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Meeting

2026 TMS Annual Meeting & Exhibition

Symposium

Artificial Intelligence Applications in Integrated Computational Materials Engineering (AI-ICME)

Presentation Title

H-13: Establishing a Large Language Model-based Systematic Alloy Design Strategy for Advanced Titanium Alloys

Author(s)

Kiwan Seo, Jin Woo Lee, Dong Woo Lee, Eun Soo Park

On-Site Speaker (Planned)

Kiwan Seo

Abstract Scope

As the demand for advanced titanium alloy designs with superior mechanical properties and biocompatibility grows, particularly in aerospace and biomedical fields, their inherent complexity poses significant design challenges. A systematic alloy design methodology that clarifies the interplay between processing parameters, microstructure, properties, and performance is thus essential. This research employs a LangChain-based Large Language Model algorithm, leveraging Human-In-The-Loop (HITL) and prompt engineering techniques for high-quality training data, ensuring accuracy and reliability. The algorithm is capable of visually representing hierarchical relationships using automatically generated Olson flow-block diagrams, significantly simplifying the process of understanding and optimizing complex alloy systems. This poster demonstrates the operational capabilities and effectiveness of our algorithm through detailed analysis of the generated Olson flow-block diagrams, especially highlighting its application in improving titanium alloy design efficiency and precision in practical applications.

Proceedings Inclusion?

Planned:

Keywords

ICME, Computational Materials Science & Engineering, Machine Learning

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