| Abstract Scope |
In response to the increasing focus on sustainability, criticality, and resource availability in materials research, we present a robust data analytics platform offering detailed on global mineral commodities complemented by AI-assisted querying for raw materials. Utilizing data from the United States Geological Survey (USGS), our web application integrates the Herfindahl-Hirschman Index (HHI) to evaluate market concentration, highlighting potential risks and opportunities related to resource availability. Central to our platform is an AI assistant powered by a Retrieval-Augmented Generation (RAG) system, which utilizes a decade of USGS mineral commodity summaries. This system employs an open-source large language model (LLM) to facilitate user queries regarding reserves, production, market share, price, substitutes, recycling, and more. By retrieving pertinent documents and generating precise, comprehensive responses, this tool fills a significant gap in public resources, providing material scientists with an essential platform to evaluate sustainability, criticality, and market risks in the development of new materials. |