Agglomeration characteristics of nano-size TiO2 particles using analytical solution

Jong Sang Youn; Se Joon Park; Hyunwook Cho; Yong Won Jung; Ki Joon Jeon

doi:10.1007/s11814-018-0095-8

Agglomeration characteristics of nano-size TiO₂ particles using analytical solution

Jong Sang Youn, Se Joon Park, Hyunwook Cho, Yong Won Jung, Ki Joon Jeon

Energy & Environmental Engineering

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

We developed equations for nano-sized titanium dioxide (TiO₂) particles self preserving time (SPT) lag that combines with agglomerate key parameters such as primary particle size (PPS), geometric standard deviation (GSD) and mass fractal dimension (MFD). A statistical formula has been developed that relies on SPT lag as the key parameter of agglomerates. Finally, this research presents the first analytical solution by integrating these key parameters into one formula, which can be utilized as a handy tool to calculate the time for reaching the asymptotic state.

Original language	English
Pages (from-to)	1948-1953
Number of pages	6
Journal	Korean Journal of Chemical Engineering
Volume	35
Issue number	9
DOIs	https://doi.org/10.1007/s11814-018-0095-8
State	Published - 1 Sep 2018

Bibliographical note

Funding Information:
This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2017R1C1B1008811).

Publisher Copyright:
© 2018, Korean Institute of Chemical Engineers, Seoul, Korea.

Keywords

Agglomerate
Geometric Standard Deviation
Mass Fractal Dimension
Nanoparticle
Primary Particle Size
Self Preserving Time

Access to Document

10.1007/s11814-018-0095-8

Cite this

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title = "Agglomeration characteristics of nano-size TiO2 particles using analytical solution",

abstract = "We developed equations for nano-sized titanium dioxide (TiO2) particles self preserving time (SPT) lag that combines with agglomerate key parameters such as primary particle size (PPS), geometric standard deviation (GSD) and mass fractal dimension (MFD). A statistical formula has been developed that relies on SPT lag as the key parameter of agglomerates. Finally, this research presents the first analytical solution by integrating these key parameters into one formula, which can be utilized as a handy tool to calculate the time for reaching the asymptotic state.",

keywords = "Agglomerate, Geometric Standard Deviation, Mass Fractal Dimension, Nanoparticle, Primary Particle Size, Self Preserving Time",

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note = "Funding Information: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2017R1C1B1008811). Publisher Copyright: {\textcopyright} 2018, Korean Institute of Chemical Engineers, Seoul, Korea.",

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AU - Youn, Jong Sang

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AU - Cho, Hyunwook

AU - Jung, Yong Won

AU - Jeon, Ki Joon

N1 - Funding Information: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2017R1C1B1008811). Publisher Copyright: © 2018, Korean Institute of Chemical Engineers, Seoul, Korea.

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N2 - We developed equations for nano-sized titanium dioxide (TiO2) particles self preserving time (SPT) lag that combines with agglomerate key parameters such as primary particle size (PPS), geometric standard deviation (GSD) and mass fractal dimension (MFD). A statistical formula has been developed that relies on SPT lag as the key parameter of agglomerates. Finally, this research presents the first analytical solution by integrating these key parameters into one formula, which can be utilized as a handy tool to calculate the time for reaching the asymptotic state.

AB - We developed equations for nano-sized titanium dioxide (TiO2) particles self preserving time (SPT) lag that combines with agglomerate key parameters such as primary particle size (PPS), geometric standard deviation (GSD) and mass fractal dimension (MFD). A statistical formula has been developed that relies on SPT lag as the key parameter of agglomerates. Finally, this research presents the first analytical solution by integrating these key parameters into one formula, which can be utilized as a handy tool to calculate the time for reaching the asymptotic state.

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KW - Geometric Standard Deviation

KW - Mass Fractal Dimension

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