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RESEARCH PAPER · Acta Materialia · 2024

Steel design based on a large language model

Shaohan Tian, Xue Feng Jiang, Weiren Wang, Zhihua Jing, Chi Zhang, Cheng Zhang, Turab Lookman, Yanjing Su

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Steel design based on a large language modelOriginalAI4Materials: Transforming the landscape of materials science and enigneering25Knowledge-guided large language model for material science16Applications of natural language processing and large language models in materials discovery132High-throughput design strategy for creep-resistance steel using machine learning and optimization algorithm0Interpretable Machine Learning Applications: A Promising Prospect of AI for Materials68Building an end-to-end battery recipe knowledge base via transformer-based text mining10Application of Large Language Models in the AECO Industry: Core Technologies, Application Scenarios, and Research Challenges12Key technologies and applications of large language models for materials science3Closed-loop inverse design of high entropy alloys using symbolic regression-oriented optimization24Research advances and new insights into multi-source solid waste-derived ceramic foams36Multi-objective optimization of corrosion resistance, strength, ductility properties of weathering steel utilizing interpretable attention-based deep learning model6Research on the optimization of seamless steel pipe cooling process based on large language models1Development of Microstructural Evolution Models for Hot Rolling Integrating Advanced Numerical Tools0LLMs and NLP integration enables ion irradiation-induced swelling prediction in stainless steels2Advancing materials discovery through artificial intelligence68Large Language Model-based defect detection in context of industry 5.00Physically interpretable flow behavior prediction of 42CrMo steel via CA-simulation-informed multimodal deep learning7AI‐Driven Decoding of Material Dynamics: From Machine Learning Potentials and Interpretability to Generative Prediction18Large Language Models (LLMs) for Materials Design14An LLM-Assisted Multimodal Materials-Informatics Pipeline for Predicting Remanence and Intrinsic Coercivity in Sintered Nd–Fe–B Magnets0Development and Innovative Applications of Data and AI Models in Materials Science0Large language model-enabled machine learning for high performance Nd–Fe–B permanent magnet design1Preparation, Characterization, and Application of Additive Manufacturing Superalloy Data0Materials Informatics: Emergence to Autonomous Discovery in the Age of AI15A general LLM-powered text mining framework: Applied to extract high entropy alloys4Facilitating creep-resistant Al alloy design through a physics-aware integrated machine learning pipeline1Accelerating materials discovery via AI-Agent integration of large language models and simulation tools2Progress and opportunities for AI in additively manufactured NiTi-based shape memory alloys2Deep learning-driven innovation in metallic materials: A comprehensive review on microstructure analysis, property prediction, and inverse design14Alloy design paradigms in additive manufacturing: a new era of material innovation4Comprehensive quality assessment of resistance spot welding: A deep learning and large language models-based approach for process and performance evaluation2Ultra-fast design and application of non-heat-treatable integrated die casting aluminum alloys1DressingGraphRAG: A domain-specific research assistant integrating GraphRAG and LLMs for wound dressing research1Semantic Intelligence in Metallurgy: A Dual‐Stage Language Model Framework for Processing‐Aware Magnesium Alloy Design1Data-driven design of Nb-W refractory alloys using Transformer-based stress-strain modeling1Machine learning applications in metallic materials: Recent advances and future perspectives8Feature screening and sample synthesis for enhancing generalization predictive performance on imbalanced small data: amorphous alloy design0Simulon: An AI ‐Assisted, PyTorch ‐Native Framework of Molecular Dynamics and Modeling0LLMs in industrial domains: A systematic review of adaptation techniques and applications from the product lifecycle perspective17Semantic Embeddings of Chemical Elements for Enhanced Materials Inference and Discovery4Challenges and opportunities in machine learning for metal additive manufacturing: data scarcity and interpretability4Transforming the modelling of nuclear structural materials: A critical review of machine learning approaches0A survey of agentic materials science and engineering: where are we and where are we going?0Intelligent Material Framework for Data Mining and Performance Prediction of Invar Alloy1LightAlloy-Bench: Benchmarking reasoning abilities of large language models in light alloys1Intelligent visualization-driven materials design via two-dimensional symbolic feature generation0A large language model-based framework for fatigue life prediction of steels across spatiotemporal scales0Dialectical systems framework for LLM applications in intelligent construction and operation0Transformative power of AI-driven knowledge extraction in materials science: From fragmented pipelines to unified understanding0High-performance Fe-based superalloys designed via large language models and knowledge graphs0LLM-driven hybrid truss-lattice design via structural gene recombination0TriboBERT: A pre-training language model tailored for tribology0Knowledge-guided descriptors for multi-property prediction and candidate screening of superalloys0LLM‐Powered AI Agents in Materials Science: From Autonomous Design to Autonomous Experimentation0Knowledge‐Constrained Multi‐Objective Reinforcement Learning for Simultaneous Optimization of Printability and Mechanical Properties in Additively Manufactured Superalloys0Large language models in materials science: mechanistic understanding, structure–property reasoning and future opportunities0AI-assisted mining and application of wheel-rail tribological information from literature: A case study on wear0

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