Machine vision-based driving and feedback scheme for digital microfluidics system
A digital microfluidic system based on electrowetting-on-dielectric is a new technology for controlling microliter-sized droplets on a plane. By applying a voltage signal to an electrode, the droplets can be controlled to move, merge, and split. Due to device design, fabrication, and runtime uncerta...
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De Gruyter
2021
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oai:doaj.org-article:03c510ffdcd94684842b2a4f09a5acce2021-12-05T14:10:44ZMachine vision-based driving and feedback scheme for digital microfluidics system2391-542010.1515/chem-2021-0060https://doaj.org/article/03c510ffdcd94684842b2a4f09a5acce2021-06-01T00:00:00Zhttps://doi.org/10.1515/chem-2021-0060https://doaj.org/toc/2391-5420A digital microfluidic system based on electrowetting-on-dielectric is a new technology for controlling microliter-sized droplets on a plane. By applying a voltage signal to an electrode, the droplets can be controlled to move, merge, and split. Due to device design, fabrication, and runtime uncertainties, feedback control schemes are necessary to ensure the reliability and accuracy of a digital microfluidic system for practical application. The premise of feedback is to obtain accurate droplet position information. Therefore, there is a strong need to develop a digital microfluidics system integrated with driving, position, and feedback functions for different areas of study. In this article, we propose a driving and feedback scheme based on machine vision for the digital microfluidics system. A series of experiments including droplet motion, merging, status detection, and self-adaption are performed to evaluate the feasibility and the reliability of the proposed scheme. The experimental results show that the proposed scheme can accurately locate multiple droplets and improve the success rate of different applications. Furthermore, the proposed scheme provides an experimental platform for scientists who focused on the digital microfluidics system.Luo ZhijieHuang BangruiXu JiazhiWang LuHuang ZitaoCao LiangLiu ShuangyinDe Gruyterarticledigital microfluidics systemelectrowetting-on-dielectricmachine visionpositionfeedbackChemistryQD1-999ENOpen Chemistry, Vol 19, Iss 1, Pp 665-677 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
digital microfluidics system electrowetting-on-dielectric machine vision position feedback Chemistry QD1-999 |
| spellingShingle |
digital microfluidics system electrowetting-on-dielectric machine vision position feedback Chemistry QD1-999 Luo Zhijie Huang Bangrui Xu Jiazhi Wang Lu Huang Zitao Cao Liang Liu Shuangyin Machine vision-based driving and feedback scheme for digital microfluidics system |
| description |
A digital microfluidic system based on electrowetting-on-dielectric is a new technology for controlling microliter-sized droplets on a plane. By applying a voltage signal to an electrode, the droplets can be controlled to move, merge, and split. Due to device design, fabrication, and runtime uncertainties, feedback control schemes are necessary to ensure the reliability and accuracy of a digital microfluidic system for practical application. The premise of feedback is to obtain accurate droplet position information. Therefore, there is a strong need to develop a digital microfluidics system integrated with driving, position, and feedback functions for different areas of study. In this article, we propose a driving and feedback scheme based on machine vision for the digital microfluidics system. A series of experiments including droplet motion, merging, status detection, and self-adaption are performed to evaluate the feasibility and the reliability of the proposed scheme. The experimental results show that the proposed scheme can accurately locate multiple droplets and improve the success rate of different applications. Furthermore, the proposed scheme provides an experimental platform for scientists who focused on the digital microfluidics system. |
| format |
article |
| author |
Luo Zhijie Huang Bangrui Xu Jiazhi Wang Lu Huang Zitao Cao Liang Liu Shuangyin |
| author_facet |
Luo Zhijie Huang Bangrui Xu Jiazhi Wang Lu Huang Zitao Cao Liang Liu Shuangyin |
| author_sort |
Luo Zhijie |
| title |
Machine vision-based driving and feedback scheme for digital microfluidics system |
| title_short |
Machine vision-based driving and feedback scheme for digital microfluidics system |
| title_full |
Machine vision-based driving and feedback scheme for digital microfluidics system |
| title_fullStr |
Machine vision-based driving and feedback scheme for digital microfluidics system |
| title_full_unstemmed |
Machine vision-based driving and feedback scheme for digital microfluidics system |
| title_sort |
machine vision-based driving and feedback scheme for digital microfluidics system |
| publisher |
De Gruyter |
| publishDate |
2021 |
| url |
https://doaj.org/article/03c510ffdcd94684842b2a4f09a5acce |
| work_keys_str_mv |
AT luozhijie machinevisionbaseddrivingandfeedbackschemefordigitalmicrofluidicssystem AT huangbangrui machinevisionbaseddrivingandfeedbackschemefordigitalmicrofluidicssystem AT xujiazhi machinevisionbaseddrivingandfeedbackschemefordigitalmicrofluidicssystem AT wanglu machinevisionbaseddrivingandfeedbackschemefordigitalmicrofluidicssystem AT huangzitao machinevisionbaseddrivingandfeedbackschemefordigitalmicrofluidicssystem AT caoliang machinevisionbaseddrivingandfeedbackschemefordigitalmicrofluidicssystem AT liushuangyin machinevisionbaseddrivingandfeedbackschemefordigitalmicrofluidicssystem |
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