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strategic integration of ai in materials science for enhanced performance - IIPSeries - Conferences & Edited Books
Publication Type: Edited Book

STRATEGIC INTEGRATION OF AI IN MATERIALS SCIENCE FOR ENHANCED PERFORMANCE

Book Name: Advancing Innovation in Smart Systems, Energy, Materials, and Manufacturing: Unleashing the Potential of IoT, AI, and Edge Intelligence
Authors: Aditya Singh, Deepanshi Agarwal, Ms. Monika Bhardwaj, Dr. Laxya
Keywords: Artificial Intelligence, Materials Science, Machine Learning, Deep Learning, Computational Modelling, Optimization Performance Enhancement.
Area/Stream: Academic / Text Book / Interdisciplinary Engineering
Published in: IIP Series
Volume: 3, Month:October,Year:2024
Page No.: 235-258
e-ISBN: 978-93-6252-115-6
DOI/Link: https://www.doi.org/10.58532/nbennuraich13

Abstract:

The integration of Artificial Intelligence (AI) in materials science has emerged as a transformative paradigm, revolutionizing the design, development, and optimization of materials with enhanced performance characteristics. This paper explores the strategic integration of AI techniques such as machine learning, deep learning, and computational modelling in materials science to accelerate the discovery process, optimize material properties, and drive innovation. By leveraging AI driven approaches, researchers can overcome traditional limitations in materials development, leading to breakthroughs in various fields ranging from electronics and energy storage to healthcare and beyond. This paper examines the current state of-the-art AI methodologies in materials science, discusses key challenges and opportunities, and proposes strategic frameworks for harnessing AI to unlock the full potential of advanced materials.

Cite this: Aditya Singh, Deepanshi Agarwal, Ms. Monika Bhardwaj, Dr. Laxya,"STRATEGIC INTEGRATION OF AI IN MATERIALS SCIENCE FOR ENHANCED PERFORMANCE", Advancing Innovation in Smart Systems, Energy, Materials, and Manufacturing: Unleashing the Potential of IoT, AI, and Edge Intelligence,IIP Series, Volume 3, October, 2024, Page no.235-258, e-ISBN: 978-93-6252-115-6, DOI/Link: https://www.doi.org/10.58532/nbennuraich13
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