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 ...

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 ...

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 ...

The number of solar field construction projects is expected to rise dramatically as McKinsey projects United States solar capacity to explode from 73 gigawatts in 2021 to 617 gigawatts in 2032.

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 ...

Researchers from the Swiss Federal Institute of Technology Lausanne discovered perovskites with the perfect band gap for solar applications. By inculcating a machine-learning program, an advanced ...

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 ...