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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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23 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Development and Implementation of a New AI-Based Tool to Support Fast Reactor Software Model Generation and Validation

This report summarizes FY26 work to develop Maggie, an artificial intelligence-based assistant designed to support software model generation and validation activities for fast reactor analysis codes. The project established a modular, code-agnostic software architecture that separates reusable agent capabilities from code-specific knowledge and tools, with initial implementation focused on the FRP-supported fast reactor safety analysis code SAS4A/SASSYS1 (SAS). A curated SAS-specific knowledge base was assembled from the code manual, training materials, historical analysis reports, and representative input files, and was integrated through retrieval-augmented generation to ground Maggie’s responses in authoritative sources. Maggie was deployed on the internal Argonne network, where it demonstrated practical user-facing capability as a chatbot for answering natural language questions about SAS and retrieving relevant technical information. Demonstration cases also showed that Maggie can generate useful snippets of SAS input for selected modeling tasks, while highlighting current limitations in reliability and consistency for more complex input generation tasks. Overall, the FY26 effort established the technical foundation for an AI-assisted capability intended to improve the efficiency, consistency, and accessibility of fast reactor software model development at Argonne and, with further improvements, to support eventual use by the broader fast reactor community, including industry users of FRP-supported analysis tools.

Thomas, Rachel [Argonne National Laboratory (ANL),↗
DOE OSTI2026

Building MCP-native hierarchical AI scientist ecosystems: a perspective on scaling multi-agent scientific discovery

Large language models (LLMs) are evolving from chatbots with limited tool-using capabilities to agentic AI systems that can perform deep research, assist in proposing hypotheses, help design experiments, automate data analysis, and draft scientific reports. However, there are currently two bottlenecks limiting LLMs' real-world impact on the broader scientific research community beyond academic demonstrations: lack of interoperability (repetitive manual tool-integration is required across scenarios) and the need for scalable coordination (unstructured communication and memory become brittle as the number of agents grows). In this Perspective, we argue that the next phase of agentic scientific discovery requires the development of an ecosystem of protocol-native agents and tools organized through hierarchies inspired by human society, beyond the current paradigm of a single monolithic “AI scientist”. We use Model Context Protocol (MCP) as a concrete example of an emerging interoperability layer for scientific tool and context exchange, and we propose three complementary pathways to increase the scaling capabilities of an MCP-native scientific ecosystem by addressing the composability issues: (1) MCP servers for high-value scientific tools maintained by domain experts, (2) automated transformation of existing code repositories into MCP services, and (3) autonomous invention and evolution of new agents and workflows. Finally, we provide a practical roadmap for scaling AI-driven scientific discovery by expanding tool supply and coordination in MCP-native scientific ecosystems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

AI in Science Communication

Generative AI has brought great innovations across multiple fields, offering great tools for enhanced communication and efficiency. This project focused on developing a custom AI chatbot using OpenAI's Chat GPT (GPT-4o) to support the Fermilab communications team. An analysis identified Chat GPT as the optimal choice, leading to the adoption of its team version and the implementation of a real-time JSON schema for website scanning. Four distinct personas were created to tailor responses to specific audiences, and Fermilab's published content was uploaded to ensure tone consistency. The training involved iterative prompt trials, resulting in a responsive and effective communication assistant. Initial evaluations indicate that the custom GPT shows promise.

Valle, Diego↗
DOE OSTI2025

Privacy-Aware RAG-Enabled LLMs for Collaborative AI in Organizations

Recent advancements in Large Language Models (LLMs) based on Transformer architectures have significantly improved capabilities in natural language processing and generation. However, deploying LLMs for inter-organizational communication poses challenges, in ensuring privacy and facilitating effective collaboration. This paper introduces a novel decentralized inference meta-agent chatbot that leverages privacy-aware Retrieval-Augmented Generation (RAG)-enabled LLMs for collaborative AI communication across organizations. Built on Microsoft’s Autogen, the platform enables LLMs to autonomously refine responses, enhancing accuracy and relevance. It incorporates advanced hallucination mitigation techniques using Uptrain and a privacy-focused RAG framework that employs synthetic document generation to protect sensitive information. Comprehensive evaluations demonstrate the platform’s effectiveness in maintaining contextual relevance and stringent privacy standards, effectively addressing critical challenges in LLM-enhanced collaborative AI communication. This work represents a significant step toward secure and efficient inter-organizational collaboration using advanced generative AI technologies.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

BESS Digital Assurance, Supply Chain Risk Management, and Emerging Regulation Session Two

The TADA BESS Supply Chain Workshops are designed to equip participants with the knowledge and tools necessary to address the evolving challenges at the intersection of battery energy storage systems (BESS), cybersecurity, and supply chain vulnerabilities. The workshops emphasize the application of Cyber-Informed Engineering (CIE) principles using INL’s procurement guide and the CIE-BAT tool. Attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their BESS projects. Additionally, the program fosters a collaborative network of practitioners and provides guidance on navigating emerging regulatory requirements, including FEOC rules under the OBBB framework, to assess and enhance organizational readiness. A comprehensive exploration of BESS cybersecurity supply chain risks, systematic vendor risk assessment through the BESS Procurement Guide, and practical application of the INL SCRM Chatbot for enhanced supply chain resilience. This is Session 2 of 3. (Full Version)

25 - ENERGY STORAGE↗