Microfluidic devices have many unique practical applications across a wide range of fields, making it important to develop accurate models of these devices, and many different models have been developed. Existing modeling methods mainly include mechanism derivation and semi-empirical correlations, but both are not universally applicable. In order to achieve a more accurate and general modeling process, the use of data-driven modeling has been studied recently. This review highlights recent advances in the application of data-driven modeling techniques for simulating and designing microfluidic devices. First, it introduces the application of traditional modeling approaches in microfluidics; subsequently, through different database sources, it reviews studies on data-driven modeling in three categories; and finally, it raises some open issues that require further investigation.
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December 2024
Review Article|
November 20 2024
Data-driven models for microfluidics: A short review
Yu Chang
;
Yu Chang
(Data curation, Investigation, Writing – original draft, Writing – review & editing)
Department of Chemical Engineering, State Key Laboratory of Chemical Engineering, Tsinghua University
, Beijing 100084, China
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Qichen Shang
;
Qichen Shang
(Writing – review & editing)
Department of Chemical Engineering, State Key Laboratory of Chemical Engineering, Tsinghua University
, Beijing 100084, China
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Zifei Yan
;
Zifei Yan
(Writing – review & editing)
Department of Chemical Engineering, State Key Laboratory of Chemical Engineering, Tsinghua University
, Beijing 100084, China
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Jian Deng
;
Jian Deng
(Investigation)
Department of Chemical Engineering, State Key Laboratory of Chemical Engineering, Tsinghua University
, Beijing 100084, China
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Guangsheng Luo
Guangsheng Luo
a)
(Conceptualization, Project administration, Visualization)
Department of Chemical Engineering, State Key Laboratory of Chemical Engineering, Tsinghua University
, Beijing 100084, China
a)Author to whom correspondence should be addressed: [email protected]
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a)Author to whom correspondence should be addressed: [email protected]
Biomicrofluidics 18, 061503 (2024)
Article history
Received:
August 31 2024
Accepted:
November 03 2024
Citation
Yu Chang, Qichen Shang, Zifei Yan, Jian Deng, Guangsheng Luo; Data-driven models for microfluidics: A short review. Biomicrofluidics 1 December 2024; 18 (6): 061503. https://doi.org/10.1063/5.0236407
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