An EPFL research project has developed a method based on machine learning to quickly and accurately search large databases, leading to the discovery of 14 new materials for solar cells. As we ...

The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...

Perovskites are a class of materials with great potential as solar cells. UC Davis materials scientists have used machine learning to explore the wide variety of perovskite formulas to find those best ...

A Swedish research group has found that using deep machine learning to identify solar energy systems in aerial images may not be so accurate in non-densely populated countries such as Sweden. They ...

Electrical power systems engineers need practical methods for predicting solar output power under varying environmental conditions of a single panel. By integrating an Arduino-based real-time data ...

A report from the Council of Energy, Environment and Water has analyzed nine of the ten countries with the largest rooftop solar markets to offer recommendations to other economies looking to ...