Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Active-matrix digital microfluidics for high-throughput, precise droplet handling

Abstract

Active-matrix digital microfluidics (AM-DMF) leverages semiconductor-derived electrode arrays to dynamically control thousands of micrometre-scale droplets and has emerged as a transformative platform for high-throughput and precise manipulation of liquid samples. This technology enables various programmable operations, such as droplet generation, transport, mixing and dilution, to be performed with unparalleled accuracy and, thereby, overcomes several limitations of conventional microchannel and passive-matrix digital microfluidics. This Review provides a critical analysis of the design principles and transformative potential of AM-DMF, focusing on its potential biomedical applications in genomics, single-cell analysis and drug discovery. Important contributions of artificial intelligence that increase the efficiency and reliability of complex AM-DMF workflows are also discussed. Despite this considerable progress, further innovation is needed to overcome ongoing challenges such as biofouling, reagent selectivity and electrode stability. This Review outlines future directions for AM-DMF as a versatile tool in life sciences and showcases its role in enabling next-generation droplet manipulation and workflow automation.

Key points

  • The transition from passive-matrix (PM) to active-matrix (AM) digital microfluidics (DMF) chip configurations notably enhances scalability, enabling both efficient and precise control of large-scale droplet arrays.

  • AM-DMF primarily uses various thin-film transistor types, printed circuit board or complementary metal oxide semiconductor processes; its driving circuits have undergone continuous evolution to enable precise droplet driving and sensing.

  • The evolution of DMF architectures from PM (DMF 1.0) through AM (DMF 2.0), gate-on-array (DMF 2.5) and integrated circuit-driven (DMF 3.0) iterations has been a key driver in advancing the commercialization of this technology.

  • Integration with multifunctional modules and artificial intelligence renders AM-DMF a promising platform for automated, multifunctional workflows.

  • AM-DMF is a transformative platform for high-throughput applications such as genomics, single-cell analysis and drug discovery.

  • Ongoing challenges such as biofouling, reagent compatibility and electrode stability remain to be addressed to promote the widespread adoption and commercialization of AM-DMF.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Digital microfluidics device architectures.
Fig. 2: Technological fundamentals of active-matrix digital microfluidics.
Fig. 3: Roadmap of active-matrix digital microfluidics.
Fig. 4: Future applications and potential prospects for active-matrix digital microfluidics.

Similar content being viewed by others

References

  1. Sackmann, E. K., Fulton, A. L. & Beebe, D. J. The present and future role of microfluidics in biomedical research. Nature 507, 181–189 (2014).

    Article  Google Scholar 

  2. Dou, Y. et al. Orally administrable H2S-scavenging metal–organic framework prepared by co-flow microfluidics for comprehensive restoration of intestinal milieu. Adv. Mater. 35, 2210047 (2023).

    Article  Google Scholar 

  3. Zhang, D., Bi, H., Liu, B. & Qiao, L. Detection of pathogenic microorganisms by microfluidics based analytical methods. Anal. Chem. 90, 5512–5520 (2018).

    Article  Google Scholar 

  4. Czerniecki, S. M. et al. High-throughput screening enhances kidney organoid differentiation from human pluripotent stem cells and enables automated multidimensional phenotyping. Cell Stem Cell 22, 929.e4–940.e4 (2018).

    Article  Google Scholar 

  5. Cao, Y. et al. Bead-jet printing enabled sparse mesenchymal stem cell patterning augments skeletal muscle and hair follicle regeneration. Nat. Commun. 13, 7463 (2022).

    Article  Google Scholar 

  6. Zhong, B. et al. Interindividual- and blood-correlated sweat phenylalanine multimodal analytical biochips for tracking exercise metabolism. Nat. Commun. 15, 624 (2024).

    Article  Google Scholar 

  7. Gopinathan, K. A., Mishra, A., Mutlu, B. R., Edd, J. F. & Toner, M. A microfluidic transistor for automatic control of liquids. Nature 622, 735–741 (2023).

    Article  Google Scholar 

  8. Peterson, V. M. et al. Multiplexed quantification of proteins and transcripts in single cells. Nat. Biotechnol. 35, 936–939 (2017).

    Article  Google Scholar 

  9. Li, C. et al. Under oil open-channel microfluidics empowered by exclusive liquid repellency. Sci. Adv. 6, eaay9919 (2020).

    Article  Google Scholar 

  10. Novak, R. et al. Robotic fluidic coupling and interrogation of multiple vascularized organ chips. Nat. Biomed. Eng. 4, 407–420 (2020).

    Article  Google Scholar 

  11. Li, J., Ha, N. S., Liu, T. ', Van Dam, R. M. & Kim, C.-J. ‘CJ’ Ionic-surfactant-mediated electro-dewetting for digital microfluidics. Nature 572, 507–510 (2019).

    Article  Google Scholar 

  12. Samiei, E., Tabrizian, M. & Hoorfar, M. A review of digital microfluidics as portable platforms for lab-on a-chip applications. Lab Chip 16, 2376–2396 (2016).

    Article  Google Scholar 

  13. Cai, L. et al. Highly multiplexing, throughput and efficient single-cell protein analysis with digital microfluidics. Small Methods 8, e2400375 (2024).

    Article  Google Scholar 

  14. Liang, S. et al. DMF-Bimol: counting mRNA and protein molecules in single cells with digital microfluidics. Anal. Chem. 96, 17253–17261 (2024).

    Article  Google Scholar 

  15. Antkowiak, P. L. et al. Integrating DNA encapsulates and digital microfluidics for automated data storage in DNA. Small 18, e2107381 (2022).

    Article  Google Scholar 

  16. Yetisen, A. K., Akram, M. S. & Lowe, C. R. Paper-based microfluidic point-of-care diagnostic devices. Lab Chip 13, 2210–2251 (2013).

    Article  Google Scholar 

  17. Hou, Y. et al. Biosensor-based microfluidic platforms for rapid clinical detection of pathogenic bacteria. Adv. Funct. Mater. 35, 2411484 (2025).

    Article  Google Scholar 

  18. Hu, C. et al. “Cell-on-demand” digital microfluidics for real-time low-abundance single-cell isolation and sample analysis. Small 21, e2504239 (2025).

    Article  Google Scholar 

  19. Mazutis, L. et al. Single-cell analysis and sorting using droplet-based microfluidics. Nat. Protoc. 8, 870–891 (2013).

    Article  Google Scholar 

  20. Scott, E. Y. et al. Integrating single-cell and spatially resolved transcriptomic strategies to survey the astrocyte response to stroke in male mice. Nat. Commun. 15, 1584 (2024).

    Article  Google Scholar 

  21. Torabinia, M., Dakarapu, U. S., Asgari, P., Jeon, J. & Moon, H. Electrowetting-on-dielectric (EWOD) digital microfluidic device for in-line workup in organic reactions: a critical step in the drug discovery work cycle. Sens. Actuators B Chem. 330, 129252 (2021).

    Article  Google Scholar 

  22. Zhai, J. et al. Drug screening on digital microfluidics for cancer precision medicine. Nat. Commun. 15, 4363 (2024).

    Article  Google Scholar 

  23. Ai, Y., Xie, R., Xiong, J. & Liang, Q. Microfluidics for biosynthesizing: from droplets and vesicles to artificial cells. Small 16, e1903940 (2020).

    Article  Google Scholar 

  24. Ngocho, K. et al. Synthetic cells from droplet-based microfluidics for biosensing and biomedical applications. Small 20, e2400086 (2024).

    Article  Google Scholar 

  25. Lin, G. et al. Magnetofluidic platform for multidimensional magnetic and optical barcoding of droplets. Lab Chip 15, 216–224 (2015).

    Article  Google Scholar 

  26. Ding, X. et al. Surface acoustic wave microfluidics. Lab Chip 13, 3626–3649 (2013).

    Article  Google Scholar 

  27. Park, J. et al. Acoustothermal tweezer for droplet sorting in a disposable microfluidic chip. Lab Chip 17, 1031–1040 (2017).

    Article  Google Scholar 

  28. Fan, Y., Wu, H., Wang, J. & Lv, J. Field-programmable topographic-morphing array for general-purpose lab-on-a-chip systems. Adv. Mater. 37, 2410604 (2025).

    Article  Google Scholar 

  29. Yang, B. et al. Automated and label-free detection of HIV DNA via digital microfluidics-chemiluminescence analysis. Sens. Actuators B Chem. 389, 133905 (2023).

    Article  Google Scholar 

  30. Hong, S. Y. et al. Stretchable active matrix temperature sensor array of polyaniline nanofibers for electronic skin. Adv. Mater. 28, 930–935 (2016).

    Article  Google Scholar 

  31. Shayan, M., Bhattacharjee, S., Song, Y.-A., Chakrabarty, K. & Karri, R. Toward secure microfluidic fully programmable valve array biochips. IEEE Trans. Very Large Scale Integr. VLSI Syst. 27, 2755–2766 (2019).

    Article  Google Scholar 

  32. Hadwen, B. et al. Programmable large area digital microfluidic array with integrated droplet sensing for bioassays. Lab Chip 12, 3305–3313 (2012). This paper presents an AM-DMF device with integrated impedance sensing and demonstrates its application in a colorimetric glucose assay of human blood serum samples.

    Article  Google Scholar 

  33. Ma, H. et al. Large-area manufacturable active matrix digital microfluidics platform for high-throughput biosample handling. In 2020 IEEE International Electron Devices Meeting 35.5.1–35.5.4 (IEEE, 2020). This work presents an a-Si:H TFT-based AM-DMF platform that achieves precise single-pixel droplet manipulation with a volume variation of ~1%.

  34. Yu, J. et al. Field programmable digital microfluidics chip for high-throughput droplet array manipulation. In 2023 International Electron Devices Meeting 1–4 (IEEE, 2023). This paper presents an AM-DMF chip with 640 × 280 pixels that uses 9T2C GOA and 3T1C circuits to enable high-throughput parallel droplet manipulation and single-cell operations for advanced biological applications.

  35. Anderson, S., Hadwen, B. & Brown, C. Thin-film-transistor digital microfluidics for high value in vitro diagnostics at the point of need. Lab Chip 21, 962–975 (2021). This paper demonstrates a fully automated sample-to-answer SARS-CoV-2 RT–PCR (PCR with reverse transcription) test from saliva using a high-resolution AM-DMF chip, showcasing its potential for point-of-need molecular diagnostics.

    Article  Google Scholar 

  36. Wang, D. et al. Active-matrix digital microfluidics design for field programmable high-throughput digitalized liquid handling. iScience 27, 109324 (2024). This article introduces a field-programmable droplet array system with a novel TFT design that can manipulate thousands of 0.5-nl droplets.

    Article  Google Scholar 

  37. Jiang, S. et al. Droplet position sensing in TFT active-matrix digital microfluidics. IEEE Electron. Device Lett. 45, 1361–1364 (2024).

    Article  Google Scholar 

  38. Guo, Z. et al. Deep learning-assisted label-free parallel cell sorting with digital microfluidics. Adv. Sci. 12, 2408353 (2025). This work presents a label-free cell sorting method that integrates an AM-DMF platform with a YOLOv8-based deep learning algorithm to enable real-time image recognition and morphology-based cell sorting.

    Article  Google Scholar 

  39. Lu, G.-R. et al. Flexible droplet routing in active matrix-based digital microfluidic biochips. ACM Trans. Des. Autom. Electron. Syst. 23, 37 (2018).

    Article  Google Scholar 

  40. Jia, Z. et al. Artificial intelligence-enabled multipurpose smart detection in active-matrix electrowetting-on-dielectric digital microfluidics. Microsyst. Nanoeng. 10, 139 (2024).

    Article  Google Scholar 

  41. Geng, H., Feng, J., Stabryla, L. M. & Cho, S. K. Dielectrowetting manipulation for digital microfluidics: creating, transporting, splitting, and merging of droplets. Lab Chip 17, 1060–1068 (2017).

    Article  Google Scholar 

  42. Shin, D. J., Trick, A. Y., Hsieh, Y.-H., Thomas, D. L. & Wang, T.-H. Sample-to-answer droplet magnetofluidic platform for point-of-care hepatitis C viral load quantitation. Sci. Rep. 8, 9793 (2018).

    Article  Google Scholar 

  43. Qian, J. et al. Rapid and comprehensive detection of viral antibodies and nucleic acids via an acoustofluidic integrated molecular diagnostics chip: AIMDx. Sci. Adv. 11, eadt5464 (2025).

    Article  Google Scholar 

  44. Lee, K. S. et al. Optofluidic Raman-activated cell sorting for targeted genome retrieval or cultivation of microbial cells with specific functions. Nat. Protoc. 16, 634–676 (2021).

    Article  Google Scholar 

  45. Yafia, M. et al. Microfluidic chain reaction of structurally programmed capillary flow events. Nature 605, 464–469 (2022).

    Article  Google Scholar 

  46. Abdelgawad, M., Park, P. & Wheeler, A. R. Optimization of device geometry in single-plate digital microfluidics. J. Appl. Phys. 105, 094506 (2009).

    Article  Google Scholar 

  47. Peng, J. et al. All-in-one digital microfluidics pipeline for proteomic sample preparation and analysis. Chem. Sci. 14, 2887–2900 (2023).

    Article  Google Scholar 

  48. Peng, C., Zhang, Z., Kim, C. J. & Ju, Y. S. EWOD (electrowetting on dielectric) digital microfluidics powered by finger actuation. Lab Chip 14, 1117–1122 (2014).

    Article  Google Scholar 

  49. Tan, J. et al. Orbital electrowetting-on-dielectric for droplet manipulation on superhydrophobic surfaces. Adv. Mater. 36, 2314346 (2024).

    Article  Google Scholar 

  50. Gong, J. & Kim, C. J. All-electronic droplet generation on-chip with real-time feedback control for EWOD digital microfluidics. Lab Chip 8, 898–906 (2008).

    Article  Google Scholar 

  51. Li, J. & Kim, C. C. Current commercialization status of electrowetting-on-dielectric (EWOD) digital microfluidics. Lab Chip 20, 1705–1712 (2020).

    Article  Google Scholar 

  52. Lippmann, M. G. Relations entre les phénomènes électriques et capillaires [French]. Ann. Chim. Phys. 5, 494–579 (1875).

    Google Scholar 

  53. Berge, B. Electrocapillarity and wetting of insulator films by water. Comptes Rendus Acad. Sci. 2b Mec. 317, 157–163 (1993).

    Google Scholar 

  54. Cho, S. K., Moon, H. & Kim, C.-J. Creating, transporting, cutting, and merging liquid droplets by electrowetting-based actuation for digital microfluidic circuits. J. Microelectromech. Syst. 12, 70–80 (2003).

    Article  Google Scholar 

  55. Chatterjee, D., Shepherd, H. & Garrell, R. L. Electromechanical model for actuating liquids in a two-plate droplet microfluidic device. Lab Chip 9, 1219–1229 (2009).

    Article  Google Scholar 

  56. Li, D. et al. Point-of-care blood coagulation assay enabled by printed circuit board-based digital microfluidics. Lab Chip 22, 709–716 (2022).

    Article  Google Scholar 

  57. Vo, P. Q. N., Husser, M. C., Ahmadi, F., Sinha, H. & Shih, S. C. C. Image-based feedback and analysis system for digital microfluidics. Lab Chip 17, 3437–3446 (2017).

    Article  Google Scholar 

  58. Jain, V. & Patrikar, R. M. A low-cost portable dynamic droplet sensing system for digital microfluidics applications. IEEE Trans. Instrum. Meas. 69, 3623–3630 (2020).

    Article  Google Scholar 

  59. Ahmadi, F. et al. Integrating machine learning and digital microfluidics for screening experimental conditions. Lab Chip 23, 81–91 (2023).

    Article  Google Scholar 

  60. Shen, J. et al. A low-temperature digital microfluidic system used for protein–protein interaction detection. Lab Chip 23, 4390–4399 (2023).

    Article  Google Scholar 

  61. Li, M. et al. One-shot high-resolution melting curve analysis for KRAS point-mutation discrimination on a digital microfluidics platform. Lab Chip 22, 537–549 (2022).

    Article  Google Scholar 

  62. Jiang, S. et al. Thin-film transistor digital microfluidics circuit design with capacitance-based droplet sensing. Sensors 24, 4789 (2024).

    Article  Google Scholar 

  63. Wang, D. et al. Active-matrix digital microfluidics design and optimization for high-throughput droplets manipulation. IEEE J. Electron. Devices Soc. 11, 411–415 (2023).

    Article  Google Scholar 

  64. Luo, Z. et al. Programmable high integration and resolution digital microfluidic device driven by thin film transistor arrays. IEEE Access 10, 30573–30582 (2022). This paper presents a high-resolution integrated circuit-driven AM-DMF device featuring a custom control system with droplet detection and feedback functions.

    Article  Google Scholar 

  65. Qin, F. et al. Solution for mass production of high-throughput digital microfluidic chip based on a-Si TFT with in-pixel boost circuit. Micromachines 12, 1199 (2021).

    Article  MathSciNet  Google Scholar 

  66. Xu, Y. et al. Digital microfluidic lab-on-a-chip on a TFT glass substrate enabling point-of-care testing. IEEE Electron. Device Lett. 44, 1500–1503 (2023).

    Article  Google Scholar 

  67. Hu, S. et al. Large-area electronics-enabled high-resolution digital microfluidics for parallel single-cell manipulation. Anal. Chem. 95, 6905–6914 (2023).

    Article  Google Scholar 

  68. Brakke, K. A. The Surface Evolver. Exp. Math. 1, 141–165 (1992).

    Article  MathSciNet  Google Scholar 

  69. Lienemann, J., Greiner, A. & Korvink, J. G. in Design Automation Methods and Tools for Microfluidics-Based Biochips (eds Chakrabarty, K. & Zeng, J.) 53–84 (Springer, 2006).

  70. Alistar, M., Pop, P. & Madsen, J. Synthesis of application-specific fault-tolerant digital microfluidic biochip architectures. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 35, 764–777 (2016).

    Article  Google Scholar 

  71. Madec, M. et al. Multiphysics simulation of biosensors involving 3D biological reaction–diffusion phenomena in a standard circuit EDA environment. IEEE Trans. Circuits Syst. Regul. Pap. 66, 2188–2197 (2019).

    Article  Google Scholar 

  72. Zeng, J. Modeling and simulation of electrified droplets and its application to computer-aided design of digital microfluidics. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 25, 224–233 (2006).

    Article  Google Scholar 

  73. Lienemann, J., Greiner, A. & Korvink, J. G. Modeling, simulation, and optimization of electrowetting. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 25, 234–247 (2006).

    Article  Google Scholar 

  74. Fink, G., Hamidovic, M., Haselmayr, W. & Wille, R. Automatic design of droplet-based microfluidic ring networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40, 339–349 (2021).

    Article  Google Scholar 

  75. Lee, H., Liu, Y., Ham, D. & Westervelt, R. M. Integrated cell manipulation system — CMOS/microfluidic hybrid. Lab Chip 7, 331–337 (2007).

    Article  Google Scholar 

  76. Khorasani, M., Behnam, M., Van Den Berg, L., Backhouse, C. J. & Elliott, D. G. High-voltage CMOS controller for microfluidics. IEEE Trans. Biomed. Circuits Syst. 3, 89–96 (2009).

    Article  Google Scholar 

  77. Noh, J. H., Noh, J., Kreit, E., Heikenfeld, J. & Rack, P. D. Toward active-matrix lab-on-a-chip: programmable electrofluidic control enabled by arrayed oxide thin film transistors. Lab Chip 12, 353–360 (2011).

    Article  Google Scholar 

  78. Cao, W. et al. The future transistors. Nature 620, 501–515 (2023).

    Article  Google Scholar 

  79. Wan, C. et al. Toward a brain–neuromorphics interface. Adv. Mater. 36, 2311288 (2024).

    Article  Google Scholar 

  80. Hsiao, H., Hsu, Y., Liu, A., Hsieh, J. & Lin, Y. Ultrasensitive refractive index sensing based on the quasi-bound states in the continuum of all-dielectric metasurfaces. Adv. Opt. Mater. 10, 2200812 (2022).

    Article  Google Scholar 

  81. Wu, T. & Suzuki, Y. Liquid dielectrophoresis on electret: a novel approach towards CMOS-driven digital microfludics. J. Adhes. Sci. Technol. 26, 2025–2045 (2012).

    Article  Google Scholar 

  82. Chung, J., Hwang, H. Y., Chen, Y. & Lee, T. Y. Microfluidic packaging of high-density CMOS electrode array for lab-on-a-chip applications. Sens. Actuators B Chem. 254, 542–550 (2018).

    Article  Google Scholar 

  83. Pollack, M. G. Electrowetting-Based Microactuation of Droplets for Digital Microfluidics. PhD dissertation, Duke Univ. (2001).

  84. Khan, S. M., Gumus, A., Nassar, J. M. & Hussain, M. M. CMOS enabled microfluidic systems for healthcare based applications. Adv. Mater. 30, 1705759 (2018).

    Article  Google Scholar 

  85. Carvalho, J. et al. Single-use microfluidic device for purification and concentration of environmental DNA from river water. Talanta 226, 122109 (2021).

    Article  Google Scholar 

  86. Hua, Z. et al. Multiplexed real-time polymerase chain reaction on a digital microfluidic platform. Anal. Chem. 82, 2310–2316 (2010).

    Article  Google Scholar 

  87. Geng, D. et al. Thin-film transistors for large-area electronics. Nat. Electron. 6, 963–972 (2023).

    Article  Google Scholar 

  88. Nathan, A. et al. Amorphous silicon thin film transistor circuit integration for organic LED displays on glass and plastic. IEEE J. Solid State Circuits 39, 1477–1486 (2004).

    Article  Google Scholar 

  89. Meng, Z., Wang, M. & Wong, M. High performance low temperature metal-induced unilaterally crystallized polycrystalline silicon thin film transistors for system-on-panel applications. IEEE Trans. Electron. Devices 47, 404–409 (2000).

    Article  Google Scholar 

  90. Lee, S. & Nathan, A. Subthreshold Schottky-barrier thin-film transistors with ultralow power and high intrinsic gain. Science 354, 302–304 (2016).

    Article  Google Scholar 

  91. Kohno, A., Sameshima, T., Sano, N., Sekiya, M. & Hara, M. High performance poly-Si TFTs fabricated using pulsed laser annealing and remote plasma CVD with low temperature processing. IEEE Trans. Electron. Devices 42, 251–257 (1995).

    Article  Google Scholar 

  92. Siddik, A. B. et al. Blue laser annealed sub-micron channel p-type low temperature poly-Si TFT without kink effect for high-resolution display. IEEE Electron. Device Lett. 42, 172–175 (2021).

    Article  Google Scholar 

  93. Sheng, J. et al. Amorphous IGZO TFT with high mobility of 70 cm2 /(V s) via vertical dimension control using PEALD. ACS Appl. Mater. Interfaces 11, 40300–40309 (2019).

    Article  Google Scholar 

  94. Xing, Y. et al. A robust and scalable active-matrix driven digital microfluidic platform based on printed-circuit board technology. Lab Chip 21, 1886–1896 (2021). This work proposes a robust and scalable PCB-based AM-DMF platform and demonstrates its versatility through the on-chip synthesis of a pentapeptide.

    Article  Google Scholar 

  95. Jiang, S., Wang, D., Ma, H., Nathan, A. & Yu, J. Low temperature polysilicon pixel circuits for active-matrix digital microfluidic chips. Displays 88, 103048 (2025).

    Article  Google Scholar 

  96. Kwon, S. et al. Prototype of flexible digital X-ray imaging detector. IEEE Electron. Device Lett. 45, 2439–2442 (2024).

    Article  Google Scholar 

  97. Hu, C., Jin, K. & Ma, H. A universal model for continuous “one-to-two” high-efficient droplet generation in digital microfluidics. Appl. Phys. Lett. 122, 181601 (2023).

    Article  Google Scholar 

  98. Jin, K. et al. “One-to-three” droplet generation in digital microfluidics for parallel chemiluminescence immunoassays. Lab Chip 21, 2892–2900 (2021).

    Article  Google Scholar 

  99. Shaik, F. A. et al. Thin-film-transistor array: an exploratory attempt for high throughput cell manipulation using electrowetting principle. J. Micromech. Microeng. 27, 054001 (2017).

    Article  Google Scholar 

  100. Yang, Z. et al. AM-DMF-SCP: integrated single-cell proteomics analysis on an active matrix digital microfluidic chip. JACS Au 4, 1811–1823 (2024). This study presents an integrated AM-DMF platform for all-in-one single-cell proteomics processing, which minimizes sample loss and improves the sensitivity of mass spectrometry analysis.

    Article  Google Scholar 

  101. Zhang, B. et al. Polar coordinate active-matrix digital microfluidics for high-resolution concentration gradient generation. Lab Chip 24, 2193–2201 (2024).

    Article  Google Scholar 

  102. Wei, Y., Wang, D., Jiang, S., Ma, H. & Yu, J. A high-voltage serial-in-parallel-out shift register with amorphous silicon TFTs. IEEE J. Electron. Devices Soc. 11, 416–420 (2023).

    Article  Google Scholar 

  103. Kalsi, S. et al. Rapid and sensitive detection of antibiotic resistance on a programmable digital microfluidic platform. Lab Chip 15, 3065–3075 (2015). This study demonstrates rapid, highly sensitive detection of an antibiotic resistance gene via AM-DMF-based recombinase polymerase amplification, which achieved a 100-fold improvement in detection limit compared to benchtop methods.

    Article  Google Scholar 

  104. Yang, G. et al. A portable driving system for high-resolution active matrix electrowetting display based on FPGA. J. Soc. Inf. Disp. 28, 287–296 (2020).

    Article  Google Scholar 

  105. Zhang, T. et al. Optimizing bipolar reset waveform to improve grayscale stability in active matrix electrowetting displays. Micromachines 15, 1247 (2024).

    Article  Google Scholar 

  106. Ji, J. et al. AM-DMF-ddRPA: an all-in-one digital microfluidic platform for rapid and automatic digital nucleic acid analysis. Angew. Chem. Int. Ed. 64, e202501913 (2025). This study describes a rapid, fully automated AM-DMF-based droplet digital recombinase polymerase amplification platform, which completes sample-to-answer quantitative detection of influenza viruses within 60 min.

    Article  Google Scholar 

  107. Fobel, R., Fobel, C. & Wheeler, A. R. DropBot: an open-source digital microfluidic control system with precise control of electrostatic driving force and instantaneous drop velocity measurement. Appl. Phys. Lett. 102, 193513 (2013).

    Article  Google Scholar 

  108. Saha, B., Das, B. & Majumder, M. A deep-reinforcement learning approach for optimizing homogeneous droplet routing in digital microfluidic biochips. Nanotechnol. Precis. Eng. 6, 023001 (2023).

    Article  Google Scholar 

  109. Bandodkar, A. J. et al. Battery-free, skin-interfaced microfluidic/electronic systems for simultaneous electrochemical, colorimetric, and volumetric analysis of sweat. Sci. Adv. 5, eaav3294 (2019).

    Article  Google Scholar 

  110. Xu, Y. et al. A TFT-based on-chip optical sensor for detection of chemiluminescence in lab-on-a-chip. IEEE Electron. Device Lett. 46, 1119–1122 (2025).

    Article  Google Scholar 

  111. Hu, C. et al. Ultra-fast electronic detection of antimicrobial resistance genes using isothermal amplification and thin film transistor sensors. Biosens. Bioelectron. 96, 281–287 (2017).

    Article  Google Scholar 

  112. Medina-Sánchez, M., Martínez-Domingo, C., Ramon, E. & Merkoçi, A. An inkjet-printed field-effect transistor for label-free biosensing. Adv. Funct. Mater. 24, 6291–6302 (2014).

    Article  Google Scholar 

  113. Shah, G. J., Ohta, A. T., Chiou, E. P., Wu, M. C. & Kim, C. J. EWOD-driven droplet microfluidic device integrated with optoelectronic tweezers as an automated platform for cellular isolation and analysis. Lab Chip 9, 1732–1739 (2009).

    Article  Google Scholar 

  114. Lamanna, J. et al. Digital microfluidic isolation of single cells for -omics. Nat. Commun. 11, 5632 (2020).

    Article  Google Scholar 

  115. Jiang, S. et al. Efficient yeast cell collection and manipulation based on dielectrophoresis-integrated digital microfluidics. Langmuir 41, 8312–8321 (2025).

    Article  Google Scholar 

  116. Huang, B. et al. Counting low-copy number proteins in a single cell. Science 315, 81–84 (2007).

    Article  Google Scholar 

  117. Hoshino, K. et al. Microchip-based immunomagnetic detection of circulating tumor cells. Lab Chip 11, 3449–3457 (2011).

    Article  Google Scholar 

  118. Wang, X. et al. Positive dielectrophoresis-based Raman-activated droplet sorting for culture-free and label-free screening of enzyme function in vivo. Sci. Adv. 6, eabb3521 (2020).

    Article  Google Scholar 

  119. Wang, Z. et al. Structure-controllable Ag aerogel optimized SERS-digital microfluidic platform for ultrasensitive and high-throughput detection of harmful substances. Sens. Actuators B Chem. 401, 134934 (2024).

    Article  Google Scholar 

  120. Das, A., Fehse, S., Polack, M., Panneerselvam, R. & Belder, D. Surface-enhanced Raman spectroscopic probing in digital microfluidics through a microspray hole. Anal. Chem. 95, 1262–1272 (2023).

    Google Scholar 

  121. Das, A. et al. On-the-fly mass spectrometry in digital microfluidics enabled by a microspray hole: toward multidimensional reaction monitoring in automated synthesis platforms. J. Am. Chem. Soc. 144, 10353–10360 (2022).

    Article  Google Scholar 

  122. Wang, Y. et al. Highly sensitive and automated surface enhanced Raman scattering-based immunoassay for H5N1 detection with digital microfluidics. Anal. Chem. 90, 5224–5231 (2018).

    Article  Google Scholar 

  123. Li, B. B. et al. Cell invasion in digital microfluidic microgel systems. Sci. Adv. 6, eaba9589 (2020).

    Article  Google Scholar 

  124. Jia, Z. et al. Intelligent single-cell manipulation: LLMs- and object detection-enhanced active-matrix digital microfluidics. Microsyst. Nanoeng. 11, 133 (2025). This research develops an AM-DMF platform that leverages large language models for automated workflow generation and advanced object detection for high-precision single-cell manipulation and identification.

    Article  Google Scholar 

  125. Shen, R. et al. Nucleic acid analysis on electrowetting-based digital microfluidics. Trends Anal. Chem. 158, 116826 (2023).

    Article  Google Scholar 

  126. Shamsi, M. H., Choi, K., Ng, A. H. C. & Wheeler, A. R. A digital microfluidic electrochemical immunoassay. Lab Chip 14, 547–554 (2014).

    Article  Google Scholar 

  127. Witters, D., Knez, K., Ceyssens, F., Puers, R. & Lammertyn, J. Digital microfluidics-enabled single-molecule detection by printing and sealing single magnetic beads in femtoliter droplets. Lab Chip 13, 2047–2054 (2013).

    Article  Google Scholar 

  128. Shih, S. C. C., Barbulovic-Nad, I., Yang, X., Fobel, R. & Wheeler, A. R. Digital microfluidics with impedance sensing for integrated cell culture and analysis. Biosens. Bioelectron. 42, 314–320 (2013).

    Article  Google Scholar 

  129. Au, S. H., Chamberlain, M. D., Mahesh, S., Sefton, M. V. & Wheeler, A. R. Hepatic organoids for microfluidic drug screening. Lab Chip 14, 3290–3299 (2014).

    Article  Google Scholar 

  130. Zallocchi, M. et al. Piplartine attenuates aminoglycoside-induced TRPV1 activity and protects from hearing loss in mice. Sci. Transl. Med. 16, eadn2140 (2024).

    Article  Google Scholar 

  131. Tummino, T. A. et al. Drug-induced phospholipidosis confounds drug repurposing for SARS-CoV-2. Science 373, 541–547 (2021).

    Article  Google Scholar 

  132. Shinozawa, T. et al. High-fidelity drug-induced liver injury screen using human pluripotent stem cell-derived organoids. Gastroenterology 160, 831.e10–846.e10 (2021).

    Article  Google Scholar 

  133. Uijttewaal, E. C. H. CRISPR-StAR enables high-resolution genetic screening in complex in vivo models. Nat. Biotechnol. 43, 1848–1860 (2025).

    Article  Google Scholar 

  134. Song, S. et al. A cell-based multiplex immunoassay platform using fluorescent protein-barcoded reporter cell lines. Commun. Biol. 4, 1338 (2021).

    Article  Google Scholar 

  135. Liu, Y., Zhan, L., Qin, Z., Sackrison, J. & Bischof, J. C. Ultrasensitive and highly specific lateral flow assays for point-of-care diagnosis. ACS Nano 15, 3593–3611 (2021).

    Article  Google Scholar 

  136. Merola, F. et al. Tomographic flow cytometry by digital holography. Light Sci. Appl. 6, e16241 (2016).

    Article  Google Scholar 

  137. Au, S. H., Kumar, P. & Wheeler, A. R. A new angle on pluronic additives: advancing droplets and understanding in digital microfluidics. Langmuir 27, 8586–8594 (2011).

    Article  Google Scholar 

  138. Ng, A. H. C., Li, B. B., Chamberlain, M. D. & Wheeler, A. R. Digital microfluidic cell culture. Annu. Rev. Biomed. Eng. 17, 91–112 (2015).

    Article  Google Scholar 

  139. Chatterjee, D., Hetayothin, B., Wheeler, A. R., King, D. J. & Garrell, R. L. Droplet-based microfluidics with nonaqueous solvents and solutions. Lab Chip 6, 199–206 (2006).

    Article  Google Scholar 

  140. Choi, K., Ng, A. H. C., Fobel, R. & Wheeler, A. R. Digital microfluidics. Annu. Rev. Anal. Chem. 5, 413–440 (2012).

    Article  Google Scholar 

  141. Dong, C. et al. On the droplet velocity and electrode lifetime of digital microfluidics: voltage actuation techniques and comparison. Microfluid. Nanofluid. 18, 673–683 (2015).

    Article  Google Scholar 

  142. Leipert, J. & Tholey, A. Miniaturized sample preparation on a digital microfluidics device for sensitive bottom-up microproteomics of mammalian cells using magnetic beads and mass spectrometry-compatible surfactants. Lab Chip 19, 3490–3498 (2019).

    Article  Google Scholar 

  143. Ho, M. et al. Antifouling properties of pluronic and tetronic surfactants in digital microfluidics. ACS Appl. Mater. Interfaces 15, 6326–6337 (2023).

    Article  Google Scholar 

Download references

Acknowledgements

The research of the authors was supported by the China Academy of Engineering, Institute of Land Cooperation Consulting Project 2025-DFZD-39.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed substantially to discussions of the article content. H.M. and J.Y. researched data for the article, D.W. and S.J. wrote the first draft, and A.N., D.W., H.M. and J.Y. reviewed and/or edited the manuscript before submission.

Corresponding authors

Correspondence to Hanbin Ma, Jun Yu or Arokia Nathan.

Ethics declarations

Diversity statement

The authors acknowledge that papers authored by scholars from historically excluded groups are systematically under-cited. Every attempt has been made to reference relevant papers in a manner that is equitable in terms of racial, ethnic, gender and geographical representation.

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Electrical Engineering thanks Ulf Schlichtmann, who co-reviewed with Yushen Zhang; Jan G. Korvink; and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Alto: https://nicoyalife.com/products-overview/alto-digital-spr/

Cobas ePlex: https://diagnostics.roche.com/global/en/products/systems/cobas-eplex-system-sys-447.html

eProtein Discovery: https://www.nuclera.com/system/

VolTRAX V2: https://nanoporetech.com/document/voltrax-v2-protocol(2019)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, D., Jiang, S., Ma, H. et al. Active-matrix digital microfluidics for high-throughput, precise droplet handling. Nat Rev Electr Eng 3, 46–60 (2026). https://doi.org/10.1038/s44287-025-00230-1

Download citation

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s44287-025-00230-1

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing