Yee‐Fun Lim
Papers
2
Total Citations
41
H-Index
2
About
Yee-Fun Lim is a rising leader in the integration of software engineering and autonomous materials discovery. Her research focuses on creating digital infrastructure for self-driving laboratories, with key contributions in workflow evolution, multi-objective optimization, and the accelerated discovery of photo-electrocatalytic materials. Lim’s most cited work, “An Object-Oriented Framework to Enable Workflow Evolution Across Materials Acceleration Platforms” (2022, 22 citations), provides a foundational software architecture that allows materials acceleration platforms to adapt and scale—a critical step toward truly autonomous, interoperable labs. Her 2023 paper on “Closed-Loop Multi-Objective Optimization for Cu–Sb–S Photo-Electrocatalytic Materials’ Discovery” (19 citations) demonstrates the power of this framework in action, using a closed-loop system to navigate the complex compositional and structural space of copper antimony sulfides, promising earth-abundant catalysts for solar-driven water splitting. By bridging object-oriented design with high-throughput experimentation, Lim is helping to shape the future of AI-driven materials science, enabling faster, more intelligent discovery of next-generation energy materials.
Research Focus
Key Achievements
Top Papers
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