Moving Perovskite Advancements from the Lab to the Manufacturing Floor
Perovskite-silicon tandem solar cells have the potential to increase the efficiency of solar cells, ultimately helping combat climate change and powering the transition to a clean energy future. However, the development of efficient and stable perovskite layers has been an ongoing challenge. MIT, in collaboration with CubicPV, Verde Technologies, Princeton University, and UC San Diego, has received an $11.25 million award from the U.S. Department of Energy’s Solar Energy Technologies Office (SETO) to establish a research center named Accelerated Co-Design of Durable, Reproducible, and Efficient Perovskite Tandems (ADDEPT) to address this challenge. This new research center proposes to use a co-optimization framework guided by machine learning and automation to create perovskite-silicon tandem solar modules that are co-designed for both stability and performance, significantly accelerating the R&D process and transfer of these achievements into commercial environments.
Related Facts:
– Current methods of creating stable and efficient perovskite layers to create tandem solar cells require extensive rounds of design iteration and testing, which inhibits their development for commercial use.
– Perovskite-silicon tandem solar cells are made through stacked materials that can absorb more of the solar spectrum than a single material, ultimately increasing efficiency.
– The ADDEPT center brings together teams of researchers from academia and industry to create perovskite-silicon tandem solar modules with a simultaneous focus on stability, reproducibility, and efficiency, with the goal of improving R&D time and transferring their successes to the manufacturing floor.
– The grant will be administered through MIT’s Research Laboratory for Electronics (RLE).
Key Takeaway:
The ADDEPT center’s creation for stable perovskite-silicon tandem solar modules is a significant step in bringing advancements from the lab to the manufacturing floor. Its co-optimization framework guided by machine learning and automation will enable a faster transfer of successes to commercial environments. Furthermore, close collaboration between academia and industry will help co-design for stability and performance, leading to a more effective production of tandem solar modules.
Conclusion:
The establishment of the ADDEPT center marks the significant potential of using machine learning and automation to accelerate R&D in tandem solar modules. Additionally, this collaboration between academia and industry will aid in the creation of solar modules that co-design for both stability and performance, aiding in a faster transfer of successes from the lab to the manufacturing floor.
