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RESEARCH PAPER · Materials Genome Engineering Advances · 2024

Artificial intelligence enabled smart design and manufacturing of advanced materials: The endless Frontier in AI + era

William Yi Wang, Suyang Zhang, Gaonan Li, Jiaqi Lu, Yong Sheng Ren, Xinchao Wang, Xingyu Gao, Yanjing Su, Haifeng Song, Jinshan Li

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Artificial intelligence enabled smart design and manufacturing of advanced materials: The endless Frontier in AI + eraOriginalEffect of order–disorder transition on thermodynamic and electronic properties of σ and χ phases in W–Re alloy: the first-principles calculation10Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning16Knowledge-enabled data-driven smart design advanced high-entropy alloys with attractive dynamic mechanical properties7Large language models enabled intelligent microstructure optimization and defects classification of welded titanium alloys13NJmat 2.0: User Instructions of Data-Driven Machine Learning Interface for Materials Science6Advanced Morphological and Material Engineering for High‐Performance Interfacial Iontronic Pressure Sensors77Advances in high‐throughput experiments of polymer crystallization for developing polymer processing9Applications of natural language processing and large language models in materials discovery132Generative Artificial Intelligence-Enabled Facility Layout Design Paradigm16AI-Driven Decision Making in Innovation0Research on discharge performance prediction of magnesium anode materials assisted by graph neural networks3Coherent heat transport in graphene grain boundary superlattices2Role of Generative AI in AI-Based Digital Twins in Industry 5.0 and Evolution to Industry 6.015Chain disorder induced by the bonding polarity in the incommensurate structure of antimony0LLMs and NLP integration enables ion irradiation-induced swelling prediction in stainless steels2OPECM: A comprehensive dataset for organic polymer energy conversion materials enabling data-driven interpretative analysis0AUTOMATED LAYOUT DESIGN USING AI SYSTEMS0From large language models to AI agents in energy materials research: enabling discovery, design, and automation12The trade-off between wear and corrosion performance in WC/W2C reinforced laser powder bed fusion duplex stainless steel composites4Agentic AI in Cybersecurity Review of Autonomous Threat Detection and Adaptive Defense Mechanisms1Agentic Artificial Intelligence: Transforming the Future of Retail0AI and nanotechnology for advancing drug development0Large language model-enabled machine learning for high performance Nd–Fe–B permanent magnet design1Design and Implementation of a Smart Education Platform Using Artificial Intelligence and Big Data Technologies0A data-driven comparative study of thermomechanical properties in rare-earth zirconate and tantalate oxides for thermal barrier coatings4Influence of annealing and tempering on the wear and corrosion behavior of WC/W2C reinforced composites fabricated by laser powder bed fusion4СТРАТЕГИИ ПРИМЕНЕНИЯ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА ДЛЯ ПРОМЫШЛЕННЫХ ИННОВАЦИЙ: ВОЗМОЖНОСТИ ИСПОЛЬЗОВАНИЯ МЕЖДУНАРОДНОГО ОПЫТА В РОССИИ0Artificial Intelligence in Lightweight Composite Materials Design and Characterization1Artificial Intelligence and Machine Learning in Advanced Materials Science0Semantic Intelligence in Metallurgy: A Dual‐Stage Language Model Framework for Processing‐Aware Magnesium Alloy Design1Physically synthesized data for deep learning-based visual scratch inspection of aerospace alloys with complex geometries1Robotic Systems and LLM Algorithms for Transforming Manufacturing Into Smart Autonomous Ecosystem1Computer vision for efficient object detection and segmentation in molecular image analysis1Application of deep learning for predicting carbon segregation in large-diameter continuously cast steel billets0MatterMind: A User‐Friendly Material Design Platform Assisted by Large Language Model0Research on the Construction Path and Practice of the “Golden Curriculum System” for AI-Empowered Intelligent Manufacturing Professional Group Under the Background of “Double High Construction (2025-2029)”0Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel0An Intelligent Partition-and-Prediction Framework for Ultra-Low-Phosphorus High-Purity Iron: Improved Interpretability and Accuracy0Multifunctional polyimide composites for extreme environments: Molecules and material structure engineering, preparation, and formulation design strategies0Aerodynamic Design Optimization, AI Creation Systems Applications, Aerospace Engineering0Machine Learning‐Accelerated Screening of VCoRu Solid‐Solution Alloy as a Superior Catalyst for Efficient Hydrogen Evolution1The validation and verification of high-throughput equivalent ternary CALPHAD algorithm for thermodynamic properties of multicomponent Ti alloys0Physicochemical Insights into Laser-Induced Graphene via Data-Driven Materials-Genome Analysis of Natural and Synthetic Precursors0Machine learning for titanium alloy development: Composition design, process optimization, microstructure informatics, and performance prediction0ChatXRD: A LLM‐Driven Framework for Crystal System Classification and Lattice Parameters Prediction Based on XRD0IGA‐POLLM: An Improved Genetic Algorithm for Prompt Optimization in Materials Literature Information Extraction0LLM‐Powered AI Agents in Materials Science: From Autonomous Design to Autonomous Experimentation0Governing The Accelerator: The Case for National Collaboration in AI‐Enabled Materials Discovery0Large language models in materials science: mechanistic understanding, structure–property reasoning and future opportunities0Computational Insights into Catalytic Hydrogenation over M6O8-Node MOFs: From Active-Site Engineering to Data-Driven Catalyst Design0Bridging Chemically Distinct Coating Systems: Cross-System Transfer Learning Enables Discovery of Ultralow-Thermal-Conductivity Ferroelastic Tantalates0

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  2. Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning

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  3. Knowledge-enabled data-driven smart design advanced high-entropy alloys with attractive dynamic mechanical properties

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  4. Large language models enabled intelligent microstructure optimization and defects classification of welded titanium alloys

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  5. NJmat 2.0: User Instructions of Data-Driven Machine Learning Interface for Materials Science

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  6. Advanced Morphological and Material Engineering for High‐Performance Interfacial Iontronic Pressure Sensors

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  7. Advances in high‐throughput experiments of polymer crystallization for developing polymer processing

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  8. Applications of natural language processing and large language models in materials discovery

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  9. Generative Artificial Intelligence-Enabled Facility Layout Design Paradigm

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  10. AI-Driven Decision Making in Innovation

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  11. Research on discharge performance prediction of magnesium anode materials assisted by graph neural networks

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  12. Coherent heat transport in graphene grain boundary superlattices

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  14. Chain disorder induced by the bonding polarity in the incommensurate structure of antimony

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  15. LLMs and NLP integration enables ion irradiation-induced swelling prediction in stainless steels

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  16. OPECM: A comprehensive dataset for organic polymer energy conversion materials enabling data-driven interpretative analysis

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  17. AUTOMATED LAYOUT DESIGN USING AI SYSTEMS

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  18. From large language models to AI agents in energy materials research: enabling discovery, design, and automation

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  19. The trade-off between wear and corrosion performance in WC/W2C reinforced laser powder bed fusion duplex stainless steel composites

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  20. Agentic AI in Cybersecurity Review of Autonomous Threat Detection and Adaptive Defense Mechanisms

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  25. A data-driven comparative study of thermomechanical properties in rare-earth zirconate and tantalate oxides for thermal barrier coatings

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  27. СТРАТЕГИИ ПРИМЕНЕНИЯ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА ДЛЯ ПРОМЫШЛЕННЫХ ИННОВАЦИЙ: ВОЗМОЖНОСТИ ИСПОЛЬЗОВАНИЯ МЕЖДУНАРОДНОГО ОПЫТА В РОССИИ

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  31. Physically synthesized data for deep learning-based visual scratch inspection of aerospace alloys with complex geometries

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  37. Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

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  42. The validation and verification of high-throughput equivalent ternary CALPHAD algorithm for thermodynamic properties of multicomponent Ti alloys

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  43. Physicochemical Insights into Laser-Induced Graphene via Data-Driven Materials-Genome Analysis of Natural and Synthetic Precursors

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  44. Machine learning for titanium alloy development: Composition design, process optimization, microstructure informatics, and performance prediction

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  45. ChatXRD: A LLM‐Driven Framework for Crystal System Classification and Lattice Parameters Prediction Based on XRD

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  46. IGA‐POLLM: An Improved Genetic Algorithm for Prompt Optimization in Materials Literature Information Extraction

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  48. Governing The Accelerator: The Case for National Collaboration in AI‐Enabled Materials Discovery

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  49. Large language models in materials science: mechanistic understanding, structure–property reasoning and future opportunities

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  50. Computational Insights into Catalytic Hydrogenation over M6O8-Node MOFs: From Active-Site Engineering to Data-Driven Catalyst Design

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