Machine learning based tool for the efficient estimation of geometric features of aggregated aerosol particles-Reference-Cited by-同舟云学术

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Machine learning based tool for the efficient estimation of geometric features of aggregated aerosol particles

Published:2024-08 Issue: Volume:180 Page:106391
ISSN:0021-8502
Container-title:Journal of Aerosol Science
language:en
Short-container-title:Journal of Aerosol Science

Author:

Singh Abhishek,Chaudhary Khushi,Thajudeen Thaseem^ORCID

Publisher

Elsevier BV

Reference37 articles.

1. Machine learning-based structure-property predictions in silica aerogels;Abdusalamov;Soft Matter,2021

2. FracMAP: A user-interactive package for performing simulation and orientation-specific morphology analysis of fractal-like solid nano-agglomerates;Chakrabarty;Computer Physics Communications,2009

3. Simulation of aggregates with point-contacting monomers in the cluster-dilute regime. Part 1: Determining the most reliable technique for obtaining three-dimensional fractal dimension from two-dimensional images;Chakrabarty;Aerosol Science and Technology,2011

4. Simulation of aggregates with point-contacting monomers in the cluster-dilute regime. Part 2: Comparison of two-and three-dimensional structural properties as a function of fractal dimension;Chakrabarty;Aerosol Science and Technology,2011

5. Slip correction factors for non-spherical bodies-III the form of the general law;Dahneke;Journal of Aerosol Science,1973

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