# Has materials modeling made any specific contribution to the success of perovskite solar cells, or has it only been experimental?

I was wondering if all the recent success of perovskite solar cells was accomplished purely experimentally or if there was some materials modeling aspect in it.

• – Tyberius Apr 29 '20 at 3:49
• Experimental tag can possibly stay: This is certainly a question that belongs on our site (since it's literally about materials modeling) but it also has to do with experimental materials science. Many experimental groups do maybe 60% experiments and 40% calculations (nowadays the other way around due to COVID lockdown) so they're welcome on this site, and would find it useful to be able to track this tag. If in 2 years there's only 3 questions with this tag, then maybe we can remove it :) – Nike Dattani Jun 26 '20 at 22:08

If you are looking for theoretical prediction of candidate perovskite solar cell materials; I have come across several papers that couple high-throughput density functional theory calculations along with machine learning for new material prediction. I haven't seen any solar cell compound discovery theoretical work that eventually validated their predictions through experiments though. However, this is not a result of an extensive search, so concluding "materials modelling has not contributed to solar cell materials discovery" is not right.

• Lu, S., Zhou, Q., Ma, L., Guo, Y., Wang, J., Rapid Discovery of Ferroelectric Photovoltaic Perovskites and Material Descriptors via Machine Learning. Small Methods 2019, 3, 1900360. https://doi.org/10.1002/smtd.201900360
• Im, J., Lee, S., Ko, T. et al. Identifying Pb-free perovskites for solar cells by machine learning. npj Comput Mater 5, 37 (2019). https://doi.org/10.1038/s41524-019-0177-0
• Jacobs, R., Luo, G., Morgan, D., Materials Discovery of Stable and Nontoxic Halide Perovskite Materials for High‐Efficiency Solar Cells. Adv. Funct. Mater. 2019, 29, 1804354. https://doi.org/10.1002/adfm.201804354
• Choudhary et al. Accelerated Discovery of Efficient Solar Cell Materials Using Quantum and Machine-Learning Methods Chem. Mater. 2019, 31, 15, 5900–5908 Publication Date:July 17, 2019 https://doi.org/10.1021/acs.chemmater.9b02166

I did find machine learning ferroelectric perovskite modelling paper that validated predictions through experiments.

• Interesting references, but your comment "I haven't seen any solar cell compound discovery theoretical work that eventually validated their predictions through experiments though" indicates that the search is still on!!! – Nike Dattani Jun 13 '20 at 17:35
• That's right. But please do note that I wrote this answer to present some of the interesting papers I had seen on this topic. This is not a result of an extensive search and therefore it's not right to conclude "there's no theoretical contribution for solar cell material synthesis". – Achintha Ihalage Jun 13 '20 at 18:44
• It might be helpful if you could include "This is not a result of an extensive search" in your answer, so that this is made clear. – Nike Dattani Jun 13 '20 at 18:50

To add to the previous answer: the new lead-free halide double perovskite $$\ce{Cs_2InAgCl_6}$$ was discovered by first-principles and then synthesized:

I'm sure there are other such examples. In addition ab-initio calculations made many predictions on specific materials properties of existing perovskites before they were measured (more common than discovering new ones).