Zheyuan Cao

Mr. Zheyuan Cao


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 October 2025 in Micromachines
Verified
Journal Article
Open access
PDF file
YLYu si Lu
Yu si Lu
ZCZheyuan Cao
Zheyuan Cao
JLJinzhong Ling
Jinzhong Ling
YYYing Yuan
Ying Yuan
XLXin Liu
Xin Liu
JGJin-Kun Guo
Jin-Kun Guo
Liquid microlenses and their arrays (LMLAs) have emerged as a transformative platform in adaptive optics, offering superior reconfigurability, compactness, and fast response compared to conventional solid-state lenses. This review summarizes recent progress from an application-oriented perspective, focusing on actuation mechanisms, fabrication strategies, and functional performance. Among actuation mechanisms, electric-field-driven approaches are highlighted, including electrowetting for shape tuning and liquid crystal-based refractive-index tuning techniques. The former excels in tuning range and response speed, whereas the latter enables programmable wavefront control with lower optical aberrations but limited efficiency. Notably, double-emulsion configurations, with fast interfacial actuation and inherent structural stability, demonstrate great potential for highly integrated optical components. Fabrication methodologies—including semiconductor-derived processes, additive manufacturing, and dynamic molding—are evaluated, revealing trade-offs among scalability, structural complexity, and cost. Functionally, advances in focal length tuning, field-of-view expansion, depth-of-field extension, and aberration correction have been achieved, though strong coupling among these parameters still constrains system-level performance. Looking forward, innovations in functional materials, hybrid fabrication, and computational imaging are expected to mitigate these constraints. These developments will accelerate applications in microscopy, endoscopy, AR/VR displays, industrial inspection, and machine vision, while paving the way for intelligent photonic systems that integrate adaptive optics with machine learning for real-time control.