How can machine learning help determine the best times and ways to use solar energy? This is what a recent study published in Advances in Atmospheric Sciences hopes to address as a team of researchers ...

Researchers at Korea University have developed a machine learning model for predicting sheet resistance in phosphorus oxychloride (POCl3) doping processes in solar cell manufacturing. “Our study aims ...

Solar-collecting windows could make office buildings and skyscrapers more energy efficient, but harnessing solar power while retaining transparency is a tricky engineering problem. A new study from ...

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 ...

Japan's PXP Corp., a startup developing chalcopyrite and perovskite solar technologies, and Suntory Holdings, a Japanese brewing company, have started a one-year trial to investigate the performance ...

A recent study in Scientific Reports presented a graphene-based metamaterial as a solar absorber. The structure consisted of three layers: aluminum (Al) as the resonator, titanium nitride (TiN) as the ...