Numerical and experimental investigation on micromixers with serpentine microchannels

Chen, Xueye; Li, Tiechuan; Zeng, Hong; Hu, Zengliang; Fu, Baoding

doi:10.1016/j.ijheatmasstransfer.2016.03.041

Cited by 233 publications

(93 citation statements)

References 31 publications

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“…To demonstrate the proposed method, the mixing performances of fabricated micromixers with two different designs, namely T‐ and Y‐micromixers, were evaluated as shown in Figure . These two types of micromixers are often employed for benchmarking purposes . The total mixing length of the micromixers is 40 mm.…”

Section: Methodsmentioning

confidence: 99%

“…The digitally captured intensity images are usually stored in the format of three 8‐bit monochromatic red, green, and blue colors (RGB), which can be converted to the grayscale, cyan/magenta/yellow/key or hue/saturation/intensity (HSI) color model. The mixing index can be calculated using grayscale images as follows:

italicMixing index = 1 - \sqrt{\frac{1}{N} \sum_{i = 1}^{N} {(\frac{{\overset{false¯}{I}}_{italicgray, normali} - I^{*}}{I^{*}})}^{2}},

where N is the total number of pixels i analyzed, I * is the expected normalized pixel intensity that equals 0.5, and

\overset{I}{true}

gray ,i is

{\overset{false¯}{I}}_{italicgray, normali} = \frac{((), I_{italicgray, i} - I_{italicgray, italicmin})}{((), I_{italicgray, italicmax} - I_{italicgray, italicmin})},

where

\overset{I}{true}

gray ,i is the normalized pixel intensity inside the image, whereas I gray, min and I gray, max are the minimum and maximum local pixel intensity, respectively, and I gray, i is

I_{gray, normali} = ((), 0.299 normalR + 0.587 normalG + 0.114 normalB) / 3,

where I gray, i is the local pixel intensity.…”

Section: Introductionmentioning

confidence: 99%

“…4 The mixing performance of these micromixers is generally characterized as a function of mixing index. On the basis of color changes, the mixing index has been employed to characterize mixing between dye colored liquids [5][6][7] , reaction between chemical that produces different colored species 8 , reaction between pH indicators [9][10][11] , and dilution of fluorescent liquids. 12,13 Several quantitative mixing indices have been defined based on intensity images recorded using typical digital video microscopes.…”

Section: Introductionmentioning

confidence: 99%

“…9,12,14,15 The digitally captured intensity images are usually stored in the format of three 8-bit monochromatic red, green, and blue colors (RGB), which can be converted to the grayscale, cyan/magenta/yellow/key or hue/saturation/intensity (HSI) color model. The mixing index can be calculated using grayscale images as follows 7,9,[14][15][16] :…”

Section: Introductionmentioning

confidence: 99%

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Method for determining mixing index in microfluidics by RGB color model

Mahmud

Tamrin

2020

Asia-Pacific J Chem Eng

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Microfluidic mixing is a key process in miniaturized analysis system. Achieving adequate mixing performance is considerably difficult in microfluidic micromixer, as the flow is always associated with unfavorable laminar flow and dominated by molecular diffusion. The mixing performance of these micromixers are generally characterized as a function of mixing index based on dispersion (homogeneity) information, leading to either an overestimated or underestimated mixing index. This paper presents a new method for determining the mixing index of micromixers based on RGB color model by decoding mixing images to their respective red, green, and blue pixel intensities. Several digital composite images were used to perform initial benchmarking, and the proposed method accurately quantified the mixing index significantly better than previously adopted methods. The practicality of the method was further demonstrated by characterizing mixing of well‐known micromixers, namely T‐ and Y‐ micromixers, at varying Reynolds numbers of 5 ≤ Re ≤ 100. The results show that the mixing index decreases with the increase in Reynolds number, whereas the mixing index of the T‐micromixer was superior to that of Y‐micromixer, both agreeing well with the literature. The mixing index of these micromixers at varying Reynolds numbers of 5 ≤ Re ≤ 100 calculated using other methods were also compared and discussed. The proposed method is foreseen handy and robust in characterizing mixing in real time for gradient mixing in networked microchannels and multivortex mixing for the manipulation of fluids, particles, and biological substances.

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Section: Methodsmentioning

confidence: 99%

italicMixing index = 1 - \sqrt{\frac{1}{N} \sum_{i = 1}^{N} {(\frac{{\overset{false¯}{I}}_{italicgray, normali} - I^{*}}{I^{*}})}^{2}},

where N is the total number of pixels i analyzed, I * is the expected normalized pixel intensity that equals 0.5, and

\overset{I}{true}

gray ,i is

{\overset{false¯}{I}}_{italicgray, normali} = \frac{((), I_{italicgray, i} - I_{italicgray, italicmin})}{((), I_{italicgray, italicmax} - I_{italicgray, italicmin})},

where

\overset{I}{true}

gray ,i is the normalized pixel intensity inside the image, whereas I gray, min and I gray, max are the minimum and maximum local pixel intensity, respectively, and I gray, i is

I_{gray, normali} = ((), 0.299 normalR + 0.587 normalG + 0.114 normalB) / 3,

where I gray, i is the local pixel intensity.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Method for determining mixing index in microfluidics by RGB color model

Mahmud

Tamrin

2020

Asia-Pacific J Chem Eng

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“…Recently, studies of spatial formation of materials on the principle of 3D printing have been developed [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]. For computer manufacturing in the space of different objects, information on the component composition of the material is needed.…”

mentioning

confidence: 99%

Biotechnology for Formation of Aromatic Properties of National- Foodstuffs on the Basis of Meat Raw Material under Influence of Bacterial Crops and Chromato-Mass-Spectrometric Analysis of the Flavoring Components

Ivankin¹

2017

JABB

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Describes the process of the formation of the organoleptic characteristics of the raw sausage "Brunswick", prepared by the original fermented technology of the VM Gorbatov All-Russian Meat Research Institute in the presence of reactive mixtures of starter cultures Lactobacillus plantarum/Staphylococcus carnosus, and Lactobacillus plantarum/Micrococcus varians. Identified changes in the pool of chemicals that make up the flavor and aroma of the national product, associated with the presence of bacterial cultures and added cardamom and black pepper.

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Facile Room‐Temperature Anion Exchange Reactions of Inorganic Perovskite Quantum Dots Enabled by a Modular Microfluidic Platform

Abdel‐Latif

Epps

Kerr

et al. 2019

Adv Funct Materials

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In an effort to produce the materials of next-generation photoelectronic devices, postsynthesis halide exchange reactions of perovskite quantum dots are explored to achieve enhanced bandgap tunability. However, comprehensive understanding of the multifaceted halide exchange reactions is inhibited by their vast relevant parameter space and complex reaction network. In this work, a facile room-temperature strategy is presented for rapid halide exchange of inorganic perovskite quantum dots. A comprehensive understanding of the halide exchange reactions is provided by isolating reaction kinetics from precursor mixing rates utilizing a modular microfluidic platform, Quantum Dot Exchanger (QDExer). The effects of ligand composition and halide salt source on the rate and extent of the halide exchange reactions are illustrated. This fluidic platform offers a unique time-and material-efficient approach for studies of solution phase-processed colloidal nanocrystals beyond those studied here and may accelerate the discovery and optimization of next-generation materials for energy technologies.The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adfm.201900712.to outperform conventional and wellstudied II-VI, IV-VI, and III-V QDs (e.g., CdSe, [7] CdSe/ZnS, [8] PbS, [9] and InP [10] ) in QD-based solar cells [7] and light-emitting diodes (LEDs). [11,12] Perovskite QDs have enabled lower energy consumption and a wider reaching color gamut in QD-based LED displays and unparalleled improvements in photovoltaic power conversion efficiency of QD-based solar cells compared to other third-generation technologies. Recent work [13][14][15] has demonstrated that hybrid perovskite QDs, compared to their thin-film counterparts of equivalent composition, achieve higher open-circuit voltage. The outstanding performance of perovskite QDs can be attributed to their unique optical properties including inherently high charge carrier mobility, long diffusion lengths, high PLQY, and facile bandgap tunability. Moreover, postsynthesis halide exchange of perovskite QDs with halide salts offers an additional degree of control and tunability of the nanocrystal optical properties. [16] Over the last 3 years, various solid-solvent, [17] incompatible solvent-solvent, [18] and homogeneous solution-phase [16] anion exchange strategies have been developed for organic and inorganic perovskite QDs. Among these strategies, homogeneous solution-phase reactions are far more conducive toward continuous nanomanufacturing processes, enabling enhanced parameter control and multidimensional tunability. Further development and implementation of these materials could potentially result in more effective energy technologies toward addressing ever-growing global energy demands via low-cost, high-efficiency solar energy harnessing solutions.Conventionally, manual flask-based techniques have been the primary approach for the synthesis, characterization, and optimization of colloidal QDs. However, the time-and mate...

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Numerical and experimental investigation on micromixers with serpentine microchannels

Cited by 233 publications

References 31 publications

Method for determining mixing index in microfluidics by RGB color model

Method for determining mixing index in microfluidics by RGB color model

Biotechnology for Formation of Aromatic Properties of National- Foodstuffs on the Basis of Meat Raw Material under Influence of Bacterial Crops and Chromato-Mass-Spectrometric Analysis of the Flavoring Components

Facile Room‐Temperature Anion Exchange Reactions of Inorganic Perovskite Quantum Dots Enabled by a Modular Microfluidic Platform

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