TY - GEN
T1 - Optoelectronic Manipulation Platform for Parallel and Sequential Droplet Processing
AU - Li, Zonghao
AU - Zhang, Shuhao
AU - Guo, Zongliang
AU - Chen, Kangfu
AU - Xie, Huikai
AU - Fu, Rongxin
AU - Zhang, Shuailong
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - Optoelectronic manipulation platforms have emerged as a transformative technology for droplet microfluidics, offering the unique capability to actuate droplets on unstructured surfaces via dynamic light patterns. However, realizing its full potential for high-throughput applications has been hindered by the challenges of orchestrating collision-free motion for massive droplet swarms and the lack of intelligent, real-time feedback. In this work, we report an integrated platform, OptoBot @ 500, that overcomes these limitations by synergizing optoelectrowetting (OEW) with advanced computer vision and path planning. The system utilizes a deep learning-based YOLO model for high-precision single-cell identification and the Window Hierarchical Cooperative Algorithm for robust multi-agent navigation. This paradigm establishes a scalable solution for next-generation single-cell analysis, combinatorial chemistry, and synthetic biology.
AB - Optoelectronic manipulation platforms have emerged as a transformative technology for droplet microfluidics, offering the unique capability to actuate droplets on unstructured surfaces via dynamic light patterns. However, realizing its full potential for high-throughput applications has been hindered by the challenges of orchestrating collision-free motion for massive droplet swarms and the lack of intelligent, real-time feedback. In this work, we report an integrated platform, OptoBot @ 500, that overcomes these limitations by synergizing optoelectrowetting (OEW) with advanced computer vision and path planning. The system utilizes a deep learning-based YOLO model for high-precision single-cell identification and the Window Hierarchical Cooperative Algorithm for robust multi-agent navigation. This paradigm establishes a scalable solution for next-generation single-cell analysis, combinatorial chemistry, and synthetic biology.
KW - Deep Learning
KW - Droplet Manipulation
KW - Optoelectrowetting
KW - Path Planning
UR - https://www.scopus.com/pages/publications/105041719104
U2 - 10.1109/MEMS64181.2026.11419256
DO - 10.1109/MEMS64181.2026.11419256
M3 - Conference contribution
AN - SCOPUS:105041719104
T3 - Proceedings of the IEEE International Conference on Micro Electro Mechanical Systems (MEMS)
SP - 318
EP - 321
BT - 2026 IEEE 39th International Conference on Micro Electro Mechanical Systems, MEMS 2026
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2026
Y2 - 25 January 2026 through 29 January 2026
ER -