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Multi-Junction Discovery
About
- Our group, the Multi-junction Discovery Group, focuses on establishing a data-driven, high-throughput paradigm for next-generation photovoltaic research and development. We aim to overcome the Shockley-Queisser limit and accelerate the discovery of high-performance solar cells by moving beyond traditional trial-and-error approaches.
- Leveraging automated spin-coating, blade-coating, evaporation, and characterization platforms, we enable large‑scale, highly reproducible fabrication and measurement of novel photovoltaic devices, including organic photovoltaics (OPV), perovskite solar cells, and perovskite-based tandem devices. By integrating machine learning with high-throughput experimentation, we systematically investigate the complex relationships between processing conditions, material properties, and device performance, with the long-term goal of developing reliable, efficient, and industrially viable photovoltaic technologies.
Research Topics
- Autonomous Robotic Processing
Automated fabrication and high-throughput characterization of OPV, perovskite, and perovskite-based tandem solar cells - AI-Driven Material Discovery
Machine learning-guided material screening, multi-objective process optimization, and predictive performance modeling - Accelerated Aging & Lifetime Prediction
High-throughput indoor aging, stability assessment, and degradation modeling - Analysis & Device Physics
Building Process–Property–Performance relationships to bridge the gap between microscopic material properties and macroscopic device performance
Team members
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Last Modified: 13.04.2026