Artificial Intelligence for Energy Conversion
Tapasi Ghosh, Bhargavi Koneru, Prasun Banerjee
Many aspects of modern life are dependent on energy of various forms, which has already created strain on natural energy reserves and affected our environment adversely. Scientists and researchers are searching for alternative sources of energy that are sustainable, environment friendly, and renewable. However, any developmental work to invent a material or technique as a new source of energy involves a lengthy and complex experimental process to produce in scale. The last decade has seen remarkable progress in the field of Artificial Intelligence (AI) due to advancements of many new computer hardware, software’s, algorithms, technologies, and availability of a large amount of raw input data. We have started harnessing the power of AI to facilitate the process of discovering new materials as alternative energy sources and exploring the different advanced methodologies over the traditional approaches to utilize natural and eco-friendly sources for energy conversion. This book chapter will highlight some of the advancements in Machine Learning and Deep Learning techniques to explore new material resources and methodologies for energy conversion.
Keywords
AI, ML, ANN, Energy Conversion, Catalysts, Microbial Fuel Cell
Published online , 16 pages
Citation: Tapasi Ghosh, Bhargavi Koneru, Prasun Banerjee, Artificial Intelligence for Energy Conversion, Materials Research Foundations, Vol. 147, pp 123-138, 2023
DOI: https://doi.org/10.21741/9781644902530-6
Part of the book on Application of Artificial Intelligence in New Materials Discovery
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