{
  "abstract": "Thermal optimization of 2D CFET inverters requires testing structural proposals against their electrical costs. We examine these research tasks using an AI agent workflow within a supplied electrothermal model. At 12 nm, Astra selects a redistributed source-interconnect geometry, while a coordinating agent proposes a substrate-directed heat-removal path. The combined design reduces peak temperature rise by 1.67 K at fixed metal volume and 20 μW. A subsequent metal-resistance sensitivity gives about 0.6-K inverter cooling alongside a 2% nFET on-current loss. Effective contact-length scaling further shows that lower temperature can accompany higher thermal resistance when current falls. Reproduction identifies agreeing implementations and retains a 104.95-K failure for diagnosis. These results show that an AI scientist workflow can propose thermal structures, test them under common constraints, and quantify their electrical cost.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.17123",
  "author_total": 4,
  "authors": [
    {
      "name": "Min-Hui Kim"
    },
    {
      "name": "Khushi Sharma"
    },
    {
      "name": "Sarah Zhang"
    },
    {
      "name": "Ye Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/45fmaz28ydjna.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.17123",
  "fulltext_url": null,
  "id": "45fmaz28ydjna",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.17123",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cond-mat.mtrl-sci"
    ],
    [
      "arxiv",
      "cs.AI"
    ],
    [
      "arxiv",
      "cs.AR"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2609.17123",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/45fmaz28ydjna.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:41Z",
      "native_id": "2609.17123",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.17123"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.mtrl-sci",
      "subfield": "condensed-matter"
    }
  ],
  "title": "AI for Science with GPT-6 Astra: Thermal Design and Electrothermal Analysis of 2D CFET",
  "title_text": "AI for Science with GPT-6 Astra: Thermal Design and Electrothermal Analysis of 2D CFET",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:41Z",
  "url": "https://research.draconitic.com/paper/45fmaz28ydjna",
  "venue": "arXiv",
  "versions": []
}