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Article
Engineering, Chemical
Junjie Wang et al.
Summary: This study investigates the microdispersion performances of hydrogen, oxygen, or water in the anthraquinone working solution using an observation platform, aiming to provide reliable data for developing new microchemical processes. The influence of two-phase flow rate, viscosity, and channel size on bubble size in a circular microchannel was studied. A mathematical prediction model for gas-liquid and liquid-liquid microdispersion was developed, which can be used for future practical industrial system process intensification.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Multidisciplinary Sciences
Jordi Bures et al.
Summary: In this study, a deep neural network model is used to analyze kinetic data and automate mechanistic elucidation. The model can accurately identify various classes of mechanisms, including non-steady state mechanisms, and performs well even with data containing errors or limited time points. The model is freely available and is expected to contribute to the development of fully automated organic reaction discovery and development.
Article
Engineering, Chemical
Wei Liu et al.
Summary: Micro-packed bed reactors (mu PBRs) have been successfully used in hydrogenation and oxidation reactions due to their high heat and mass transfer efficiency as well as excellent safety. However, the study of gas-liquid flow regimes in mu PBRs is still lacking due to the micro-scale limitation and complexity of capillary force. In this study, the flow regimes in a two-dimensional mu PBR were systematically investigated using a high-performance camera. Four typical flow regimes and their characteristics were observed, and the transition between flow regimes was analyzed. The effects of gas and liquid superficial velocities, liquid physical properties, and particle sizes on liquid spreading and pressure drop were also studied. Additionally, a correlation between churn flow and pseudo-static flow in mu PBRs was provided for the first time based on a summary of previous research.
Article
Engineering, Chemical
Jian Li et al.
Summary: This article develops a deep learning-based tomographic imaging technique using electrical capacitance tomography (ECT) to characterize particle concentration distribution in a circulating fluidized bed (CFB). Experimental results demonstrate that the deep tomographic imaging technique of ECT can successfully measure particle distribution in both 60 mm and 100 mm pipes, showing good prediction and generality of the designed convolutional neural network (CNN) model. The experimental findings reveal a flow regime transformation from annular flow to core-annular flow and pneumatic conveying, which are highly affected by the fluidized gas flow rate and the initial bed height.
Article
Chemistry, Multidisciplinary
Yu Chang et al.
Summary: This study aims to develop general design rules for gas-liquid Taylor flow T-junction microreactors. Two major issues to address are the relationship between gas flow rate and pressure drop, and the bubble generation and hydrodynamics in different devices. A dimensionless relationship between gas pressure and flow rate is proposed, along with a model to predict bubble generation and investigate hydrodynamics. Lastly, a design procedure for gas-liquid Taylor flow T-junction microreactors is proposed.
REACTION CHEMISTRY & ENGINEERING
(2023)
Review
Engineering, Chemical
Zifei Yan et al.
Summary: This review comprehensively organizes the recent progress in microfluidic technology for measuring reaction kinetics, summarizing the kinetic modeling thoughts, determination methods, and essential regularities. It covers various reaction types and important innovations in microplatform.
CHINESE JOURNAL OF CHEMICAL ENGINEERING
(2022)
Article
Engineering, Chemical
Lin Sheng et al.
Summary: This study investigates the generation rules and behavior of bubbles in liquids with higher viscosity through experiments and mathematical modeling. The results show that the bubble formation process in higher viscous liquids consists of three stages: expansion, shrinking, and necking, and the generation of satellite bubbles as a new bubble generation performance is observed.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)
Article
Engineering, Chemical
Shuai Chen et al.
Summary: A multiphase flow 3D numerical simulation method employing the coupled volume of fluid (VOF) and level set model is established to study the reactive absorption of CO2 by the monoethanolamine (MEA) aqueous solution in a falling film microchannel. The enhancement effect of the Marangoni convection in this reactive absorption process is analyzed, and the influence of different MEA concentrations on CO2 absorption is investigated. The appropriate MEA concentration for absorption enhanced by the Marangoni convection is determined.
CHINESE JOURNAL OF CHEMICAL ENGINEERING
(2022)
Article
Engineering, Chemical
Sumit R. Hazare et al.
Summary: A machine learning-based data-driven methodology is proposed to predict the gas hold-up in a gas-liquid bubble column. The performance of various machine learning methods is compared, and the extra tree method is found to be the most suitable for gas hold-up prediction.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2022)
Article
Engineering, Chemical
Jing Song et al.
Summary: The impact of colliding microdispersion on droplet generation has been investigated, and novel T-junction microdevices and scaling laws for droplet size have been proposed. Moreover, the flow regime distribution and liquid-liquid flow pattern under high Weber number were explored.
CHEMICAL ENGINEERING SCIENCE
(2022)
Article
Engineering, Chemical
Lin Sheng et al.
Summary: This study focuses on the vertical squeezing bubble generation mechanism in viscous liquids in a T-junction microchannel. The results show the stages of retraction, expansion, shrinking, and necking in the vertical squeezing route, with a new formation stage, the retraction stage, compared to horizontal squeezing. The influence of operating conditions on the generation mechanism and the different formation mechanisms of satellite bubbles were investigated. Models for the generation frequency and bubble size were proposed based on the findings.
CHEMICAL ENGINEERING SCIENCE
(2022)
Article
Thermodynamics
Yichuan He et al.
Summary: This study predicts bubble departure frequency in subcooling flow boiling using machine learning-based approaches. By comparing a consolidated dataset and nine regression models, it is found that the XGBoost model performs the best in predicting bubble departure frequency, providing a reliable tool.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Biochemical Research Methods
Karl Gardner et al.
Summary: This study develops an automated droplet and cell detector using YOLOv3 and YOLOv5 object detectors, and demonstrates its capability in real-time cell encapsulation optimization.
Article
Biochemical Research Methods
Loic Chagot et al.
Summary: The control of droplet formation and size using microfluidic devices is essential for laboratory and industrial applications. This study investigates how surfactants can improve stability and control droplet size in silicone oil. Two data-driven models, based on Bayesian regularised artificial neural network and XGBoost, accurately predict droplet size as a function of flow rates and surfactant properties. Compared to semi-empirical models, the data-driven models have higher accuracy. The models were also trained with simplified inputs, showing good prediction results. Additionally, a synthetic data set was generated, proving the feasibility of using this method in future lab on a chip applications.
Review
Biochemical Research Methods
David McIntyre et al.
Summary: Microfluidics is a mature field with wide-ranging applications. However, the complexity of designing and controlling microfluidic devices hinders its adoption. Integration of machine learning with microfluidics can overcome these barriers and enable broader applications.
Article
Multidisciplinary Sciences
Ali Lashkaripour et al.
Summary: Microfluidic devices based on droplet generation show great potential in various life science applications, but the lack of predictive understanding makes the design process iterative and resource-intensive. The DAFD tool utilizes machine learning algorithms to predict performance and automate the design of flow-focusing droplet generators, reducing the need for design iterations.
NATURE COMMUNICATIONS
(2021)
Article
Engineering, Chemical
Yuchao Chen et al.
Summary: This study investigated gas-liquid bubbly flows in T-junction microdevices with different microstructures and found that the gas injector diameter has a significant influence on bubble dispersion. When the gas injector diameter is small and the gas-phase flow rate is lower than the liquid-phase flow rate, bubbly microflows are easily formed. Furthermore, designing a step T-junction microchannel with a small capillary and a narrow slit can improve bubble generation ability.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2021)
Article
Engineering, Chemical
Lin Sheng et al.
Summary: This work reports the generation of short bubbles with high frequency in a capillary embedded step T-junction microdevice for gas-liquid process intensification. The specific surface area of the generated gas-liquid microdispersion system is larger than 10,400 m(2)/m(3), and the bubble formation mechanism is mainly driven by the relatively higher pressure drop providing a much higher breakup force for the squeezing flow.
Article
Engineering, Chemical
Lin Sheng et al.
Summary: The study systematically investigated the general rules of bubble formation in viscous liquids, revealing that the formation frequencies can be divided into four periods and the bubble diameter is scaled perfectly with the gas-liquid flow rate ratio and the capillary number.
CHEMICAL ENGINEERING SCIENCE
(2021)
Article
Biochemical Research Methods
Jinghong Su et al.
Summary: This study presents a fast numerical algorithm and machine learning techniques for analysis and design of inertial microfluidic devices, generating a database of inertial lift forces in straight microchannels and developing a machine learning assisted model to predict particle trajectories quickly and accurately.
Review
Biochemical Research Methods
Linbo Liu et al.
Article
Engineering, Aerospace
S. Arias et al.
MICROGRAVITY SCIENCE AND TECHNOLOGY
(2020)
Article
Thermodynamics
Liwei Zhou et al.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2020)
Article
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Sheng Mi et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2019)
Review
Green & Sustainable Science & Technology
Nor Haziq Naqiuddin et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2018)
Review
Multidisciplinary Sciences
Keith T. Butler et al.
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Engineering, Aerospace
S. Arias et al.
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Engineering, Environmental
Y. K. Li et al.
CHEMICAL ENGINEERING JOURNAL
(2016)
Review
Chemistry, Multidisciplinary
Hannes P. L. Gemoets et al.
CHEMICAL SOCIETY REVIEWS
(2016)
Article
Biochemistry & Molecular Biology
Evan Z. Macosko et al.
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Engineering, Chemical
Taotao Fu et al.
CHEMICAL ENGINEERING SCIENCE
(2015)
Article
Engineering, Chemical
Chaoqun Yao et al.
Article
Mechanics
Ken Yamamoto et al.
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW
(2013)
Article
Engineering, Chemical
Taotao Fu et al.
Article
Computer Science, Interdisciplinary Applications
S. Arias et al.
COMPUTERS & FLUIDS
(2012)
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Engineering, Chemical
K. Wang et al.
Article
Biochemical Research Methods
Elena Castro-Hernandez et al.
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Engineering, Environmental
J. Tan et al.
CHEMICAL ENGINEERING JOURNAL
(2009)
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Engineering, Chemical
Volkert van Steijn et al.
CHEMICAL ENGINEERING SCIENCE
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Physics, Applied
JH Xu et al.
APPLIED PHYSICS LETTERS
(2006)
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Biochemical Research Methods
P Garstecki et al.