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Engineers Apply Physics-Informed Machine Learning to Solar Cell Production Using Frontera

Engineers apply physics-informed machine learning to solar cell production

 E-Mail IMAGE: Despite the recent advances in the power conversion efficiency of organic solar cells, insights into the processing-driven thermo-mechanical stability of bulk heterojunction active layers are helping to advance the field.. view more  Credit: Department of Mechanical Engineering and Mechanics/Lehigh University Today, solar energy provides 2% of U.S. power. However, by 2050, renewables are predicted to be the most used energy source (surpassing petroleum and other liquids, natural gas, and coal) and solar will overtake wind as the leading source of renewable power. To reach that point, and to make solar power more affordable, solar technologies still require a number of breakthroughs. One is the ability to more efficiently transform photons of light from the Sun into useable energy.

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