Data-driven prediction and optimization of emerging photovoltaic materials

Lei Zhang

Nanjing University oflnformation Science and Technology, Nanjing, 210044, China 

EXTENDED ABSTRACT: Emerging solar cell materials such as the lead halide perovskites offer interesting optoelectronic properties, yet suffering from several notorious issues with large virtual design space unsuitable for traditional design methods. In this talk, I will discuss the recent data-driven and machine learning studies for optimizing the halide perovskite materials and predicting new photovoltaic materials in our group. Various data-driven efforts for molecularly modifying the halide perovskite surfaces will be explained, including the high-throughput calculations and experiments, data mining, machine learning and symbolic regression methods [1-2]. In the second half of the talk, I will discuss the pros and cons of the natural language processing approaches to help inversely predicting new solar cell materials by automating the literature reading process [3]. Keywords: data-driven; natural language processing; machine learning; photovoltaic materials; perovskite

REFERENCES

[1] Zhang L and He M (2022) Unsupervised machine learning for solar cell materials from the literature J. Appl. Phys. 131 064902

[2] Zhang L, He M and Shao S (2020) Machine learning for halide perovskite materials Nano Energy 78 105380

[3] Tshitoyan V, Dagdelen J, Weston L, Dunn A, Rong Z, Kononova 0, Persson KA, Ceder G and Jain A (2019) Unsupervised word embeddings capture latent knowledge from materials science literature Nature 571 95—8

Brief Introduction of Speaker
Lei Zhang

Lei Zhang is a full-time professor at the Nanjing University of Information Science and Technology(NUIST). He obtained his PhD degree in Natural Science (Physics) from Cavendish Laboratory, University of Cambridge. Prior to this, he received his MSc in Composite Materials from Imperial College London, and BEng degree from Nanyang Technological University, Singapore. His research interests include materials informatics, photovoltaic materials and computational materials science. He has published > 100 scientific papers in SCI journals such as Nano Energy and Advanced Functional Materials. He has refereed hundreds of manuscripts for journals including Nat. Mater., Nat. Comm., J. Am. Chem. Soc., Adv. Mater., Matter, Adv. Energy Mater., Adv. Funct. Mater. and ACS Nano.