Papers

28

Total Citations

1,390

H-Index

18

About

Luzhuo Chen is a prominent materials scientist and engineer whose research focuses on the design and development of advanced actuator systems, smart materials, and bioinspired robotics. His work centers on harnessing the extraordinary properties of carbon-based nanomaterials — particularly carbon nanotubes and graphene — to create next-generation responsive actuators capable of mimicking biological motion and intelligence. Chen's most significant contributions lie in pioneering multi-responsive actuator systems that respond to diverse stimuli including light, humidity, electricity, and pressure. His landmark studies on graphene oxide composites and carbon nanotube-coated polymer bilayers — each accumulating over 125 citations — demonstrated unprecedented actuation performance that outpaced many competing carbon-based technologies. He has consistently pushed boundaries by integrating sensing and actuation into unified platforms, as illustrated by his graphene-based actuator with real-time sensing feedback (136 citations) and his pressure-perceptive actuators for tactile soft robotics. Beyond materials innovation, Chen has demonstrated a sophisticated design philosophy, drawing inspiration from biological systems — including electric fish and cobwebs — to engineer functional devices with energy-storage and multi-modal capabilities. With a body of work collectively exceeding 1,000 citations, Chen's research has meaningfully advanced the fields of soft robotics, artificial muscles, and intelligent flexible electronics.

Research Focus

Key Achievements

18
H-Index
28
Papers
1,390
Total Citations
50
Avg Citations/Paper
🏆 Most Cited Paper
Multi-responsive actuators based on a graphene oxide composite: intelligent robot and bioinspired applications
184 citations · 2017
📈 Most Prolific Year: 2016 (4 Papers)
🤝 Key Collaborators: 53
🏛 Institutions: Fujian Normal University, Tan Kah Kee Innovation Laboratory

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago