citations
1
Primary Topic
MXene and MAX Phase Materials
Type
article
Field-Weighted Citation Impact
0.52
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article

Optimized size sorting of MXene particles via centrifugal sedimentation: a practical approach using an empirical model and image processing technique

Bircan Haspulat Taymaz, Volkan Eskizeybek, Handan Kamış, Buket Onat
1 citations
Particulate Science And Technology
MXene and MAX Phase Materials
0.52
article

Optimized size sorting of MXene particles via centrifugal sedimentation: a practical approach using an empirical model and image processing technique

Bircan Haspulat Taymaz, Volkan Eskizeybek, Handan Kamış, Buket Onat
article en
1 citations

Abstract

Controlling the physical, mechanical, and electrochemical properties of MXene-based materials is crucial for their effectiveness in macroscale applications and is closely tied to the particle size distribution of MXene. This study aimed to accomplish dimensional control and sorting of MXene colloids with different particle sizes using centrifugal sedimentation based on an empirical model. Centrifuge time and rotating speed were identified as key parameters and optimized using a mathematical formula generated from the model, considering particle forces in the solution. A novel image processing technique aimed at ease of use was devised to evaluate the separation process, assuring the audience of its usability. The separation efficiencies were measured individually at rotating speeds ranging from 2900 to 6000 rpm. The optimal experimental settings differed between the supernatant and sediment fractions. The maximum separation efficiency was reached at 86% for the supernatant at 3500 rpm for 49 min and 43% for the sediment at 4200 rpm for 34 min, suggesting that supernatant-based separation is more efficient than sediment-based techniques. This study offers a valuable guideline for separating the sizes of 2D materials. Image processing offers scalable particle size measurement, which improves material property control for a variety of applications.

Particulate Science And TechnologyVol. 43(5)
Çanakkale Onsekiz Mart Üniversitesi (TR), Konya Technical University (TR)
Openalex Percentile: Top 40%
MXene and MAX Phase Materials
0.52
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Optimized size sorting of MXene particles via centrifugal sedimentation: a practical approach using an empirical model and image processing technique — Bircan Haspulat Taymaz, Volkan Eskizeybek, et al. · Particulate Science And Technology (2025) | TGRS Research Map | TGRS