Skip to main content
NCBI home page
ACS Omega logoLink to ACS Omega
. 2024 May 17;9(21):22801–22818. doi: 10.1021/acsomega.4c00966

Visualization and Analysis of Mapping Knowledge Domain of Fluid Flow Related to Microfluidic Chip

Kai Fan †, Chang Guo †,*, Nan Liu †,*, Xiaoyu Liang †, Kan Jin †, Zedong Wang †, Chuanjie Zhu ‡
PMCID: PMC11137721  PMID: 38826539

Abstract

graphic file with name ao4c00966_0015.jpg

Microfluidic chips are important tools to study the microscopic flow of fluid. To better understand the research clues and development trends related to microfluidic chips, a bibliometric analysis of microfluidic chips was conducted based on 1115 paper records retrieved from the Web of Science Core Collection database. CiteSpace and VOSviewer software were used to analyze the distribution of annual paper quantity, country/region distribution, subject distribution, institution distribution, major source journals distribution, highly cited papers, coauthor cooperation relationship, research knowledge domain, research focuses, and research frontiers, and a knowledge domain map was drawn. The results show that the number of papers published on microfluidic chips increased from 2010 to 2023, among which China, the United States, Iran, Canada, and Japan were the most active countries in this field. The United States was the most influential country. Nanoscience, energy, and chemical industry and multidisciplinary materials science were the main fields of microfluidic chip research. Lab on a Chip, Microfluidics and Nanofluidics, and Journal of Petroleum Science and Engineering were the main sources of papers published. The fabrication of chips, as well as their applications in porous media flow and multiphase flow, is the main knowledge domain of microfluidic chips. Micromodeling, fluid displacement, wettability, and multiphase flow are the research focuses in this field currently. The research frontiers in this field are enhanced oil recovery, interfacial tension, and stability.

1. Introduction

The motion of microscopic fluid refers to the flow behavior of a fluid on the microscopic scale. Microscopic flow of fluid is very important for understanding the basic properties and flow phenomena of a fluid. The basic properties of fluid viscosity, diffusion coefficient, thermal conductivity, fluid stability, heat and mass transfer are closely related to the microscopic flow of fluid.1 The study of microscopic flow can provide guidance for the engineering applications of fluid. For example, researchers in fluid mechanics can improve the efficiency of fluid delivery and reduce energy loss by designing efficient flow channels.2−5 In chemical applications, efficient reactors and separators can be designed to improve the reaction rate and separation rate by microscopic fluid research.6−8 In bioengineering, the characteristics of fluid flowing through microchannels can be used for cell sorting, enrichment, transport, and other operations.9−12 Therefore, it is of great significance to study the microscopic flow of a fluid.

Microfluidics technology refers to the science and technology involved in systems that use microtubes (tens to hundreds of micrometers in size) to process or manipulate tiny fluids (nanoliters to milliliters in volume). It is a new interdisciplinary subject developed on the basis of microelectronics, micromachinery, bioengineering, and nanotechnology. It focuses on constructing microfluidic channel system to realize various complex microfluidic manipulation functions, rather than reducing the size of the device.13 Microfluidic chips can integrate the experimental steps needed in biology, chemistry, and physics onto tiny chips. They are composed of microchannel, microvalve, micropump, microsensor, and other components, which can realize the functions of fluid control, mixing, separation, detection, and so on. Microfluidic chips are characterized by miniaturization, integration, and portability. They can be used for complex and high-precision experimental operations in a small space. Microfluidic chips are applied to many fields.14−16 In the biomedical field, microfluidic chips can be applied to gene sequencing, drug screening, and disease diagnosis.17−19 They can also be used for chemical reaction, separation and purification and quantitative analysis in chemical analysis.20−26 In terms of energy geology, microfluidic chips have played an important role in oil and gas exploitation, as well as CO2 geological storage.27 By observing the flow of oil, coal methane, and fracturing solvent in the fracture channel of the chips, the single and multiphase flow of oil/gas reservoirs can be investigated.28,29

Bibliometrics is able to represent the complex knowledge system in the research field through data analysis, information processing, and graphical representation. Among the most widely used and important methods are cluster analysis, cocitation analysis, co-occurrence analysis, etc.30,31 Bibliometric methods can be used to present and summarize the academic achievements and development of each research field. For example, Yang et al.32 used the knowledge mapping method to analyze the methodology of emerging technologies in interdisciplinary fields. Wang et al.33 sorted out the development of China’s cross-border e-commerce through bibliometrics. Shao et al.34 analyzed coal porosity using Citespace and VOSviewer software, and obtained the development dynamics of global research on spontaneous combustion of coal and gas hazards and trends.

The research applications of microfluidic chips are extensive. Researchers are active in this field, and the research frontiers of microfluidic chips have been changing. Therefore, it is necessary to analyze and summarize the knowledge framework, research evolution, frontiers, and focuses in the field of microfluidic chips. However, there is a lack of comprehensive analyses. There are few studies using bibliometrics to sort out the research content related to microfluidic chips. In order to enable researchers to better understand the current research status and the development trend of microfluidic chips, bibliometrics was used in this paper to analyze this research field by drawing knowledge maps.

The research objects are related papers of microfluidic chips in the core database of Web of Science (WOS) in the past 14 years. In this research, bibliometrics and visual analysis were used to analyze relevant papers, and visualization software Citespace and VOSviewer were applied. The spatial and temporal distribution of paper, cocitation relationship of paper, cooperative relationship of authors, cooperative relationship between institutions and journals, and co-occurrence relationship of keywords were studied in this research. The influential papers and basic knowledge of microfluidic chips were identified. The current theoretical research and development processes were analyzed. The research frontiers and development directions were also explored, and the evolutionary path of the field was determined.

2. Data and Methods

2.1. Data Source

At present, there are many platforms for paper retrieval worldwide, such as WOS, Google Scholar, Scopus, CNKI, WILEY, and so on. WOS is the world-famous academic citation search engine, covering the top journals of multiple disciplines and a wide range of papers. It provides detailed citation intelligence, which makes it easy to understand the impact of papers and analyze academic trends and research associations. The paper data extracted from WOS can cover the research in most of the microfluidics fields. From this view, this work retrieved data from the core database of WOS. The retrieval formula was set as Topic (TS) = (micromodel OR micromodel OR micro model OR microchip OR microchip OR micro chip OR microfluidic chip) AND TS = (fluid flow). The retrieval time was set from 2010 to 01-01 to 2023-12-31. It was found that there were few relevant research papers before 2010 after several retrieval attempts. The number of papers began to have a certain scale in 2010 and have analytical value. Therefore, the starting point was set as 2010. 1115 retrieval records were obtained from 210 institutions in 66 countries, including 195 authors and 231 publications. The types of paper are shown in Table 1. There were six types of documents: articles, proceedings, reviews, early access, book chapters, and abstracts. Among them, the proportion of articles was the highest, reaching 85.93%, followed by the proceeding papers and reviews, accounting for 8.30 and 4.55%, respectively. The other two were small and negligible. The total number of publications in Table 1 was greater than that of the articles. It was because that a paper might belong to two types of publication. Therefore, this research focused on the first three types of papers.

Table 1. Paper Types Related to Microfluidic Chips.

rank type of paper total publication proportion (%)
1 article 983 85.93
2 proceeding paper 95 8.30
3 review 52 4.55
4 early access 12 1.05
5 book chapters 1 0.085
6 meeting 1 0.085
total   1144  
Open in a new tab

2.2. Method

In this article, the paper about microfluidic chips was quantitatively and visually analyzed by bibliometrics. Bibliometrics analysis is a scientific method to explore the laws of paper content, quantity and distribution by means of cluster analysis, cooperative network analysis, co-occurrence and cocitation analysis, etc., so as to understand the research status and trend of the field to be studied and predict the future development direction of the field.35 VOSviewer and CiteSpace are software tools for constructing and visualizing document metrology networks. They can realize the drawing of scientific knowledge graph and show the relationship between structure, evolution, cooperation, and other aspects of knowledge domain. Their outstanding feature is a strong graphical display ability, which is suitable for large-scale data. They were adopted to visualize and analyze the result and output graphs, so that the development process, research focuses, and field frontiers of the field of microfluidics chips could be better understood. The author cooperation network, author cocitation network, country and organization cocitation network, journal cocitation, keyword cocitation, paper cocitation, and other knowledge maps were drawn by VOSviewer. The keyword timeline and time zone map were drawn by CiteSpace. The main research steps and methods are shown in Figure 1.

Figure 1.

Figure 1

Open in a new tab

Main research steps and methods.

VOSviewer’s clustering is formed by calculating and mapping the similarity matrix. First of all, in order to obtain a similar matrix, it is necessary to process the data and change it into a co-occurrence matrix. Then the co-occurrence matrix is normalized to obtain the similar matrix.36 VOSviewer normalizes the co-occurrence data by using a similarity measure known as association strength.37 The similarity sij between two items i and j is calculated as

2.2. 1

where Cij is the number of co-occurrences of items i and j and wi and wj denote either the total number of occurrences of items i and j or the total number of co-occurrences of these items. Second, the similarity matrix is processed by VOS mapping technology, and the cluster is constructed. The specific principles are as follows: the idea of VOS mapping is to perform a distance-weighted sum between all pairs of elements in the minimization. The higher the similarity between two elements, the higher the weight of their distance squared in the sum. In order to avoid the possibility that all elements are in the same location, the constraint that the average distance between two elements must be equal to 1 is imposed. Let n denote the number of elements to be mapped. The elements 1, ....,n are arranged in such a way that the distance between each pair of elements i and j reflects their similarity sij. Elements with high similarity should be placed close to each other, while elements with low similarity should be placed away from each other. The formula is

2.2. 2

where the vector xi = (xi1,xi2) is the location of item i in a two-dimensional map and where ||*|| is the Euclidean norm. The constraint condition is

2.2. 3

3. Results and Discussion

3.1. Temporal Distribution of the Papers

3.1.1. Temporal Distribution of the Papers Globally

According to the set conditions, 1115 papers related to microfluidic chips were retrieved from the WOS core database. The citation analysis of relevant papers was carried out, and the change of the research on microfluidic chips over time was obtained, as shown in Figure 2. The h-index values here can be exported directly from WOS. The value is intended to show the level of the annual output of paper and the impact of that year. The annual average number of papers published in this field from 2010 to 2023 was 79.64. Through the chart analysis, the trend in microfluidic chip research can be divided into two stages: steady development and rapid growth.

Figure 2.

Figure 2

Open in a new tab

Trend of global publications related to microfluidic chips. (TP: total publications; SOTC: sum of times cited; CPP: citations per paper).

The first stage was stable development (2010–2016), during which the published papers stabilized at about 58 per year. The number of published papers did not increase significantly during this period. A total of 411 papers were published in this field during these seven years, accounting for 35.93% of the total. Most of the published papers used microfluidic chips for porous media and biological cells study.

The second stage is rapid growth (2017–2023), and the number of papers published in this field has increased rapidly since 2017, with an average growth rate of 69.8% higher than that of the first stage. A total of 733 papers were published in 6 years, accounting for 64.07% of the total. In addition, the number of citations also increased significantly and grew rapidly in this stage. In recent years, researchers have invested a lot in the utilization of microfluidic chips in computational fluid dynamics, nanoscale particles, oil, and coal bed gas extraction.12,38−42

3.1.2. Temporal Distribution of the Paper by Active Nations

According to the data searched in the WOS core database, it was concluded that five countries, namely, China, the United States, Iran, Canada, and Japan, were currently the most active in the field of microfluidic chip research and had published far more papers than other countries. The development rules of these five active countries were compared by analyzing the time distribution of their published papers, as shown in Figure 3. Before 2017, the research and utilization of microfluidic chips in the United States was at the leading level, and the number of published papers was much higher than that of other countries, and the number of published papers in the United States in this field was relatively stable without great change. With the development of microfluidic chips, China has paid more attention to the research field of microfluidic chips since 2017. The number of publications of China surged in 2017 with further research, thus affecting the growth of global publications in related fields. It was almost equal to the number of United States. China’s number in this field had continued to increase since then and increased further in 2021 to become the country with the highest number of publications. From 2021 to 2023, the number of published papers in China continued to increase, while the number of published papers in the other four countries declined year by year. Although Japan, Iran and Canada ranked in the top five in terms of paper publication, they have been at a low level compared with China and the United States, and the number of Iranian papers has increased slightly after 2018, which can be seen as China and the United States being in the core position in the research field of microfluidic chips.

Figure 3.

Figure 3

Open in a new tab

Trends in publication growth for the five active countries (China, USA, Iran, Canada, and Japan).

3.2. Spatial Distribution of the Paper

3.2.1. Country/Region Distribution

Data on microfluidic chips in 64 countries and regions were obtained from the WOS database. The top 10 countries and regions with the highest number of published papers were selected for comparative analysis, as shown in Table 2.

Table 2. Top 10 Countries/Region in Microfluidic Chip Research, 2010–2023a.
rank country/region location quantity percentage (%) h-index ACI total link strength
1 China East Asia 338 29.54 34 16.69 109
2 United States North America 280 24.48 51 30.68 169
3 Iran West Asia 106 9.23 23 18.68 44
4 Canada North America 60 5.24 19 20.22 32
5 Japan East Asia 58 5.07 18 17.76 23
6 Germany Europe 54 4.72 22 22.48 54
7 South Korea East Asia 51 4.46 18 26.35 24
8 Netherlands Europe 49 4.28 22 38.98 46
9 Taiwan, China East Asia 47 4.12 13 10.74 10
10 England Europe 46 4.02 21 25.52 54
Open in a new tab
a

ACI: Average Citations per Item.

In Table 2, the quantity is the total number of papers published in each country. Percentage is the proportion of the total publications. The h-index, which is exported from WOS, represents the influence of papers in the country or region. The ACI is the average number of citations of papers. Total link strength is the total number of co-occurrences of a keyword with other keywords. It indicates the frequency of cooperation between a country and other countries. The number of published papers and h-index were plotted on the world map. Countries are marked in different colors to allow for a more intuitive analysis of the region of the country in which the paper was published, as shown in Figure 4.

Figure 4.

Figure 4

Open in a new tab

Top 10 countries/region in paper production and h-index.

As can be seen from Table 2, China and the United States were far ahead in the number of publications in this field and were the two countries with the most. The h-index of the United States was the highest, and the ACI was also at a very high level. It can be seen that the United States had a great influence on microfluidic chip research and was very mature. By contrast, although the number of papers in China was the highest, the ACI ranking was low. The Netherlands had fewer publications and the highest ACI, indicating that research in this field had a huge impact.

The 1115 retrieved records were imported into VOSviewer for calculation of total link strength and visualization of national and regional cooperation networks. The results are shown in Table 2 and Figure 5 respectively. In Figure 5, each node represents a country, and the larger the node, the more papers the country has. The width of the connecting lines between nodes indicates the strength of cooperation between countries. The thicker the lines, the closer the cooperation. The United States and China had paid the most attention to the research of microfluidic chips, and they also had the closest cooperation. Although China ranked first in the number of publications, its cooperation intensity with other countries was low. It was one of the reasons for the low ACI value of China. Meanwhile, the focuses of scholars in different countries in this field were also different. The United States and China paid more attention to nanoscience and chemical analysis. Iran and Canada scholars studied energy fuels most. Japanese researchers focused on the field of instrumentation.

Figure 5.

Figure 5

Open in a new tab

Cooperation among countries and regions in microfluidic chip research.

3.2.2. Disciplinary Distribution of Paper

By analysis of the subject distribution of the paper, the subject categories in the field of microfluidic chips can be better understood. In this paper, 89 disciplines of different categories were obtained through CiteSpace analysis data, among which 10 disciplines with the largest number of publications are shown in Table 3. Among them, nanoscience nanotechnology was the discipline with the largest number of articles published. There were 266 papers published, accounting for 26.49% of the total. The second and third disciplines in terms of publication volume were chemistry analytical and instrumentation, accounting for 23.71 and 20.42%, respectively. Centrality is a concept used to measure how close a point in a network is to the center of the entire network. It represents the attention degree of the paper, and it is an important index to measure the importance of the paper. Of the top 10 subject categories, the highest centrality was multidisciplinary materials science, at 0.22. Obviously, although the number of publications of this discipline was small, it was a research focus in this field. Next are nanoscience, at 0.21, chemical engineering, at 0.15, energy fuels, at 0.14, and instrumentation, at 0.14.

Table 3. Top 10 Subject Categories for Microfluidic Chip Research.
rank quantity centrality WOS categories percentage (%)
1 266 0.21 nanoscience nanotechnology 26.49
2 238 0.13 chemistry analytical 23.71
3 205 0.14 instruments instrumentation 20.42
4 123 0.09 biochemical research methods 12.25
5 121 0.11 chemistry multidisciplinary 12.05
6 120 0.09 physics applied 11.95
7 114 0.14 energy fuels 11.35
8 110 0.15 engineering chemical 10.96
9 87 0.22 materials science multidisciplinary 8.67
10 85 0.01 fluids plasmas 8.47
Open in a new tab

Because the research of microfluidic chips was mostly in the microscopic field, scholars paid more attention to nanoscience, nanotechnology, and material science. At the same time, it was an important tool in the study of fluid flow in energy and chemical industry, so its centrality in chemical industry, energy, and other fields was also high. Therefore, these were popular subjects in the field of microfluidic chip research.

3.2.3. Institutional Distribution of the Paper

According to the data retrieved from the WOS database, a total of 1196 institutions published papers in the field of microfluidic chips. The top 10 institutions with the highest number of publications from 2010 to 2023 are shown in Table 4, which listed the institution, country, quantity of publications, sum of the times cited, average citations per item, and total link strength. Among the top 10 institutions, three were three from the United States and four from China, indicating that China and the United States were the leaders in this field. Sharif University of Technology (Iran) published the most papers (45), followed by the Chinese Academy of Sciences (38) and national laboratories of the United States Department of Energy (25). The top three institutions with the highest ACI were national laboratories of the United States Department of Energy (64.16), University of California (53.43), and Utrecht University (49.91). Chinese institutions published a lot of papers in microfluidic chip research, but their ACIs were not very high and the number of citations was small. The main reason was that Chinese research on microfluidic chips started late, and the research has not been in-depth. In the past two years, with the development of science and technology in China, scientific research investment has been increasing, and the quantity and quality of China’s published papers have been rapidly improved. It is expected that Chinese research institutions will have an increasing influence in this field in the coming years.

Table 4. Top 10 Institutions in Microfluidic Chip Researcha.
rank institution country quantity STC ACI total link strength
1 Sharif University of Technology Iran 45 938 20.84 34
2 Chinese Academy of Sciences China 38 676 17.79 26
3 United States Department of Energy USA 25 1604 64.16 9
4 China University of Petroleum China 24 486 20.25 12
5 University of California USA 23 1229 53.43 4
6 Utrecht University Netherlands 22 1098 49.91 20
7 National Center for Scientific Research France 21 276 13.14 5
8 Tsinghua University China 21 490 23.33 12
9 University of Texas USA 21 332 15.81 10
10 Petroleum University of Technology Iran 20 631 31.55 25
Open in a new tab
a

ACI: Average Citations per Item. STC: Sum of the Times Cited.

VOSviewer was used to screen institutions with no less than five publications. The institutions with fewer than five publications had a total link strength of 0, which was not significant for the analysis. Totally, 102 institutions were obtained for the visualization. Four clusters were drawn by removing clusters with less than seven institutions, as the small cluster with less than seven institutions can be integrated into the large cluster. As can be seen from Figure 6, Sharif University of Technology, Chinese Academy of Sciences, Utrecht University and Tsinghua University had the closest connection and frequent cooperation. The blue cluster was based on two universities, Sharif University of Technology and Tsinghua University. Its main research direction was chemical energy, analyzing the influence of the distribution of aperture cracks on fluids. For example, Mohammadi43 (2020) studied the pore scale mechanism of drilling fluid induced formation damage to improve reservoir performance during production. The red cluster, with the Chinese Academy of Sciences as its core, focused on microfluidic chip design. Song44 (2020) designed a reverse microfluidic chip scheme to solve the problem of channel blockage caused by stagnation zones. Ma45 (2019) developed a novel micropump for pumping fluids in microfluidic chips to increase its resolution and maximum flow rate. The yellow cluster, with Utrecht University as the core, mainly studied the application of microfluidic chips in the direction of water resources. Yin46 (2019) used fluid volumetric simulation to simulate two-phase flow in porous media of different complexity. The green cluster was centered at the University of California and National Taiwan University, and it was focused on nanoscience and biochemistry. Feng47 (2012) used flow control of microfluidic chips to denucleate cells, enabling cells to denucleate at high speed and transfer rapidly.

Figure 6.

Figure 6

Open in a new tab

Cooperative institutions in microfluidic chip research.

3.2.4. Journal Distribution

Journals are carriers of papers; each journal has its established major inclusion categories, and the papers included in them have a greater correlation with the categories in which the journals are positioned. Therefore, analyzing journals as a feature can capture the distribution characteristics in which microfluidic chip-related papers are located and thus understand the research of microfluidic chips in various fields.

Through visual analysis of journals in the field of microfluidic chip research by VOSviewer, a cooperation network of major journals was obtained, as shown in Figure 7. A node represents a journal, and the size of the node indicates the number of papers published by the journal in the field. The larger the node, the more papers published. The thicker the line, the more related the two journals are in the field and the more similar the research content involved. According to the data in Table 5, Lab on a Chip, Microfluidics and Nanofluidics, and Journal of Petroleum Science and Engineering were the three journals with the highest number of published papers.

Figure 7.

Figure 7

Open in a new tab

Cooperative main research journals in microfluidic chip research.

Table 5. Top 10 Journals in Microfluidic Chip Researcha.
rank journal title quantity impact factor (2023) citation index ACI H-index
1 Lab on a Chip 67 6.132 SCI 48.13 30
2 Microfluidics and Nanofluidics 42 2.825 SCIE 14.07 14
3 Journal of Petroleum Science and Engineering 35 4.413 SCI 16.46 16
4 Micromachines 29 3.225 SCI 7.59 8
5 Water Resources Research 29 5.4 SCI 27.66 18
6 Analytical Chemistry 23 7.413 SCI/SCIE 36.7 15
7 Electrophoresis 22 2.915 SCI 13.82 10
8 Scientific Reports 19 4.632 SCI 25.42 13
9 Sensors and Actuators B: Chemical 19 8.409 SCI 15.47 11
10 Advances in Water Resources 18 4.75 SCI 36.56 12
Open in a new tab
a

ACI: Average citations per item.

In this paper, VOSviewer was used to process the paper data in the core database of WOS, and 61 nodes were obtained by excluding noncooperative journals with a total link strength of 0. By using the algorithm of VOSviewer, journals published in similar research fields were clustered to form four clusters. The green and red clusters had the largest number of nodes. The journal with the largest nodes in the red cluster was Microfluidics and Nanofluidic and the cluster’s core research areas focused on nanomaterials. Journals with large green cluster nodes included Journal of Petroleum Science and Engineering and Fuel, and this cluster focused on petroleum geology. The yellow cluster took Lab on a Chip as the core journal, which was related to the design of the microchip’s system and also the largest node in the figure. The main journals of the blue cluster were Energy& Fuel and Scientific Reports. The main research content of this cluster was related to energy as well as clinical sciences. The blue cluster in Figure 7 had more journal collaborations (paper citations) with the green cluster, because the petroleum geology component of the green cluster was more relevant to energy development.

Figure 8 shows the trends of the annual number of publications and the annual average citations of highly productive journals. The peak publication periods of the highly productive journals can be seen in Figure 8a. The main research focuses in the field of microfluidics in each period can be inferred according to the annual number of publications. Using the average annual citations of the highly productive journals, readers can understand the overall quality of the papers and the credibility of the research results in each highly productive journal. Lab on a Chip’s publications peaked in 2011 and 2017, and geology and biology were focal research field in microfluidic chips in Lab on a Chip. Combined with the data in Table 5, the three journals with the higher average number of citations were Lab on a Chip, Analytical Chemistry and Advances in Water Resources, and their impact factors were 6.132, 7.413, and 4.75, respectively.

Figure 8.

Figure 8

Open in a new tab

Number of papers published per year and average citations per year of the highly productive journals of microfluidic chip research.

3.3. Highly Cited Paper Analysis

The number of citations is a direct evaluation of the paper’s quality. Through the analysis of highly cited papers, research focus in the field of microfluidic chips can be realized. The top 15 most cited articles in the field are listed, including title, journal, author, type of paper, publication year, etc., are shown in Table 6.

Table 6. Top 15 Most-Cited Articlesa.

rank title journal type authors Y C NI NC Reference
1 Materials for Microfluidic Chip Fabrication Accounts of Chemical Research review Kangning Ren et al. 2013 544 3 1 (13)
2 Influence of Viscous and Capillary Forces on Immiscible Fluid Displacement: Pore-Scale Experimental Study in a Water-Wet Micromodel Demonstrating Viscous and Capillary Fingering Energy and Fuels article Zhang et al. 2011 305 2 2 (22)
3 Optofluidic Fluorescent Imaging Cytometry on a Cell Phone Analytical Chemistry article Zhu et al. 2011 302 2 2 (56)
4 Enhanced cell sorting and manipulation with combined optical tweezer and microfluidic chip technologies Lab on a Chip article Wang et al. 2011 294 4 2 (48)
5 Acoustofluidics 8: Applications of acoustophoresis in continuous flow microsystems Lab on a Chip article Lenshof et al. 2012 242 2 1 (49)
6 A Review on efficient thermal management of air- and liquid-cooled data centers: From chip to the cooling system Applied Energy review Khalaj and Halgamuge 2017 240 1 1 (50)
7 Automated cellular sample preparation using a Centrifuge-on-a-Chip Lab on a Chip article Mach et al. 2011 232 5 2 (17)
8 Three-dimensional brain-on-a-chip with an interstitial level of flow and its application as an in vitro model of Alzheimer’s disease Lab on a Chip article Park et al. 2015 218 4 1 (51)
9 Lattice-Boltzmann studies of fluid flow in porous media with realistic rock geometries Computers and Mathematics with Applications article Boek and Venturoli 2010 199 2 2 (24)
10 Paper review of low salinity waterflooding from a length and time scale perspective Fuel review Bartels et al. 2019 193 4 2 (18)
11 Primary Human Lung Alveolus-on-a-chip Model of Intravascular Thrombosis for Assessment of Therapeutics Clinical Pharmacology & Therapeutics article Jain et al. 2018 185 7 3 (15)
12 Visualization of improved sweep with foam in heterogeneous porous media using microfluidics Soft Matter article Liontas et al. 2012 173 1 1 (52)
13 Generation of Gradients on a Microfluidic Device: Toward a High-Throughput Investigation of Spermatozoa Chemotaxis Plos One article Zhang et al. 2015 163 3 1 (14)
14 Tumour cell identification by means of Raman spectroscopy in combination with optical traps and microfluidic environments Lab on a Chip article Dochow et al. 2011 162 3 1 (16)
15 A Review of Micromodels and Their Use in Two-Phase Flow Studies Vadose Zone Journal review Karadimitriou and Hassanizadeh 2012 160 1 1 (20)
Open in a new tab
a

Y = Year; C = Citations; NI = Number of Institute(s); NC = Number of Country(ies). (NI and NC are available from the paper information home page in WOS.).

In Table 6, the publication years of the papers with the highest citations are mostly concentrated in the stable development period. Therefore, the previous papers published in this field were of high reference value. Among the 15 most cited papers, most of them were articles and others were reviews. Among them, the review named Materials for Microfluidic Chip Fabrication by Ren53 et al. was the most cited (544), which was published in the journal Accounts of Chemical Research in 2013. It introduced the evolution of the materials used to manufacture microfluidic chips, and the advantages and disadvantages of different materials for application were explored. The article Influence of Viscous and Capillary Forces on Immiscible Fluid Displacement: Pore-Scale Experimental Study in a Water-Wet Micromodel Demonstrating Viscous and Capillary Fingering by Zhang et al.54 in the journal Energy& Fuels was the second most-cited. The effects of viscous force and capillary force on displacement stability and the fluid saturation distribution of immiscible fluids were introduced. A series of displacement tests in porous media were simulated by using a water-wet microfluidic model. They extended and confirmed the numerical simulation results of immiscible motion in porous media by Lenormand et al.55 The article named Optofluidic Fluorescent Imaging Cytometry on a Cell Phone published by Zhu et al.56 in 2011 ranked third in terms of citations. This paper emphasized the application of microfluidic chips in the chemical industry and biomedicine. A photofluid imaging cell device was designed by microfluidic channel and mobile phone camera. Through diode excitation light passing through the microfluidic channel, the mobile phone camera could record and analyze the digital frame of the sample to quantify the number of samples. It could be used for various cell counts as well as water quality analysis.

In addition to the top three most cited papers, there were five studies on fluid movement in rock porous media among the other 12 papers. The remaining seven were about human cells, which mainly explored biological mechanisms such as cell enrichment and movement. It can be seen that microfluidic chip models are increasingly being used in studying the motion behavior of fluid in microstructure, as well as in chemistry, biomedicine, and physics.

3.4. Coauthorship Analysis

Coauthor means someone who appears as the author of the same paper. The visual analysis of the coauthor can clearly show the cooperation network of researchers in the field of microfluidic chips, so as to understand the cooperation situation and research direction of scholars in this field. It can provide useful information for comparative analysis of research levels in different countries.

VOSviewer was used to visualize the author cooperation network in the field of microfluidic chip research. The minimum number of published papers by authors was set to 2, forming a total of 11 clusters with 236 authors. The authors with total link strength of 0 were excluded. Further data processing was performed to obtain Figure 9. The size of the nodes represents the number of published documents. The lines represent cooperation between authors. The author nodes in the same cluster indicate that these authors had a common research direction or were conducting the same research together. Nodes in the position of connecting different clusters show that the author had research cooperation among the different fields. The number of connected clusters represents the author’s cooperation with other scholars in the field of microfluidics. The authors of different research directions mainly established a common research issue by cross-merging between fields and then integrated their own research methods and techniques to conduct cooperative research.

Figure 9.

Figure 9

Open in a new tab

Cooperative authors in microfluidic chip research.

Figure 9 shows 11 clusters, of which the purple and red clusters are closely related to the other clusters. The node of Mart Oostrom, the node of Mohammad Hossein Ghazanfari, and the node of Nikolaos K. Karadimitriou are the largest. Their works promoted communication and contact among authors of different research directions. Scholars in purple clustering mainly used micromodels to study and analyze fluid flow in pore networks. The light green cluster scholars focused on the study of two-phase or multiphase flow. They used microfluidic chips to explore the colloid transport of two-phase and multiphase flows and the transient-steady state flow properties of two-phase flow. Researchers in the blue cluster focused on simulating the effects of different material pores on the oil recovery rate of mineral deposits and the displacement effect of different solute polymers on heavy oil through micromodels. The scholars of green clustering mainly studied the fluid flow characteristics in the pores of carbonate rocks and analyzed the oil flooding of different chemical polymers under favorable viscosity ratio. The yellow cluster researchers used micromodels to study the effects of liquid wettability on the displacement oil phases. The brown clustering scholars worked on the effect of pore surface roughness on fluids, and mainly studied the pore scale flow dynamics of CO2 and water through micromodels. The pink clustering included researchers who studied the effects of wettability and heterogeneity on the displacement of immiscible fluids. The scholars of light blue clustering used micromodels to optimize the CO2 injection formation and storage mechanism. The red clustering focuses on improving the speed and appropriateness of chemical reactions between solvents through micromodels. The specific microchannels were used as a reaction vessel to control reaction rate under different conditions of multicomponent, multiscale, and multiphase states. The light pink clustering scholars mostly applied microfluidic chips in biological studies. The microchannels were used to simulate the xylem channels and stomata of plants to study the water vapor diffusion in plants. In addition, the micromodels were used to grow and enrich cells to simulate the environment in the human body, which is significant for biomedical experiments.

The information on the top 10 authors with the most publications is shown in Table 7, which included the author’s country, organization, average citations per item, and total link strength. As can be seen from Table 7, the highest ACI value was that of Mart Oostrom in the United States (81.62), followed by that of S. Majid Hassanizadeh in Germany (50.73) and N. K. Karadimitriou in Germany (44.5). The United States and Germany had a high level of research in the field of microfluidic chips, and their achievements received a lot of attention. Mohammad Hossein Ghazanfari from Iran published the most papers, but his average citations were at the lower end of the top 10. The number of papers published by Chen Xueye in China was in the middle, but the lowest ACI was his 12.91. Scholars from Iran, China and Japan can cooperate and exchange more with international scholars in the United States and Germany.

Table 7. Authors with the Largest Number of Publications in Microfluidic Chip Research in WOS, 2010–2023a.

rank author organization country quantities ACI links
1 Ghazanfari, Mohammad Hossein Sharif University of Technology Iran 22 27.18 (16)
2 Hassanizadeh, S. Majid University of Stuttgart Germany 15 50.73 (23)
3 Kharrat, Riyaz University of Leoben Austria 15 38.87 (14)
4 Karadimitriou, N. K. University of Stuttgart Germany 14 44.5 (22)
5 Oostrom, Mart Pacific Northwest National Laboratory USA 13 81.62 (30)
6 Masihi, Mohsen Sharif University of Technology Iran 11 26.18 (14)
7 Chen, Xueye Ludong University China 11 12.91 (2)
8 Niasar, Vahid University of Manchester UK 10 37.5 (5)
9 Mohammadi, Saber Iran University of Medical Sciences Iran 9 27.44 (11)
10 Tanaka, Yo Osaka University Japan 8 21 (5)
Open in a new tab
a

ACI: Average citations per item.

3.5. Research Knowledge Domain

Paper cocitation means that two or more papers are cited by other papers at the same time, and then they form a cocitation relationship. The cocited papers have common similarities in the subject matter, so the number of cocitations can represent the relevance of the paper in terms of content. The more the cocitations, the higher the relevance and importance of the paper. These cocited papers constitute the knowledge domain of the research field, and the journals where the cocited papers are located are the carriers of the knowledge domain. In this paper, VOSviewer was used to analyze the cocited papers and source journals to determine the research field of microfluidic chips.

3.5.1. Reference Cocitation Analysis

Cocitation analysis is a bibliometric method used to study the cross-citation relationship between papers. It can reveal which paper has made a significant impact in the academic field.

In Figure 10, VOSviewer was used to perform citation analysis on the selected papers and to process the data to obtain the visual graphics of 43 nodes. The papers with a total link strength of 0 were excluded. The node size represents the number of cocitations, and the distance between nodes represents the correlation between the documents. The closer the documents were, the higher the degree of correlation. As can be seen from Figure 10, the paper citation knowledge based on the field of microfluidic chips mainly included three categories:

  • (i)

    Application of microfluidic chips in fluid flow of porous media (green clustering). With the development of micromodels, they had been widely used in various fields to study the fluid flow inside microstructures. Through micromodels, researchers observed fluid flow and solute transport in pore spaces, thereby improving the understanding of micro and macro flow phenomena. It has been used in the field of fluid displacement in porous media, fluid–fluid interface area and phase saturation measurement and relative permeability measurement and enhanced oil recovery.57

  • (ii)

    Two-phase flow analysis (blue clustering). Two-phase immiscible fluid displacement affects geological carbon sink, oil recovery, and groundwater pollution caused by nonaqueous liquids. Microfluidic chips were used to study the two-phase flow and multiphase flow, and analyze the behavior difference of the transmission process, which can characterize the macroscopic flow of the fluid. The study of two-phase flow has also become one of the research bases in this field.

  • (iii)

    Microfluidics design (red clustering). The microfluidic chip is characterized by a micropipeline network and contains the fluid at nanometer scale. By designing and adjusting the channel mechanism and size in the microfluidic chip, efficient processing and analysis in various media can be realized. Teh et al.58 (2329 citations) reviewed droplet microfluidic systems, which have been shown to be compatible with many chemical and biological reagents and can be used for microreactions ranging from length scales of nanometers and time scales of femtoseconds, as well as biomedical applications for encapsulating biological entities and exploring pathologic cellular problems.

Figure 10.

Figure 10

Open in a new tab

Reference cocitation network of microfluidic chip research.

3.5.2. Journal Cocitation Analysis

At present, the study of multidisciplinary integration is a mainstream. Crossing disciplines can not only broaden the horizon of the discipline but also lead to the forefront of the discipline. By the journal cocitation analysis and the integration of similar journals, the main concentration areas and the core of similar journals can be presented. Meanwhile, this can reflect the interdisciplinary research status of microfluidic chips. VOSviewer was used to take journals with representative disciplines as analysis objects to conduct cocitation analysis of journals. All kinds of miscellaneous journals were integrated and clustered to show their mutual relationships clearly so as to explore the subject structure characteristics of this research field. The visual graph is shown in Figure 11. 249 nodes were obtained through statistical analysis and screening, and these nodes form four clusters. Each node represents a journal, the size of the node represents the number of citations of cocited journals, and the distance between nodes represents the correlation between journals. The closer the distance, the stronger the triggering relationship between journals.

Figure 11.

Figure 11

Open in a new tab

Journal cocitation network of microfluidic chip research.

The red cluster represents engineering chemistry journals, mainly included Lab on a Chip (3258 citations), Analytical Chemistry (1605 citations) and Proceedings of the National Academy of Sciences of the United States (560 citations). The yellow cluster was dominated by biomedical journals, with core journals including Electrophoresis (622 citations) and Journal of Chromatography A (202 citations). The green cluster journals mainly focused on environmental materials, including Water Research (792 citations), Journal of Colloid and Interface Science (502 citations) and Energy& Fuel (410 citations). The Blue Cluster was a thermodynamic Journal with the core of the International Journal of Heat and Mass Transfer (395 citations) and Applied Thermal Engineering (132 citations). It can be seen from Figure 11 that the red cluster is closely related to the yellow cluster and that the interdisciplinary direction of microfluidic chip research is mainly engineering biology.

3.6. Research Focus and Frontier Analysis

3.6.1. Research Focus Analysis

Keywords directly reflect the core content of a paper. VOSviewer and CiteSpace software were used to extract and analyze the keywords of the selected papers, and 4183 keywords were summarized. Through screening, the top 20 keywords with the most frequent occurrences were obtained, as shown in Table 8, which were the most representative pieces of research in this field. Among them, “flow” was the most frequent keyword, appearing 183 times. “Microfluidics” and “micromodel” were the second and third most frequently searched keywords, appearing 146 and 83 times, respectively. The research of these keywords mainly focused on the two-phase flow and multiphase flow displacement of porous media, fluid wetting and nonwetting analysis, and cell biological experiments.

Table 8. Top 20 Keywords of Microfluidic Chip Researches.
rank keywords occurrences total link strength rank keywords occurrences total link strength
1 flow 183 884 11 chip 67 314
2 microfluidics 146 646 12 systems 56 313
3 micromodel 83 583 13 phase flow 39 303
4 porous-media 76 505 14 microfluidic chip 90 300
5 displacement 59 432 15 transport 50 299
6 wettability 60 416 16 mechanisms 44 295
7 multiphase flow 57 409 17 model 52 292
8 water 56 369 18 separation 58 274
9 fluid 58 357 19 pore-scale 31 247
10 simulation 53 328 20 visualization 34 241
Open in a new tab

3.6.2. Keyword Cluster Analysis

The keywords were visualized by VOSviewer and formed a keyword co-occurrence network diagram, as shown in Figure 12. The size of nodes represents the frequency of the keyword, and the lines between nodes represent correlations. The width of the line reflects the strength of the connection between them. As can be seen from Figure 12, there were three clusters of green, blue and red in the keyword co-occurrence network, with “micromodel,” “transport,” and “fluid” as the core keywords, respectively. Among them, the keyword “fluid” appeared the most, and the total connection strength was 884 times. Besides, microfluidic transport in porous media was the main research direction. The popular topics in this field included micromodeling, fluid displacement, wettability research, and multiphase flow research.

Figure 12.

Figure 12

Open in a new tab

Keyword co-occurrence network of microfluidic chip research.

For green clustering, the keyword with the most frequent occurrence was “micromodel” (583 times). The other keywords of this cluster included “wettability,” “displacement,” “porous media,” and “multiphase flow.” This cluster was about the fluids of the porous medium flow in micromodels. The mechanism of macroscopic flow was characterized by the change in multiphase flow in the micromodel. By analyzing the change of its mechanism, the recovery efficiency of oil, coal bed gas, and other geological resources in industry can be improved.

For blue clustering, the cluster mainly revolved around three keywords, “transport,” “stability,, and “viscosity.” In formation, the pores are usually tiny. The capillary phenomenon is an important support for coal bed gas and oil extraction from the formation. At the same time, a stable displacement effect is also the goal of industrial exploitation. The displacement of unstable immiscible fluid affects the recovery rate, and the viscosity is an influence.

For red clustering, the cluster revolved around the keywords “microfluidic,” “flow”, “channel,” “system,” “manufacturing,, and so on. The center word “microfluidic” is typically added to have the paper classified correctly. The focus of the cluster lay in the manufacture and use of microfluidic chip. Microfluidic chips are of high sensitivity, high speed and low cost, and can be used to establish a microenvironment that is easy to control.59 By manipulating fluids and particles with microfluidic chips, some obstacles at the macroscale can be avoided.60 The material of the microfluidic chip determines its characteristics and uses, and different materials will have different pertinency. For the first generation of microfluidic manufactured by glass and silicon, it is very suitable for capillary electrophoresis and solvents.61−63 The elastomer can be used as the production material to culture the cells in the channel and can carry out complex fluid manipulation, which is conducive to the study of biological cells. Microchips made of plastic are popular because they are cheap and varied and can provide a choice for many needs. In conclusion, the development of microfluidic chip manufacturing is maturing, and it is becoming more portable, diversified, and low cost.

3.6.3. Combing Evolution Path

CiteSpace was used to cluster the keywords in the paper. These keywords were arranged on the time axis. They are distributed on a time horizontal line, according to the time when the keywords first appeared in 2010–2023, from left to right. The words on the right side are the overall theme of each timeline, as shown in Figure 13. Each node on the timeline represents a keyword, and the size of the node represents the number of occurrences of that keyword. The keyword that appeared the most times was selected as the label at the same node. The color change in each node indicates the time span of the keyword. When the color changes from dark to light, the degree of change is greater, and the time span of the keyword’s existence is longer. The connection lines between nodes indicate the strength of the co-occurrence relationship between keywords. If the outer ring of the node is purple, the centrality of the keyword was not less than 0.1, and it was the hub connecting other keywords. The yellow nodes in the figure represent the newly emerged keywords in recent years, representing the new research trend, among which the highest centrality of each keyword was “flow” (0.12).

Figure 13.

Figure 13

Open in a new tab

Keywords timeline view in microfluidic chip research.

In the field of microfluidic chips, the largest hub of the keyword was “flow.” As can be seen from Figure 13, from 2010 to 2013, the research on microfluidic chips mainly involved the manufacturing of microfluidic chips and the study of materials, fluid displacement in porous media, and fluid transport mechanism. At that time, the disciplines involved in microfluidic chips were not extensive, mostly in physics and chemistry. Since 2013, microfluidic chips have gradually been applied to biological aspects such as cell enrichment and culture, and a variety of microfluidic models have been used to further study fluid wettability changes, two-phase flow, stability, and other issues.

3.6.4. Research Frontier Identification

Keyword mutability refers to the sudden change of keywords over time. In this article, CiteSpace software was used to list the 15 most mutated keywords, as shown in Table 9. It shows the year in which each a keyword appeared, ended, as well as its strength. From Table 9, it can be analyzed that keywords with strong mutability represent the research frontier of the field in each period. By analyzing the results of key word mutation, the research in microfluidic chips is divided into two stages. In the first stage, “fluid,” “porous medium,” “fluid transport,” and “micromodel” were mainly used to study the microscopic mechanism of fluid flow. In the second stage, “two-phase flow,” “oil-recovery rate,” and “wettability” were the main lines. The research mechanism of micromodel fluids was characterized to the macroscale, so as to improve the recovery rate of industrial oil and coal bed gas resources. From Table 9, “capillary electrophoresis” was of highest mutation intensity (4.76), followed by “multiphase flow” (4.74). Micromodel was a key tool for the study of multiphase fluids.

Table 9. Top 15 Keywords with the Strongest Citation Mutability.

3.6.4.

Open in a new tab

Microfluidic technology has obvious advantages compared with traditional large-scale reaction technologies such as reaction vessels, test tubes, and Petri dishes. It is becoming popular because of its miniaturization, uniformity, and high stability. Previous research was mostly limited to the physics and chemistry field. Researchers now tend to take advantage of its highly integrated and small size and combine it with other fields (biology, medicine, and engineering) to solve problems. At present, “enhanced oil recovery,” “interfacial tension,” and “stability” are in a state of mutation. These have become research frontiers in the field of microfluidic chips. Oil has always been an important fossil energy and strategic resource for all countries. It can be predicted that the use of microfluidic chips to improve the oil recovery rate will be a popular topic in the future. The stable displacement of fluids and the influence of interfacial tension changes on microchannel design will be the main research content of scholars. In addition, the design of microchannels and the manufacture of chip materials will be more diverse and operable, and the application will be more and more extensive.

4. Conclusion

The research status and main knowledge structure in the field of microfluidic chips were introduced by bibliometrics to help researchers better understand the research knowledge domain and research frontier. VOSviewer and Citespace software were used to analyze the spatial and temporal distribution, paper cocitation, keyword co-occurrence, research focuses, and research frontiers. The main conclusions are as follows.

  • (i)

    The number of papers published in the field of microfluidic chips has been increasing rapidly worldwide. As can be seen from the number and distribution of papers, China, the United States, Iran, Canada, and Japan have published the most papers, of which China was the most active country. The papers covered the fields of nanomaterials, energy and chemical engineering, and biochemistry. Sharif University of Technology, Chinese Academy of Sciences, and the United States Department of Energy, which published the most papers, were the most active institutions in the field. From the distribution of journal sources, it can be observed that Lab on a Chip, Microfluidics and Nanofluidics and Journal of Petroleum Science and Technology Engineering were the most published journals in the field, and they were important channels for researchers and institutions to publish papers and exchange academic knowledge.

  • (ii)

    The highly cited papers focused on energy, physics, biology, and other disciplines, which could apply microfluidic chip characteristics to solve specific microscopic problems of specific fluids. According to the author collaboration network, there were 4073 relevant authors. The research direction of the cooperative authors is mostly in the field of energy geology, as well as in the field of biology. Nevertheless, most of these authors had no communication and cooperation with each other. Oostrom from the United States and Hassanizadeh from Germany had the highest average number of citations.

  • (iii)

    ″Two-phase flow,” “microfluidic chip,” “application of microfluidic chip in the study of fluid flow in porous media” were the knowledge domain of microfluidic chip related research. The core journals in this field include Lab on a Chip, Analytical Chemistry Electrophoresis, Water Research, Journal of Colloid and Interface Science, and International Journal of Heat and Mass Transfer. At the same time, “micromodeling,” “fluid displacement,” “wettability research and multiphase flow research” were also the research focuses in this field. As time goes by, the direction of research in this field is also changing, and now the research frontier in the field of microfluidic chips is focused on the aspects of “enhanced oil recovery,” “interfacial tension,” and “stability.”

Fluid flow has always been an important scientific issue in the fields of physics, energy, biology, environment, and so on. Microfluidic chips are widely used in the research of fluid flow at the microscopic scale due to their advantages of miniaturization and diversified design. They provide invaluable insights and technologies applicable to real-world challenges, advancing our understanding of fluid flow in porous material. The knowledge domains obtained from the visual analysis of bibliometrics enable readers to learn about the countries, journals, institutions, and authors that are currently active in the field of microfluidic chip research, as well as the popular directions and the latest results of the research. It is convenient for scholars who do not know the field and those who are ready to know the field to find the key content quickly so that scholars can accelerate the learning of microfluidic chip knowledge field structure. It could be conducive to exploring the new research direction and focus of microfluidic chip and promoting the more in-depth development of the field.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (52204247 and 12302448) and the Natural Science Foundation of Zhejiang Province (LQ21E040005 and LQ23E040009).

Author Contributions

K.F. contributed to writing—original draft, data curation, and visualization. C.G. and N.L. contributed to writing—review and editing, conception, methodology, and software. X.L. and K.J. contributed to software. Z. W. and C.Z. contributed to data curation, investigation, and visualization.

The authors declare no competing financial interest.

References

  1. Silverio V.; Canane P.; Martins T. A.; Afonso R.; Cardoso S.; Batista E. Development of a microfluidic electroosmosis pump on a chip for steady and continuous fluid delivery. Biomed. Eng. 2023, 68 (1), 79–90. 10.1515/bmt-2022-0051. [DOI] [PubMed] [Google Scholar]
  2. Gol B.; Tovar-Lopez F. J.; Kurdzinski M. E.; Tang S. Y.; Petersen P.; Mitchell A.; Khoshmanesh K. Continuous transfer of liquid metal droplets across a fluid–fluid interface within an integrated microfluidic chip. Lab Chip 2015, 15 (11), 2476–2485. 10.1039/C5LC00415B. [DOI] [PubMed] [Google Scholar]
  3. Zhang Y. Q.; Khorshidian H.; Mohammadi M.; et al. Functionalized multiscale visual models to unravel flow and transport physics in porous structures[J]. Water Res. 2020, 175, 115676. 10.1016/j.watres.2020.115676. [DOI] [PubMed] [Google Scholar]
  4. Cui Y. T., Wang Z., Sun C., Sheng Y., Yu C., Zhou C.. et al. The Measurement of Flow Rate of Micro-fluid On-chip by Digital Holography: HOLOGRAPHY, DIFFRACTIVE, OPTICS, AND APPLICATIONS VII[Z]. Conference on Holography, Diffractive Optics, and Applications VII: 2017: 10022.
  5. Wu C.; Almuaalemi H.; Sohan A.; Yin B. Effect of Flow Velocity on Laminar Flow in Microfluidic Chips. Micromachines 2023, 14 (7), 1277. 10.3390/mi14071277. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Santigosa E.; Maspoch S.; Ramos Payán M. Liquid phase microextraction integrated into a microchip device for the extraction of fluoroquinolones from urine samples. Microchem. J. 2019, 145, 280–286. 10.1016/j.microc.2018.10.051. [DOI] [Google Scholar]
  7. Gan J., Xu Y., Cao M. X., Ni Y. A., Peng J. L., Ma L. B., Chuan N.. Research of Separation of Amino Acids on Micro-Free Flow Electrophoresis Chip with Voltage Applied in Two-Dimension: MEMS/NEMS NANO TECHNOLOGY[Z]. 12th Annual Conference of the Chinese Society of Micro-Nano Technology/2nd International Conference of Chinese Society of Micro-Nano Technology: 2011: 483:276–280, 10.4028/www.scientific.net/kem.483.276. [DOI]
  8. Hua X.; Zhu Q.; Liu Y.; et al. A double tangential flow filtration-based microfluidic device for highly efficient separation and enrichment of exosomes[J]. Anal. Chim. Acta 2023, 1258, 341160. 10.1016/j.aca.2023.341160. [DOI] [PubMed] [Google Scholar]
  9. Wang Y.; Shao Z. X.; Zheng W. C.; Xie Y.; Luo G.; Ding M.; Liang Q. A 3D construct of the intestinal canal with wrinkle morphology on a centrifugation configuring microfluidic chip. Biofabrication 2019, 11 (4), 045001. 10.1088/1758-5090/ab21b0. [DOI] [PubMed] [Google Scholar]
  10. Yang H.; Chen T.; Hu Y. C.; Niu F.; Zheng X.; Sun H.; Cheng L.; Sun L. A microfluidic platform integrating dynamic cell culture and dielectrophoretic manipulation for in situ assessment of endothelial cell mechanics[J]. Lab Chip 2023, 23 (16), 3581–3592. 10.1039/D3LC00363A. [DOI] [PubMed] [Google Scholar]
  11. Cheng X. H.; Gupta A.; Chen C. C.; Tompkins R. G.; Rodriguez W.; Toner M. Enhancing the performance of a point-of-care CD4+ T-cell counting microchip through monocyte depletion for HIV/AIDS diagnostics. Lab Chip 2009, 9 (10), 1357–1364. 10.1039/b818813k. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Yoon K.; Jung H. W.; Chun M. S. Two-phase flow in microfluidic-chip design of hydrodynamic filtration for cell particle sorting. Electrophoresis 2020, 41 (10–11), 1002–1010. 10.1002/elps.201900394. [DOI] [PubMed] [Google Scholar]
  13. Ren K. N.; Zhou J. H.; Wu H. K. Materials for Microfluidic Chip Fabrication. Acc. Chem. Res. 2013, 46 (11), 2396–2406. 10.1021/ar300314s. [DOI] [PubMed] [Google Scholar]
  14. Zhang Y.; Xiao R. R.; Yin T. L.; Zou W.; Tang Y.; Ding J.; Yang J. Generation of Gradients on a Microfluidic Device: Toward a High-Throughput Investigation of Spermatozoa Chemotaxis. PLoS One 2015, 10 (11), e0142555 10.1371/journal.pone.0142555. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Jain A.; Barrile R.; van der Meer A. D.; Mammoto A.; Mammoto T.; De Ceunynck K.; Aisiku O.; Otieno M.; Louden C.; Hamilton G.; et al. Primary Human Lung Alveolus-on-a-chip Model of Intravascular Thrombosis for Assessment of Therapeutics. Clin. Pharmacol. Therapeut. 2018, 103 (2), 332–340. 10.1002/cpt.742. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Dochow S.; Krafft C.; Neugebauer U.; Bocklitz T.; Henkel T.; Mayer G.; Albert J.; Popp J. Tumour cell identification by means of Raman spectroscopy in combination with optical traps and microfluidic environments. Lab Chip 2011, 11 (8), 1484–1490. 10.1039/c0lc00612b. [DOI] [PubMed] [Google Scholar]
  17. Mach A. J.; Kim J. H.; Arshi A.; Hur S. C.; Di Carlo D. Automated cellular sample preparation using a Centrifuge-on-a-Chip. Lab Chip 2011, 11 (17), 2827–2834. 10.1039/c1lc20330d. [DOI] [PubMed] [Google Scholar]
  18. Bartels W. B.; Mahani H.; Berg S.; Hassanizadeh S. Literature review of low salinity waterflooding from a length and time scale perspective. Fuel 2019, 236, 338–353. 10.1016/j.fuel.2018.09.018. [DOI] [Google Scholar]
  19. Maghzi A.; Mohammadi S.; Ghazanfari M. H.; Kharrat R.; Masihi M. Monitoring wettability alteration by silica nanoparticles during water flooding to heavy oils in five-spot systems: A pore-level investigation. Exp. Therm. Fluid Sci. 2012, 40, 168–176. 10.1016/j.expthermflusci.2012.03.004. [DOI] [Google Scholar]
  20. Karadimitriou N. K.; Hassanizadeh S. M. A Review of Micromodels and Their Use in Two-Phase Flow Studies. Vadose Zone J. 2012, 11 (3), vzj2011.0072. 10.2136/vzj2011.0072. [DOI] [Google Scholar]
  21. Grate J. W.; Dehoff K. J.; Warner M. G.; Pittman J. W.; Wietsma T. W.; Zhang C.; Oostrom M. Correlation of Oil–Water and Air–Water Contact Angles of Diverse Silanized Surfaces and Relationship to Fluid Interfacial Tensions. LANGMUIR 2012, 28 (18), 7182–7188. 10.1021/la204322k. [DOI] [PubMed] [Google Scholar]
  22. Zhang C. Y.; Oostrom M.; Wietsma T. W.; Grate J. W.; Warner M. G. Influence of Viscous and Capillary Forces on Immiscible Fluid Displacement: Pore-Scale Experimental Study in a Water-Wet Micromodel Demonstrating Viscous and Capillary Fingering. Energy Fuel. 2011, 25 (8), 3493–3505. 10.1021/ef101732k. [DOI] [Google Scholar]
  23. Liu H. H.; Zhang Y. H.; Valocchi A. J. Lattice Boltzmann simulation of immiscible fluid displacement in porous media: Homogeneous versus heterogeneous pore network. Phys. Fluids 2015, 27 (5), 052103. 10.1063/1.4921611. [DOI] [Google Scholar]
  24. Boek E. S.; Venturoli M. Lattice-Boltzmann studies of fluid flow in porous media with realistic rock geometries. Comput. Math. Appl. 2010, 59 (7), 2305–2314. 10.1016/j.camwa.2009.08.063. [DOI] [Google Scholar]
  25. Maghzi A.; Mohammadi S.; Ghazanfari M. H.; Kharrat R.; Masihi M. Monitoring wettability alteration by silica nanoparticles during water flooding to heavy oils in five-spot systems: A pore-level investigation. Exp. Therm. Fluid Sci. 2012, 40, 168–176. 10.1016/j.expthermflusci.2012.03.004. [DOI] [Google Scholar]
  26. Maghzi A.; Mohebbi A.; Kharrat R.; Ghazanfari M. H. Pore-Scale Monitoring of Wettability Alteration by Silica Nanoparticles During Polymer Flooding to Heavy Oil in a Five-Spot Glass Micromodel. Transport Porous Media 2011, 87 (3), 653–664. 10.1007/s11242-010-9696-3. [DOI] [Google Scholar]
  27. Chang C.; Kneafsey T. J.; Zhou Q. L. Experimental study of three-dimensional CO2-water drainage and fracture-matrix interactions in fractured porous media[J]. Adv. Water Resour. 2021, 155, 104008. 10.1016/j.advwatres.2021.104008. [DOI] [Google Scholar]
  28. Chang C.; Kneafsey T. J.; Tokunaga T. K.; Wan J.; Nakagawa S. Impacts of Pore Network-Scale Wettability Heterogeneity on Immiscible Fluid Displacement: A Micromodel Study. Water Resour. Res. 2021, 57 (9), e2021WR030302 10.1029/2021wr030302. [DOI] [Google Scholar]
  29. Chang C.; Kneafsey T. J.; Wan J. M.; Tokunaga T. K.; Nakagawa S. Impacts of Mixed-Wettability on Brine Drainage and Supercritical CO2 Storage Efficiency in a 2.5-D Heterogeneous Micromodel[J]. Water Resour. Res. 2020, 56 (7), e2019WR026789 10.1029/2019wr026789. [DOI] [Google Scholar]
  30. Feofilovs M.; Spalvins K.; Valters K. Bibliometric Review of State-of-the-art Research on Microbial Oils’ Use for Biobased Epoxy. Environ. Clim. Technol. 2023, 27 (1), 150–163. 10.2478/rtuect-2023-0012. [DOI] [Google Scholar]
  31. Wang X.; Liu H.; Pan K.; Huang R.; Gou X.; Qiang Y. Exploring thermal hazard of lithium-ion batteries by bibliometric analysis. J. Energy Storage 2023, 67, 107578. 10.1016/j.est.2023.107578. [DOI] [Google Scholar]
  32. Yang H. Y., Kocaoglu D. F., Anderson T. R., Daim T. U.. Knowledge Mapping Method for Emerging Technology Detection and Examination on Interdisciplinary Research Fields: 2011 PROCEEDINGS OF PICMET 11: TECHNOLOGY MANAGEMENT IN THE ENERGY-SMART WORLD (PICMET)[Z]. Portland International Center for Management of Engineering and Technology (PICMET) Conference on Technology Management in the Energy-Smart World: 2011.
  33. Wang R., Chen S. S., Huang Z. H., Tu Y.. et al. Review on the Status Quo of China’s Cross-border E-commerce Research Based on Bibliometrics: PROCEEDINGS OF EIGHTEENTH WUHAN INTERNATIONAL CONFERENCE ON E-BUSINESS[Z]. 18th Annual Wuhan International Conference on E-Business (WHICEB), 2019, 208–216.
  34. Shao Z. Z.; Tan B.; Guo Y.; et al. Visualization and analysis of mapping knowledge domains for coal pores studies[J]. Fuel 2022, 320, 123761. 10.1016/j.fuel.2022.123761. [DOI] [Google Scholar]
  35. Lang Z.; Wang D.; Liu H.; Gou X. Mapping the knowledge domains of research on corrosion of petrochemical equipment: An informetrics analysis-based study. Eng. Fail. Anal. 2021, 129, 105716. 10.1016/j.engfailanal.2021.105716. [DOI] [Google Scholar]
  36. van Eck N. J.; Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010, 84 (2), 523–538. 10.1007/s11192-009-0146-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. van Eck N. J., Waltman L., Larsen B., Leta J.. VOSviewer: A Computer Program for Bibliometric Mapping: PROCEEDINGS OF ISSI 2009 - 12TH INTERNATIONAL CONFERENCE OF THE INTERNATIONAL SOCIETY FOR SCIENTOMETRICS AND INFORMETRICS, VOL 2[Z]. 12th International Conference of the International-Society-for-Scientometrics-and-Informetrics: 2009: 2:886–897.
  38. Tahir M. U.; Liu W. D.; Zhou H. T.; Memon A.; Ansari U.; Akbar I.; Zafar A.; Shaikh A.; Kashif M.; Urinov A. A review study on micro fluid chips for enhancing the oil recovery by injecting the chemical floods. Therm. Sci. 2020, 24, S423–S432. 10.2298/tsci200620262t. [DOI] [Google Scholar]
  39. Liu H. Y.; Zhang H.; Wang J.; Wei J.; Zhang Y. Biological synthesis of Pt nanoparticles in a microfluidic chip and modeling of the formation process with PBM and CFD. J. Chem. Technol. Biotechnol. 2017, 92 (8), 2171–2177. 10.1002/jctb.5233. [DOI] [Google Scholar]
  40. Meghdadi Isfahani A. H.; Afrand M. Experiment and Lattice Boltzmann numerical study on nanofluids flow in a micromodel as porous medium[J]. Phys. E Low-dimens. Syst. Nanostruct. 2017, 94, 15–21. 10.1016/j.physe.2017.07.008. [DOI] [Google Scholar]
  41. Zheng X.; Jang J. W. Impacts of Wettability on Immiscible Fluid Flow Pattern-Microfluidic Chip Experiment[J]. China Pet. Process. Petrochem. Technol. 2019, 21 (1), 80–89. [Google Scholar]
  42. Tangirala S.; Sheng J. J. Investigation of oil production and flowback in hydraulically-fractured water-wet formations using the Lab-on-a-Chip method[J]. Fuel 2019, 254, 115543. 10.1016/j.fuel.2019.05.126. [DOI] [Google Scholar]
  43. Mohammadi M.; Mahani H. Insights into the Pore-Scale Mechanisms of Formation Damage Induced by Drilling Fluid and Its Control by Silica Nanoparticles. Energy Fuel. 2020, 34 (6), 6904–6919. 10.1021/acs.energyfuels.0c00605. [DOI] [Google Scholar]
  44. Song F. F., Ma Y. T., Wu Y. L., et al. Study of a microfluidic chip with converse fluid: 4TH INTERNATIONAL CONFERENCE ON FLUID MECHANICS AND INDUSTRIAL APPLICATIONS (FMIA 2020)[Z]. 4th International Conference on Fluid Mechanics and Industrial Applications (FMIA): 2020: 1600.
  45. Ma T.; Sun S. X.; Li B. Q.; Chu J. Piezoelectric peristaltic micropump integrated on a microfluidic chip. Sens. Actuators, A 2019, 292, 90–96. 10.1016/j.sna.2019.04.005. [DOI] [Google Scholar]
  46. Yin X.; Zarikos I.; Karadimitriou N. K.; Raoof A.; Hassanizadeh S. Direct simulations of two-phase flow experiments of different geometry complexities using Volume-of-Fluid (VOF) method. Chem. Eng. Sci. 2019, 195, 820–827. 10.1016/j.ces.2018.10.029. [DOI] [Google Scholar]
  47. Feng L., Ichikawa A., Arai F., et al. Continuous Enucleation of Bovine Oocyte by Microrobot with Local Flow Distribution Control: 2012 INTERNATIONAL CONFERENCE ON MANIPULATION, MANUFACTURING AND MEASUREMENT ON THE NANOSCALE (3M-NANO)[Z], et al. International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO), 2012, 59–64.
  48. Wang X.; Chen S.; Kong M.; et al. Enhanced cell sorting and manipulation with combined optical tweezer and microfluidic chip technologies. Lab Chip 2011, 11 (21), 3656–3662. 10.1039/C1LC20653B. [DOI] [PubMed] [Google Scholar]
  49. Lenshof A.; Magnusson C.; Laurell T. Acoustofluidics 8: Applications of acoustophoresis in continuous flow microsystems. Lab Chip 2012, 12 (7), 1210–1223. 10.1039/C2LC21256K. [DOI] [PubMed] [Google Scholar]
  50. Habibi Khalaj A. H.; Halgamuge S. K. A Review on efficient thermal management of air- and liquid-cooled data centers: From chip to the cooling system. Applied Energy 2017, 205, 1165–1188. 10.1016/j.apenergy.2017.08.037. [DOI] [Google Scholar]
  51. Park J.; Lee B. K.; Jeong G. S.; et al. Three-dimensional brain-on-a-chip with an interstitial level of flow and its application as an in vitro model of Alzheimer’s disease. Lab Chip 2015, 15 (1), 141–150. 10.1039/c4lc00962b. [DOI] [PubMed] [Google Scholar]
  52. Ma K.; Liontas R.; Conn C. A.; et al. Visualization of improved sweep with foam in heterogeneous porous media using microfluidics. Soft Matter 2012, 8 (41), 10669–10675. 10.1039/c2sm25833a. [DOI] [Google Scholar]
  53. Ren K. N.; Zhou J. H.; Wu H. K. Materials for Microfluidic Chip Fabrication. Acc. Chem. Res. 2013, 46 (11), 2396–2406. 10.1021/ar300314s. [DOI] [PubMed] [Google Scholar]
  54. Zhang C. Y.; Oostrom M.; Wietsma T. W.; Grate J. W.; Warner M. G. Influence of Viscous and Capillary Forces on Immiscible Fluid Displacement: Pore-Scale Experimental Study in a Water-Wet Micromodel Demonstrating Viscous and Capillary Fingering. Energy Fuel. 2011, 25 (8), 3493–3505. 10.1021/ef101732k. [DOI] [Google Scholar]
  55. Lenormand R.; Touboul E.; Zarcone C. Numerical models and experiments on immiscible displacements in porous media. Fluid Mech. 1988, 189, 165–187. 10.1017/S0022112088000953. [DOI] [Google Scholar]
  56. Zhu H. Y.; Mavandadi S.; Coskun A. F.; Yaglidere O.; Ozcan A. Optofluidic Fluorescent Imaging Cytometry on a Cell Phone. Anal. Chem. 2011, 83 (17), 6641–6647. 10.1021/ac201587a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Wang K.; You Q.; Long Q. M.; Zhou B.; Wang P. Experimental study of the mechanism of nanofluid in enhancing the oil recovery in low permeability reservoirs using microfluidics. Petrol. Sci. 2023, 20 (1), 382–395. 10.1016/j.petsci.2022.09.026. [DOI] [Google Scholar]
  58. Teh S. Y.; Lin R.; Hung L. H.; Lee A. P. Droplet microfluidics. Lab Chip 2008, 8 (2), 198–220. 10.1039/b715524g. [DOI] [PubMed] [Google Scholar]
  59. Cai S. X.; Jin Y. W.; Lin Y.; He Y.; Zhang P.; Ge Z.; Yang W. Micromixing within microfluidic devices: Fundamentals, design, and fabrication. Biomicrofluidics 2023, 17 (6), 061503. 10.1063/5.0178396. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Loganathan A. K.; Devaraj R.; Krishnamoorthy L. Revolutionizing plasma separation: cutting-edge design, simulation, and optimization techniques in microfluidics using COMSOL. Microfluid. Nanofluidics 2023, 27 (11), 73. 10.1007/s10404-023-02684-x. [DOI] [Google Scholar]
  61. Karadimitriou N. K.; Hassanizadeh S. M. A Review of Micromodels and Their Use in Two-Phase Flow Studies. Vadose Zone J. 2012, 11 (3), vzj2011.0072. 10.2136/vzj2011.0072. [DOI] [Google Scholar]
  62. Ren K. N.; Zhou J. H.; Wu H. K. Materials for Microfluidic Chip Fabrication. Acc. Chem. Res. 2013, 46 (11), 2396–2406. 10.1021/ar300314s. [DOI] [PubMed] [Google Scholar]
  63. Chen G. D.; Fachin F.; Fernandez-Suarez M.; Wardle B. L.; Toner M. Nanoporous Elements in Microfluidics for Multiscale Manipulation of Bioparticles. Small 2011, 7 (8), 1061–1067. 10.1002/smll.201002076. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from ACS Omega are provided here courtesy of American Chemical Society

RESOURCES