Abstract
Finding new solar cell materials among the vast elemental combinatorial space is an onerous task—one that should not be left to serendipity. Two recent papers, one published in npj Computational Materials and another in Journal of Physical Chemistry C, report advanced machine learning approaches to predict the band gap of new ABX3 perovskite materials. These methods represent continued progress toward accelerated materials discovery for photovoltaics.
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