Using Machine Learning to Find Reliable and Low-Cost Solar Cells

Researchers at the University of California, Davis College of Engineering are using machine learning to identify new materials for high-efficiency solar cells. Using high-throughput experiments and machine learning-based algorithms, they have found it is possible to forecast the materials’ dynamic behaviour with very high accuracy, without the need to perform as many experiments.
The work is featured on the cover of the April issue of ACS Energy Letters. 
Environmental News Network - Using Machine Learning to Find Reliable and Low-Cost Solar Cells
https://www.enn.com/articles/72378-using-machine-learning-to-find-reliable-and-low-cost-solar-cells
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Hybrid perovskites are organic-inorganic molecules that have received a lot of attention over the past 10 years for their potential use in renewable energy, said Marina Leite, associate professor of materials science and engineering at UC Davis and senior author on the paper. Some are comparable in efficiency to silicon for making solar cells, but they are cheaper to make and lighter, potentially allowing a wide range of applications, including light-emitting devices.

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Peter Karanga
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6 w
Using machine learning to find reliable and low-cost solar cells is an incredibly powerful tool that can help make solar energy more accessible to more people. Machine learning can be used to analyze large amounts of data and help identify cells with better performance and low costs. It can also help identify other related factors like production quality and reliability, which can lead to further cost savings. ML can thus help manufacturers, installers, and users to make better decisions going forward, while helping to move the solar industry forward.
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Mc Kaka
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6 w
This is credible!
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Hilda Wangui
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6 w
Kudos!to Davis college of engineering for the positive use of technology to find possible solutions on climate change
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Richard Smith
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6 w
#Applied 💚 #Transitoon
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Munene Mugambi
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6 w
Incorporation of technology in the fight against climate change saves us time and resources. A great move
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