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 ...

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 ...

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 ...

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 ...

Through its Powering Livelihoods programme, Delhi-based think tank CEEW focuses on decentralised renewable solutions that ...