1. Self-Driving Lab for Materials Development
Our Self-Driving Lab integrates advanced automation and machine learning to optimize electrolyte formulations. By using LabVIEW-based control systems and Python-driven ML loops, we aim to create a fully automated, high-speed closed-loop experimental platform. This research is crucial for speeding up the development of next-generation battery materials with precise control over composition and performance.
2. Large-Area Laser Advanced Manufacturing
We are developing a laser-based heat treatment process to enhance the manufacturing of solid-state batteries, aiming to overcome the limitations of traditional processes. By applying large-area laser technology to improve bonding density and production speed, this research will help scale up battery manufacturing while ensuring high reliability and efficiency in energy storage systems.
3. Extreme Temperature Battery Materials
Our work focuses on designing electrolytes and electrode materials that can operate effectively in extreme temperature conditions ranging from –40°C to 60°C. This research is vital for creating reliable energy storage solutions for environments with fluctuating or extreme temperatures, ensuring the consistent performance of batteries in diverse operational settings.
4. Multi-Energy Network with ESS Optimization
We explore the optimization of multi-energy networks, integrating solar, heat pumps, compressed air, and thermal storage systems, along with energy storage systems (ESS). This research focuses on improving the efficiency and reliability of energy management in real-world industrial settings, contributing to more sustainable and cost-effective energy solutions through simulation and modeling.
