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Computational Intelligence (CI) in the Sustainable Manufacturing of Emerging Materials for Energy Storage and Environmental Applications
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Author(s): Vijayalaxmi Vishwanath Sonkamble (Indian Institute of Technology, Bombay, India)and Vinod Govind Gawai (Tata Motors Pvt. Ltd., India)
Copyright: 2025
Pages: 28
Source title:
Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials
Source Author(s)/Editor(s): Kamalakanta Muduli (Papua New Guinea University of Technology, Papua New Guinea), Bikash Ranjan Moharana (Papua New Guinea University of Technology, Papua New Guinea), Steve Korakan Ales (Papua New Guinea University of Technology, Papua New Guinea)and Dillip Kumar Biswal (Aryan Institute of Engineering and Technology, Bhubaneswar, India)
DOI: 10.4018/979-8-3693-7974-5.ch007
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Abstract
The demand for sustainable energy storage has driven advancements in material science, where Computational Intelligence (CI) is emerging as a key tool. CI techniques like machine learning and neural networks optimize complex processes, enhancing material properties and manufacturing efficiency. In energy storage, CI accelerates the discovery of materials for advanced batteries, supercapacitors, and hydrogen storage, improving energy density, cycle life, and safety. CI also aids environmental applications, such as water purification and carbon capture, by enhancing material performance. Despite challenges like data availability and computational resources, CI's integration into manufacturing promises a more sustainable future.
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