Perovskite discovery goes automatic: New platform expedites material development for next-gen tech
A new research development, published in Nature Communications, from Queen Mary University of London paves the way for faster discovery of novel perovskite materials with desirable properties for applications in wireless communication and biosensors. Perovskites are a class of materials with a wide range of potential uses, but the vast number of possible chemical compositions makes traditional discovery methods slow and labor-intensive.
An international team of scientists has used machine learning to help them develop perovskite solar cells with near-record efficiency. In their paper published in the journal Science, the group describes how they used the machine-learning algorithm to help them find new hole-transporting materials to improve the efficiency of perovskite solar…
Researchers in Australia have harnessed AI to produce solar cells from the mineral perovskite in just a matter of weeks, bypassing years of human labor and human error to optimize the cells.
Tandem solar cells based on perovskite semiconductors convert sunlight to electricity more efficiently than conventional silicon solar cells. In order to make this technology ready for the market, further improvements with regard to stability and manufacturing processes are required.