ChatGPT boosts efficiency of perovskite solar cells
- Revolutionizing solar cell design with ChatGPT: Nankai University and Linköping University discover PAA's potential for efficiency boost, showcasing the power of AI in material science.
Researchers from Nankai University in China and Linköping University in Sweden utilized ChatGPT to design a more efficient perovskite solar cell. By inputting requests into the large language model, the team identified polyallylamine (PAA) as a potential material for surface passivation in the cells. They manually verified the plausibility of the suggested materials and conducted real-world experiments to test their hypotheses.
The team fabricated 125 devices with a structure based on a standard p-i-n architecture and applied a thin layer of PAA onto the perovskite film before the deposition of the electron transport layer. The experiments showed an average increase in device performance by around 2 percent units, with a top performance of 22.75%, highlighting the potential of human-AI collaboration in material science research.
How did researchers improve perovskite solar cells using ChatGPT and PAA?
- Researchers utilized ChatGPT to identify polyallylamine (PAA) as a potential material for surface passivation in perovskite solar cells
- The team manually verified the plausibility of the suggested material and conducted real-world experiments to test their hypotheses
- They fabricated 125 devices with a structure based on a standard p-i-n architecture and applied a thin layer of PAA onto the perovskite film before the deposition of the electron transport layer
- The experiments showed an average increase in device performance by around 2 percent units, with a top performance of 22.75%
- This study highlights the potential of human-AI collaboration in material science research and the improvement of perovskite solar cells.
