{"title":"In situ and on-line measurement of soot size using the light-based method","authors":"Jingjing Xia , Chaohao Yang , Jin Zeng","doi":"10.1016/j.jaerosci.2025.106679","DOIUrl":null,"url":null,"abstract":"<div><div>In situ and on-line measurement of soot's particle size distribution (PSD) is crucial for comprehending its physical and chemical properties. The non-contact nature and high sensitivity of optical techniques have led to their widespread adoption in soot characterization. To overcome the computational burden associated with modeling fractal structures, this study utilizes the discrete dipole approximation (DDA) to represent soot as ellipsoids. Meanwhile, a miniaturized prototype sensor was utilized to collect the light scattering phase function (LSPF), providing sufficient optical information to retrieve soot's PSD. Experiments with Di-Ethyl-Hexyl-Sebacate (DEHS) demonstrated that the prototype sensor can accurately collect the LSPF, with a maximum relative error (RE) below 15 %. The Kullback-Leibler divergence (<em>D</em><sub><em>KL</em></sub>) of the PSD retrieved by the hybrid iterative inversion algorithm that was proposed in this study is no larger than 0.05. Further testing with open-flame combustion confirmed that the method proposed in this study can accurately sense soot's PSD and decouple its ovality parameter (OP). The method proposed in this study exhibits significant potential for in situ and on-line measurement of soot's PSD and provides a reliable framework for characterizing irregular particles.</div></div>","PeriodicalId":14880,"journal":{"name":"Journal of Aerosol Science","volume":"191 ","pages":"Article 106679"},"PeriodicalIF":2.9000,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Aerosol Science","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0021850225001569","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
Abstract
In situ and on-line measurement of soot's particle size distribution (PSD) is crucial for comprehending its physical and chemical properties. The non-contact nature and high sensitivity of optical techniques have led to their widespread adoption in soot characterization. To overcome the computational burden associated with modeling fractal structures, this study utilizes the discrete dipole approximation (DDA) to represent soot as ellipsoids. Meanwhile, a miniaturized prototype sensor was utilized to collect the light scattering phase function (LSPF), providing sufficient optical information to retrieve soot's PSD. Experiments with Di-Ethyl-Hexyl-Sebacate (DEHS) demonstrated that the prototype sensor can accurately collect the LSPF, with a maximum relative error (RE) below 15 %. The Kullback-Leibler divergence (DKL) of the PSD retrieved by the hybrid iterative inversion algorithm that was proposed in this study is no larger than 0.05. Further testing with open-flame combustion confirmed that the method proposed in this study can accurately sense soot's PSD and decouple its ovality parameter (OP). The method proposed in this study exhibits significant potential for in situ and on-line measurement of soot's PSD and provides a reliable framework for characterizing irregular particles.
期刊介绍:
Founded in 1970, the Journal of Aerosol Science considers itself the prime vehicle for the publication of original work as well as reviews related to fundamental and applied aerosol research, as well as aerosol instrumentation. Its content is directed at scientists working in engineering disciplines, as well as physics, chemistry, and environmental sciences.
The editors welcome submissions of papers describing recent experimental, numerical, and theoretical research related to the following topics:
1. Fundamental Aerosol Science.
2. Applied Aerosol Science.
3. Instrumentation & Measurement Methods.