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Quantum Computing and Artificial Intelligence in Materials Discovery for Batteries
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Author(s): S. Harish (RL Jalappa Institute of Technology, India), R. V. V. Krishna (Aditya College of Engineering and Technology, Jawaharlal Nehru Technological University, Kakinada, India), V. Satyanarayana (Aditya College of Engineering and Technology, Jawaharlal Nehru Technological University, Kakinada, India)and Bala Chandra Pattanaik (Wallaga University, Ethiopia)
Copyright: 2024
Pages: 13
Source title:
Real-World Challenges in Quantum Electronics and Machine Computing
Source Author(s)/Editor(s): Christo Ananth (Samarkand State University, Uzbekistan), T. Ananth Kumar (IFET College of Engineering, India)and Osamah Ibrahim Khalaf (Al-Nahrain University, Iraq)
DOI: 10.4018/979-8-3693-4001-1.ch015
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Abstract
The synergistic integration of amount computing and artificial intelligence (AI) in the field of accoutrements discovery for batteries. Using the computational power of amount computing and the pattern recognition capabilities of AI, this study aims to accelerate the identification and design of new battery accoutrements with enhanced performance characteristics. By employing amount-calculating algorithms for accurate simulation of infinitesimal relations and electronic structures, coupled with AI-driven prophetic modelling ways, experimenters can efficiently explore vast accoutrement libraries and prognosticate material parcels applicable to battery performance. The chapter investigates colourful methodologies and case studies where an amount of computing and AI have been applied to expedite the discovery of high-capacity, stable, and environmentally sustainable battery accoutrements.
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