Bayesian estimation of pore size distribution in porous carbon using a novel GCMC-based kernel incorporating surface roughness

Bayesian estimation of pore size distribution in porous carbon using a novel GCMC-based kernel incorporating surface roughness

Porous carbons play vital roles in adsorption-based applications, and their pore size distributions (PSDs) are crucial for performance. Kernel-based inversion of adsorption isotherms is the standard route to obtain PSDs, yet it still faces technical limitations. In this study, we address these issue...

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Bibliographic Details
Main Authors: Shotaro Hiraide, Naruaki Fuse, Kohei Yamamoto, Hideki Tanaka, Kazuyuki Nakai, Satoshi Watanabe
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Carbon Trends
Subjects:
Pore size distribution
Bayesian estimation
Surface roughness
Kernel
Molecular simulation
Porous carbon
Online Access:http://www.sciencedirect.com/science/article/pii/S2667056925001002
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http://www.sciencedirect.com/science/article/pii/S2667056925001002

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