AI-Assisted Discovery of Novel Alloys for Extreme Environmental Conditions

  • Authors

    • Dr. Venkatesh Iyer Professor, SRM Institute of Science and Technology, India Author
    • Dr. Nandhini Ravi Assistant Professor, VIT University, India Author

    DOI:

    https://doi.org/10.67228/30716357/IJMRSE-2018PI4K7N

    Published 01-03-2018

  • Artificial Intelligence (Ai), Alloy Design, Extreme Environmental Conditions, Machine Learning (Ml), Materials Informatics, High-Throughput Screening, Generative Models, Active Learning, Data-Driven Discovery, Materials Science

    Issue

    Vol. 1 No. 1 (2018)

    Section

    Articles

    How to Cite

    AI-Assisted Discovery of Novel Alloys for Extreme Environmental Conditions. (2018). International Journal of Modern Research in Science & Engineering, 1(1), 01-13. https://doi.org/10.67228/30716357/IJMRSE-2018PI4K7N

  • Abstract

    The discovery of advanced alloys capable of withstanding extreme environmental conditions such as high temperatures, intense radiation, corrosive atmospheres, and mechanical stress is critical for applications in aerospace, nuclear energy, deep-sea exploration, and space missions. Traditional experimental and computational approaches to alloy design are often time-consuming and resource-intensive. Recent advances in artificial intelligence (AI) and machine learning (ML) offer powerful tools to accelerate the discovery process by enabling high-throughput screening, property prediction, and design optimization. This paper presents a comprehensive review and methodology for AI-assisted alloy discovery, focusing on the integration of data-driven models with physical principles, high-fidelity simulations, and experimental validation. We highlight successful case studies, discuss the challenges of data scarcity and model interpretability, and propose a framework for closed-loop design that incorporates generative models and active learning. This AI-driven approach represents a paradigm shift toward faster, more cost-effective discovery of next-generation materials for extreme environments.

  • References

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