{
  "abstract": "Area-selective atomic layer deposition (AS-ALD) of SiO 2 -on-SiO 2 requires passivating adjacent SiN to isolate charge-trap nitride in 3D-NAND. We hypothesize that a smallmolecule electrophilic inhibitor chemoselectively acylates SiN surface amines (–NH 2 /–NH) over SiO 2 silanols (–OH), capping SiN against oxide nucleation. We build an in-silico AI co-scientist that (i) constructs amorphous a-SiO 2 /aSiN surfaces validated against diffraction and calibrates their reactive-site density to experiment, (ii) benchmarks its own methods, (iii) agentically screens inhibitors, and (iv) validates against a published positive control. The core selectivity is kinetic: reaction thermodynamics are near-degenerate, but acylation strongly favors the SiN amine over the SiO 2 silanol (gas-phase barrier difference ∼0.9 eV, a stepwise addition; xTB and DFT concur on the direction), reproducing textbook amine≫silanol chemose-lectivity. With a first-principles cap oxidative-initiation barrier (Ea≈0.68 eV ⇒ kdeg≈2.9× 10 −2 /cycle), a mechanistic multi-cycle model then demonstrates the target rather than assuming it: a re-passivation supercycle (redose every 3 cycles) reaches S = 0.91 at 10 nm. Run as a genuine closed loop, the agent autonomously proposes and screens candidates, inventing a novel lead that beats a naive electrophilicity-only baseline by 2.5 eV of selectivity. Our pipeline independently reproduces the published aminosilane oxide-preference (BDIPADS), anchoring the method. The pipeline is built entirely on open-source software.",
  "abstract_shown": true,
  "affiliations": [
    "Boston University"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Anand Sahu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2h9qqzd15xq3d.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15008158/v1",
  "fulltext_url": null,
  "id": "2h9qqzd15xq3d",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008158/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2208|Semiconductor materials and devices"
    ]
  ],
  "openalex": "W7204933162",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15008158/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-01",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/2h9qqzd15xq3d.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:17Z",
      "native_id": "10.26434/chemrxiv.15008158",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008158/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "source:chemrxiv",
      "subfield": "general"
    }
  ],
  "title": "An experiment-calibrated in-silico AI co-scientist discovers chemoselective silicon-nitride passivation for area-selective SiO2 atomic layer deposition",
  "title_text": "An experiment-calibrated in-silico AI co-scientist discovers chemoselective silicon-nitride passivation for area-selective SiO2 atomic layer deposition",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:17Z",
  "url": "https://research.draconitic.com/paper/2h9qqzd15xq3d",
  "venue": "ChemRxiv",
  "versions": []
}