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Title: Accelerated Aging and Mechanical Loading: Study Protocol’s for Photovoltaic Lifetime Degradation Research
Keywords: FAIR Data, Photovoltaics, Software, Data Analytics, Computational Workflows
Abstract: The field of photovoltaics and PV's application in reliable energy production systems have advanced rapidly since the solar cells’ inception in the mid 1950s. The last two decades have seen an exponential growth in the adoption of PV. The rate at which new systems are coming online along with rapid developments in PV technology reveal the need for equivalent advances in the ways which we collect, monitor, and analyze our data. Traditional methods of experimentation and previous study protocols are being refined into statistically informed processes that enable researchers to accelerate the rate of learning by leveraging semantic reasoning and artificial intelligence. These new methods of study integrate the rapid developments by tech giants such as Google, providing an equal level of impact within the fields of material data science and engineering. These methods along with a data enabled workforce are revolutionizing the way science is performed while providing new heights from which to develop tomorrow's technology and solve the world's most pressing energy needs. This work demonstrates some of the modern tools and novel techniques used in solar energy research, along with the software systems developed to meet the needs of researchers today.