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Tang T, Julian T, Ma D, Yang Y, Li M, Hosokawa Y, Yalikun Y. A review on intelligent impedance cytometry systems: Development, applications and advances. Anal Chim Acta 2023; 1269:341424. [PMID: 37290859 DOI: 10.1016/j.aca.2023.341424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/10/2023]
Abstract
Impedance cytometry is a well-established technique for counting and analyzing single cells, with several advantages, such as convenience, high throughput, and no labeling required. A typical experiment consists of the following steps: single-cell measurement, signal processing, data calibration, and particle subtype identification. At the beginning of this article, we compared commercial and self-developed options extensively and provided references for developing reliable detection systems, which are necessary for cell measurement. Then, a number of typical impedance metrics and their relationships to biophysical properties of cells were analyzed with respect to the impedance signal analysis. Given the rapid advances of intelligent impedance cytometry in the past decade, this article also discussed the development of representative machine learning-based approaches and systems, and their applications in data calibration and particle identification. Finally, the remaining challenges facing the field were summarized, and potential future directions for each step of impedance detection were discussed.
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Affiliation(s)
- Tao Tang
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, Nara, 630-0192, Japan; Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117583, Singapore
| | - Trisna Julian
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, Nara, 630-0192, Japan
| | - Doudou Ma
- Center for Biosystems Dynamics Research (BDR), RIKEN, 1-3 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Yang Yang
- Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan, 572000, PR China
| | - Ming Li
- School of Engineering, Macquarie University, Sydney, 2109, Australia
| | - Yoichiroh Hosokawa
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, Nara, 630-0192, Japan
| | - Yaxiaer Yalikun
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, Nara, 630-0192, Japan; Center for Biosystems Dynamics Research (BDR), RIKEN, 1-3 Yamadaoka, Suita, Osaka, 565-0871, Japan.
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2
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Sahin MA, Werner H, Udani S, Di Carlo D, Destgeer G. Flow lithography for structured microparticles: fundamentals, methods and applications. LAB ON A CHIP 2022; 22:4007-4042. [PMID: 35920614 DOI: 10.1039/d2lc00421f] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Structured microparticles, with unique shapes, customizable sizes, multiple materials, and spatially-defined chemistries, are leading the way for emerging 'lab on a particle' technologies. These microparticles with engineered designs find applications in multiplexed diagnostics, drug delivery, single-cell secretion assays, single-molecule detection assays, high throughput cytometry, micro-robotics, self-assembly, and tissue engineering. In this article we review state-of-the-art particle manufacturing technologies based on flow-assisted photolithography performed inside microfluidic channels. Important physicochemical concepts are discussed to provide a basis for understanding the fabrication technologies. These photolithography technologies are compared based on the structural as well as compositional complexity of the fabricated particles. Particles are categorized, from 1D to 3D particles, based on the number of dimensions that can be independently controlled during the fabrication process. After discussing the advantages of the individual techniques, important applications of the fabricated particles are reviewed. Lastly, a future perspective is provided with potential directions to improve the throughput of particle fabrication, realize new particle shapes, measure particles in an automated manner, and adopt the 'lab on a particle' technologies to other areas of research.
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Affiliation(s)
- Mehmet Akif Sahin
- Control and Manipulation of Microscale Living Objects, Central Institute for Translational Cancer Research (TranslaTUM), Department of Electrical and Computer Engineering, Technical University of Munich, Einsteinstraße 25, Munich 81675, Germany.
| | - Helen Werner
- Control and Manipulation of Microscale Living Objects, Central Institute for Translational Cancer Research (TranslaTUM), Department of Electrical and Computer Engineering, Technical University of Munich, Einsteinstraße 25, Munich 81675, Germany.
| | - Shreya Udani
- Department of Bioengineering, University of California, Los Angeles, California 90095, USA.
| | - Dino Di Carlo
- Department of Bioengineering, University of California, Los Angeles, California 90095, USA.
- Department of Mechanical and Aerospace Engineering, California NanoSystems Institute and Jonsson Comprehensive Cancer Center, University of California, Los Angeles, California 90095, USA
| | - Ghulam Destgeer
- Control and Manipulation of Microscale Living Objects, Central Institute for Translational Cancer Research (TranslaTUM), Department of Electrical and Computer Engineering, Technical University of Munich, Einsteinstraße 25, Munich 81675, Germany.
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Ashley BK, Sui J, Javanmard M, Hassan U. Aluminum Oxide-Coated Particle Differentiation Employing Supervised Machine Learning and Impedance Cytometry. IEEE INTERNATIONAL CONFERENCE ON NANO/MICRO ENGINEERED AND MOLECULAR SYSTEMS. IEEE INTERNATIONAL CONFERENCE ON NANO/MICRO ENGINEERED AND MOLECULAR SYSTEMS 2022; 2022:10.1109/nems54180.2022.9791160. [PMID: 35782306 PMCID: PMC9245459 DOI: 10.1109/nems54180.2022.9791160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
This article uses a supervised machine learning (ML) system for identifying groups of nanoparticles coated with metal oxides of varying thicknesses using a microfluidic impedance cytometer. These particles generate unique impedance signatures when probed with a multifrequency electric field and finds applications in enabling many multiplexed biosensing technologies. However, current experimental and data processing techniques are unable to sensitively differentiate different metal oxide coated particle types. Here, we employ various machine learning models and collect multiple particle metrics measured. In reported experiments, a 75% accuracy was determined to separate aluminum oxide coated (10nm and 30nm), which is significantly greater than observing only univariate data between different microparticle types. This approach will enable ML models to differentiate such particles with greater accuracies.
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Affiliation(s)
- Brandon K Ashley
- Department of Biomedical Engineering Rutgers, New Jersey State University, Piscataway, United States
| | - Jianye Sui
- Department of Electrical Engineering Rutgers, New Jersey State University, Piscataway, United States
| | - Mehdi Javanmard
- Department of Electrical Engineering Rutgers, New Jersey State University, Piscataway, United States
| | - Umer Hassan
- Department of Electrical Engineering Rutgers, New Jersey State University, Piscataway, United States
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Lee S, de Rutte J, Dimatteo R, Koo D, Di Carlo D. Scalable Fabrication and Use of 3D Structured Microparticles Spatially Functionalized with Biomolecules. ACS NANO 2022; 16:38-49. [PMID: 34846855 PMCID: PMC10874522 DOI: 10.1021/acsnano.1c05857] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Microparticles with defined shapes and spatial chemical modification can interface with cells and tissues at the cellular scale. However, conventional methods to fabricate shaped microparticles have trade-offs between the throughput of manufacture and the precision of particle shape and chemical functionalization. Here, we achieved scalable production of hydrogel microparticles at rates of greater than 40 million/hour with localized surface chemistry using a parallelized step emulsification device and temperature-induced phase-separation. The approach harnesses a polymerizable polyethylene glycol (PEG) and gelatin aqueous two-phase system (ATPS) which conditionally phase separates within microfluidically generated droplets. Following droplet formation, phase separation is induced and phase separated droplets are subsequently cross-linked to form uniform crescent and hollow shell particles with gelatin functionalization on the boundary of the cavity. The gelatin localization enabled deterministic cell loading in subnanoliter-sized crescent-shaped particles, which we refer to as nanovials, with cavity dimensions tuned to the size of cells. Loading on nanovials also imparted improved cell viability during analysis and sorting using standard fluorescence activated cell sorters, presumably by protecting cells from shear stress. This localization effect was further exploited to selectively functionalize capture antibodies to nanovial cavities enabling single-cell secretion assays with reduced cross-talk in a simplified format.
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Affiliation(s)
- Sohyung Lee
- Department of Chemical and Biomolecular Engineering, University of California- Los Angeles, Los Angeles, CA 90095, USA
| | - Joseph de Rutte
- Partillion Bioscience, Los Angeles, CA 90095, USA
- Department of Bioengineering, University of California- Los Angeles, Los Angeles, California 90095, USA
| | - Robert Dimatteo
- Department of Chemical and Biomolecular Engineering, University of California- Los Angeles, Los Angeles, CA 90095, USA
| | - Doyeon Koo
- Department of Bioengineering, University of California- Los Angeles, Los Angeles, California 90095, USA
| | - Dino Di Carlo
- Department of Bioengineering, University of California- Los Angeles, Los Angeles, California 90095, USA
- Department of Mechanical and Aerospace Engineering, University of California- Los Angeles, Los Angeles, CA 90095, USA
- California NanoSystems Institute (CNSI), University of California- Los Angeles, Los Angeles, CA 90095, USA
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Ashley BK, Hassan U. Time-domain signal averaging to improve microparticles detection and enumeration accuracy in a microfluidic impedance cytometer. Biotechnol Bioeng 2021; 118:4428-4440. [PMID: 34370302 PMCID: PMC8589102 DOI: 10.1002/bit.27910] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 07/30/2021] [Accepted: 08/01/2021] [Indexed: 01/12/2023]
Abstract
Microfluidic impedance cytometry is a powerful system to measure micro and nano-sized particles and is routinely used in point-of-care disease diagnostics and other biomedical applications. However, small objects near a sensor's detection limit are plagued with relatively significant background noise and are difficult to identify for every case. While many data processing techniques can be utilized to reduce noise and improve signal quality, frequently they are still inadequate to push sensor detection limits. Here, we report the first demonstration of a novel signal averaging algorithm effective in noise reduction of microfluidic impedance cytometry data, improving enumeration accuracy, and reducing detection limits. Our device uses a 22 µm tall × 100 µm wide (with 30 µm wide focused aperture) microchannel and gold coplanar microelectrodes that generate an electric field, recording bipolar pulses from polystyrene microparticles flowing through the channel. In addition to outlining a modified moving signal averaging technique theoretically and with a model data set, we also performed a compendium of characterization experiments including variations in flow rate, input voltage, and particle size. Multivariate metrics from each experiment are compared including signal amplitude, pulse width, background noise, and signal-to-noise ratio (SNR). Incorporating our technique resulted in improved SNR and counting accuracy across all experiments conducted, and the limit of detection improved from 5 to 1 µm particles without modifying microchannel dimensions. Succeeding this, we envision implementing our modified moving average technique to develop next-generation microfluidic impedance cytometry devices with an expanded dynamic range and improved enumeration accuracy. This can be exceedingly useful for many biomedical applications, such as infectious disease diagnostics where devices may enumerate larger-scale immune cells alongside sub-micron bacterium in the same sample.
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Affiliation(s)
- Brandon K. Ashley
- Department of Biomedical Engineering, Rutgers, the State University of New Jersey, Piscataway, NJ, 08854, USA
| | - Umer Hassan
- Department of Biomedical Engineering, Rutgers, the State University of New Jersey, Piscataway, NJ, 08854, USA
- Department of Electrical and Computer Engineering, Rutgers, the State University of New Jersey, Piscataway, NJ, 08854, USA
- Global Health Institute, Rutgers, the State University of New Jersey, New Brunswick, NJ, 08901, USA
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Ashley BK, Mukerji I, Hassan U. Investigating Cell-Particle Conjugate Orientations in a Microfluidic Channel to Ameliorate Impedance-based Signal Acquisition and Detection . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:7233-7236. [PMID: 34892768 PMCID: PMC8767423 DOI: 10.1109/embc46164.2021.9630171] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Many biomedical experimental assays rely on cell-to-microparticle conjugation and their subsequent detection to quantify disease-related biomarkers. In this report, we investigated the effect of particle attachment position on a cell's surface to a signal acquired using impedance cytometry. We also present a novel configuration of independent coplanar microelectrodes positioned at the bottom and top of the microfluidic channel. In simulation results, our configuration accurately identifies different particle positions around the cell. We implemented a channel design with focusing regions between electrodes, and considered external factors around the channel such as polydimethylsiloxane (PDMS) interacting with the electric field and physical constraints of top electrodes placed farther away from the channel which improves detection accuracy.
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Ashley BK, Hassan U. Frequency-Time Domain (FTD) Impedance Data Analysis to Improve Accuracy of Microparticle Enumeration in a Microfluidic Electronic Counter. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:1201-1204. [PMID: 34891502 PMCID: PMC8764509 DOI: 10.1109/embc46164.2021.9630635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Experimental background noise present in biosensors' data hinders the ability for sensitive and accurate detection of critical biomarkers. Here, we report our digital signal processing analysis with respect to frequency and time domain (FTD) data to reduce noise in an experimental microfluidic impedance cytometer. We evaluated the effectiveness of employed noise filtering techniques independently, including baseline drift correction, high frequency noise filtering, and powerline interference mitigation. We further explored the combined effect of all filters and determine improvements in signal-to-noise (SNR) ratio and particle counting accuracy. By removing noise regimes, SNR improved with this impedance cytometer device, and our future efforts will explore filtering effects of more specific and uncommon noise spectrums to greater optimize device performance.
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Xi H, Jiang H, Juhas M, Zhang Y. Multiplex Biosensing for Simultaneous Detection of Mutations in SARS-CoV-2. ACS OMEGA 2021; 6:25846-25859. [PMID: 34632242 PMCID: PMC8491437 DOI: 10.1021/acsomega.1c04024] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 09/10/2021] [Indexed: 05/02/2023]
Abstract
COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has become the world's largest public health emergency of the past few decades. Thousands of mutations were identified in the SARS-CoV-2 genome. Some mutants are more infectious and may replace the original strains. Recently, B.1.1.7(Alpha), B1.351(Beta), and B.1.617.2(Delta) strains, which appear to have increased transmissibility, were detected. These strains accounting for the high proportion of newly diagnosed cases spread rapidly over the world. Particularly, the Delta variant has been reported to account for a vast majority of the infections in several countries over the last few weeks. The application of biosensors in the detection of SARS-CoV-2 is important for the control of the COVID-19 pandemic. Due to high demand for SARS-CoV-2 genotyping, it is urgent to develop reliable and efficient systems based on integrated multiple biosensor technology for rapid detection of multiple SARS-CoV-2 mutations simultaneously. This is important not only for the detection and analysis of the current but also for future mutations. Novel biosensors combined with other technologies can be used for the reliable and effective detection of SARS-CoV-2 mutants.
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Affiliation(s)
- Hui Xi
- College
of Science, Harbin Institute of Technology
(Shenzhen), Shenzhen, Guangdong 518055, China
| | - Hanlin Jiang
- College
of Science, Harbin Institute of Technology
(Shenzhen), Shenzhen, Guangdong 518055, China
| | - Mario Juhas
- Medical
and Molecular Microbiology Unit, Department of Medicine, Faculty of
Science and Medicine, University of Fribourg, Fribourg CH-1700, Switzerland
| | - Yang Zhang
- College
of Science, Harbin Institute of Technology
(Shenzhen), Shenzhen, Guangdong 518055, China
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Ashley BK, Hassan U. Point-of-critical-care diagnostics for sepsis enabled by multiplexed micro and nanosensing technologies. WILEY INTERDISCIPLINARY REVIEWS. NANOMEDICINE AND NANOBIOTECHNOLOGY 2021; 13:e1701. [PMID: 33650293 PMCID: PMC8447248 DOI: 10.1002/wnan.1701] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 12/14/2020] [Accepted: 01/08/2021] [Indexed: 11/12/2022]
Abstract
Sepsis is responsible for the highest economic and mortality burden in critical care settings around the world, prompting the World Health Organization in 2018 to designate it as a global health priority. Despite its high universal prevalence and mortality rate, a disproportionately low amount of sponsored research funding is directed toward diagnosis and treatment of sepsis, when early treatment has been shown to significantly improve survival. Additionally, current technologies and methods are inadequate to provide an accurate and timely diagnosis of septic patients in multiple clinical environments. For improved patient outcomes, a comprehensive immunological evaluation is critical which is comprised of both traditional testing and quantifying recently proposed biomarkers for sepsis. There is an urgent need to develop novel point-of-care, low-cost systems which can accurately stratify patients. These point-of-critical-care sensors should adopt a multiplexed approach utilizing multimodal sensing for heterogenous biomarker detection. For effective multiplexing, the sensors must satisfy criteria including rapid sample to result delivery, low sample volumes for clinical sample sparring, and reduced costs per test. A compendium of currently developed multiplexed micro and nano (M/N)-based diagnostic technologies for potential applications toward sepsis are presented. We have also explored the various biomarkers targeted for sepsis including immune cell morphology changes, circulating proteins, small molecules, and presence of infectious pathogens. An overview of different M/N detection mechanisms are also provided, along with recent advances in related nanotechnologies which have shown improved patient outcomes and perspectives on what future successful technologies may encompass. This article is categorized under: Diagnostic Tools > Biosensing.
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Affiliation(s)
- Brandon K. Ashley
- Department of Biomedical Engineering, Rutgers, State University of New Jersey, Piscataway, NJ, 08854, USA
| | - Umer Hassan
- Department of Biomedical Engineering, Rutgers, State University of New Jersey, Piscataway, NJ, 08854, USA
- Department of Electrical Engineering, Rutgers, State University of New Jersey, Piscataway, NJ, 08854, USA
- Global Health Institute, Rutgers, State University of New Jersey. Piscataway, NJ, 08854, USA
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Honrado C, Bisegna P, Swami NS, Caselli F. Single-cell microfluidic impedance cytometry: from raw signals to cell phenotypes using data analytics. LAB ON A CHIP 2021; 21:22-54. [PMID: 33331376 PMCID: PMC7909465 DOI: 10.1039/d0lc00840k] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The biophysical analysis of single-cells by microfluidic impedance cytometry is emerging as a label-free and high-throughput means to stratify the heterogeneity of cellular systems based on their electrophysiology. Emerging applications range from fundamental life-science and drug assessment research to point-of-care diagnostics and precision medicine. Recently, novel chip designs and data analytic strategies are laying the foundation for multiparametric cell characterization and subpopulation distinction, which are essential to understand biological function, follow disease progression and monitor cell behaviour in microsystems. In this tutorial review, we present a comparative survey of the approaches to elucidate cellular and subcellular features from impedance cytometry data, covering the related subjects of device design, data analytics (i.e., signal processing, dielectric modelling, population clustering), and phenotyping applications. We give special emphasis to the exciting recent developments of the technique (timeframe 2017-2020) and provide our perspective on future challenges and directions. Its synergistic application with microfluidic separation, sensor science and machine learning can form an essential toolkit for label-free quantification and isolation of subpopulations to stratify heterogeneous biosystems.
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Affiliation(s)
- Carlos Honrado
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, USA.
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Zhou P, He J, Huang L, Yu Z, Su Z, Shi X, Zhou J. Microfluidic High-Throughput Platforms for Discovery of Novel Materials. NANOMATERIALS 2020; 10:nano10122514. [PMID: 33333718 PMCID: PMC7765132 DOI: 10.3390/nano10122514] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 11/28/2020] [Accepted: 12/02/2020] [Indexed: 12/12/2022]
Abstract
High-throughput screening is a potent technique to accelerate the discovery and development of new materials. By performing massive synthesis and characterization processes in parallel, it can rapidly discover materials with desired components, structures and functions. Among the various approaches for high-throughput screening, microfluidic platforms have attracted increasing attention. Compared with many current strategies that are generally based on robotic dispensers and automatic microplates, microfluidic platforms can significantly increase the throughput and reduce the consumption of reagents by several orders of magnitude. In this review, we first introduce current advances of the two types of microfluidic high-throughput platforms based on microarrays and microdroplets, respectively. Then the utilization of these platforms for screening different types of materials, including inorganic metals, metal alloys and organic polymers are described in detail. Finally, the challenges and opportunities in this promising field are critically discussed.
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Affiliation(s)
- Peipei Zhou
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou 510006, China; (P.Z.); (J.H.); (Z.Y.); (Z.S.)
- School of Mechatronic Engineering, Guangdong Polytechnic Normal University, Guangzhou 510665, China
| | - Jinxu He
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou 510006, China; (P.Z.); (J.H.); (Z.Y.); (Z.S.)
| | - Lu Huang
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou 510006, China; (P.Z.); (J.H.); (Z.Y.); (Z.S.)
- Correspondence: (L.H.); (J.Z.); Tel./Fax: +86-20-3938-7890 (J.Z.)
| | - Ziming Yu
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou 510006, China; (P.Z.); (J.H.); (Z.Y.); (Z.S.)
| | - Zhenning Su
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou 510006, China; (P.Z.); (J.H.); (Z.Y.); (Z.S.)
| | - Xuetao Shi
- National Engineering Research Centre for Tissue Restoration and Reconstruction, School of Material Science and Engineering, South China University of Technology, Guangzhou 510640, China;
| | - Jianhua Zhou
- Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou 510006, China; (P.Z.); (J.H.); (Z.Y.); (Z.S.)
- Correspondence: (L.H.); (J.Z.); Tel./Fax: +86-20-3938-7890 (J.Z.)
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