Materials Engineering and Design

Applications of LLMs in materials science, crystal structure analysis, and materials synthesis for engineering applications

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Materials Engineering and Design

Research on Large Language Models in Materials Engineering and Design

Bridging Materials Science and Language

Bridging Materials Science and Language

AI-driven crystal design through multimodal learning

AI-Driven Materials Discovery

AI-Driven Materials Discovery

Automating synthesis with expert-level LLMs and large-scale datasets

AlloyGAN: Revolutionizing Materials Design

AlloyGAN: Revolutionizing Materials Design

How LLMs and GANs Are Transforming Engineering Materials Discovery

AI-Powered Materials Discovery

AI-Powered Materials Discovery

Leveraging LLMs for Chemical Search and Materials Design

ML-Powered Chemical Reaction Yield Prediction

ML-Powered Chemical Reaction Yield Prediction

Leveraging NLP Techniques for Better Chemical Process Outcomes

Unlocking Crystal Structures with AI

Unlocking Crystal Structures with AI

How LLMs can generate stable crystal structures without specialized training

Revolutionizing Materials Discovery with LLMs

Revolutionizing Materials Discovery with LLMs

A multimodal approach combining text and molecular data for better material property prediction

Overcoming Data Scarcity with LLMs

Overcoming Data Scarcity with LLMs

How Large Language Models are transforming materials engineering

AI-Powered Catalyst Discovery

AI-Powered Catalyst Discovery

Leveraging LLMs to accelerate catalyst design for clean hydrogen production

Foundation Models for Atomic Simulation

Foundation Models for Atomic Simulation

Scaling LLM approaches to revolutionize materials science

Harnessing LLMs for Materials Science Discovery

Harnessing LLMs for Materials Science Discovery

Using AI to uncover causal relationships in complex materials

OmniScience: Specialized AI for Scientific Discovery

OmniScience: Specialized AI for Scientific Discovery

A domain-specialized LLM advancing scientific reasoning across disciplines

CrossMatAgent: AI-Powered Metamaterial Innovation

CrossMatAgent: AI-Powered Metamaterial Innovation

Accelerating design through multi-agent LLM and generative AI integration

Enhancing Polymer Prediction with LLMs

Enhancing Polymer Prediction with LLMs

Combining language models with molecular structures for better materials science

Advancing Polymer Science with AI

Advancing Polymer Science with AI

A standardized database for polymer informatics and machine learning

MatAgent: AI-Powered Materials Engineering

MatAgent: AI-Powered Materials Engineering

Accelerating inorganic materials discovery with LLM-based reasoning

Reinforcement Learning Transforms Materials Design

Reinforcement Learning Transforms Materials Design

AI-powered discovery of stable, high-performance materials

Unlocking Materials Science with AI

Unlocking Materials Science with AI

Fine-tuning LLMs to extract critical materials relationships

AI-Powered Autonomous Microscopy

AI-Powered Autonomous Microscopy

Zero-shot AI for intelligent characterization of 2D materials

Key Takeaways

Summary of Research on Materials Engineering and Design