2025-09-19 ジョンズ・ホプキンス大学
Web要約 の発言：
＜関連情報＞
- https://hub.jhu.edu/2025/09/19/chatgpt-materials-explorer/
- https://link.springer.com/article/10.1007/s40192-025-00410-9#change-history
ChatGPTマテリアルエクスプローラー：材料科学アプリケーション向けカスタムGPTアシスタントの設計と実装 ChatGPT Material Explorer: Design and Implementation of a Custom GPT Assistant for Materials Science Applications
Kamal Choudhary
Integrating Materials and Manufacturing Innovation Published:09 July 2025
DOI:https://doi.org/10.1007/s40192-025-00410-9
Abstract
Custom generative pre-trained transformers (GPTs) are transforming domain-specific problem-solving across scientific fields. However, materials science lacks a dedicated, accessible GPT-based assistant tailored to its unique challenges. To address this gap, I present ChatGPT Material Explorer 1.0 (CME), a custom GPT that integrates large language models with graph neural networks (GNN) models and other domain-specific APIs to enhance materials design workflows. The assistant offers core functionalities such as: (1) intelligent exploration of molecular and materials databases, (2) GNN-driven prediction of materials properties, (3) efficiently searching arXiv for papers, and (4) interactive, conversational support for scientific analysis and writing. I evaluate its performance against general-purpose models such as OpenAI GPT-4o highlighting its superior ability to retrieve accurate data, reduce hallucination, and provide context-aware responses. By combining natural language understanding with real-time data access and physics-informed modeling, CME aims to democratize computational tools and accelerate decision-making in materials research. More details about CME are available at: https://github.com/AtomGPTLab/chatgpt_material_explorer to facilitate broader community adoption.
