EventsThe 6th International Electronic Conference on Applied Sciences
Published
This submission belongs to the session S6. Energy, Environmental and Earth Science of the event The 6th International Electronic Conference on Applied Sciences
Published date
03 Dec, 2025
Academic Editor
author-avatarSimeone Chianese
Citation
Carlos Alves, Carlos Figueiredo, Jorge Sanjurjo-Sánchez, Ana Hernández, Assessing the application of artificial intelligence to the discovery of new mineral species, in Proceedings of The 6th International Electronic Conference on Applied Sciences, 9 December–11 December 2025, MDPI: Basel, Switzerland
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Assessing the application of artificial intelligence to the discovery of new mineral species

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1. Lab2PT&School of Sciences (Earth Sciences Department) , University of Minho, 4710-057 Braga, Portugal, Portugal
2. CERENA, Higher Technical Institute, University of Lisbon, 1649-004 Lisbon, Portugal, Portugal
3. University Institute of Geology, University of A Coruña, A Coruña, 15071, Spain, Spain
Abstract

Artificial intelligence is having a revolutionary effect on diverse areas of research, such as proteins, drugs, and materials (in July of 2025, Google Scholar listed around eighty publications with “artificial intelligence” and “materials” in the title and dated from the current year), including prediction of new entities.

The discovery of new mineral species constitutes a more demanding challenge as these predicted new mineral species must have natural occurrences resulting from geological processes. There are some initial results, however, that are not especially impressive, as we will discuss.
We assess diverse instances of available generative artificial intelligence tools (Aria, ChatGPT, Claude, Copilot, Gemini, Grok, M365 Copilot, Meta AI, Perplexity, and YouChat) in relation to their usefulness in predicting new, undiscovered mineral species along the following main lines: the current state of the art in relation to confirmed predictions, and proposed methodologies of artificial intelligence (including potential limitations) for this goal. Special attention will be given to the issue of natural occurrence. Accordingly, we promote an evaluation of artificial intelligence potential by artificial intelligence tools.

Results are widely variable, with some generic answers, some problems with references, and some promising suggestions regarding the conditions under which the new mineral species could be found.

Keywords
Artificial intelligence
Mineralogy
Earth Sciences
Poster
AlvesEtAl_PosterNMS.pdf
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