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Autonomous Analysis of Thermoelectric Materials Big Data by Multi-Agentic AI and Construction of a Knowledge Base and Specialized AI — arXiv:2611.00627

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.00627
License (as archived): CC0-1.0
Archived: 2026-11-03T10:39:40.498Z
SHA-256 of the archived text: 07a483b8d1c8cd30cab1c40ce6f33cd0e9480f3ffc674f80778fec7d6f2585f0
Stable URL of this page: https://metraipolis.com/documento/dc_fb8ea3adf63d

How to cite

Autonomous Analysis of Thermoelectric Materials Big Data by Multi-Agentic AI and Construction of a Knowledge Base and Specialized AI — arXiv:2611.00627 — arXiv (en), https://arxiv.org/abs/2611.00627 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_fb8ea3adf63d (Metraipolis archive dc_fb8ea3adf63d, sha256 07a483b8d1c8cd30cab1c40ce6f33cd0e9480f3ffc674f80778fec7d6f2585f0)

BibTeX

@misc{dcfb8ea3adf63d,
  title = {Autonomous Analysis of Thermoelectric Materials Big Data by Multi-Agentic AI and Construction of a Knowledge Base and Specialized AI — arXiv:2611.00627},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.00627},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_fb8ea3adf63d; sha256 07a483b8d1c8cd30cab1c40ce6f33cd0e9480f3ffc674f80778fec7d6f2585f0},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.00627. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Extracting knowledge from large databases of experimental materials data requires repeated analyses and reusable records of their choices and results. We developed Multi-Agentic AI (MAA), a multi-agent system in which AI agents with distinct roles analyze experimental thermoelectric data under predefined instructions and quality checks, saving analysis records traceable to their sources. In four experiments varying theme and cycle counts, we measured what accumulated in these records. In the largest experiment (100 analyses across 10 themes and 10 cycles), concept co-occurrences were concentrated within themes, vocabulary was shared across themes and some relation descriptions were first detected in later cycles. A specialized AI that searches this experiment's knowledge bases and reads their analysis records answered materials questions with cited sources. Retrospective checks, including tracing an answer generated with a preliminary corpus back to the source data, exposed errors: traceability makes errors findable but not absent.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.MA, nuovi lavori del giorno).
Categorie arXiv: Artificial Intelligence (cs.AI) ; Materials Science (cond-mat.mtrl-sci); Multiagent Systems (cs.MA).
Pagina del lavoro: https://arxiv.org/abs/2611.00627 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-03T10:39:34.936Z dalla pagina https://arxiv.org/list/cs.MA/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).