{
  "abstract": "In-line spectroscopy now carries the chemical plant’s quality decisions over shared industrial wireless links, yet the schedulers distributing those links optimize throughput, fairness or delay and are blind to chemistry: an MIR quantification stream survives compression, while a runaway precursor confined to a narrow wavenumber window disappears with it. We present ChemRAN, a chemistry-aware orchestration framework for wireless process analytical technology networks. ChemQoI predicts how an allocation changes a stream’s analytical error, detection sensitivity and measurement-failure probability, and converts them into an expected chemical risk reduction using a sparse spectral sketch and a process cost matrix. SCARF allocates each window by marginal risk reduction under a hard safety floor for hazard streams, and RECAP couples allocation with offloading through a shared adaptation tensor and asynchronous updates conditioned on chemistry descriptors. On the Tennessee Eastman process, Buchwald–Hartwig and Suzuki–Miyaura screens and in-line MIR soft sensing, ChemRAN attains 0.9755 F1, 0.966 yield 𝑅2 and 1.08 g L−1 𝜅-casein RMSECV, cuts the risk-weighted chemical loss by 19% and the hazard miss rate from 2.31% to 0.88%, and retains over 90% of its performance on unseen plants and campaigns.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "Zeyu Pan",
      "orcid": "0009-0005-8820-866X"
    },
    {
      "name": "Yating Qin"
    },
    {
      "name": "Yihang Wu"
    },
    {
      "name": "Chenyi Zhang"
    },
    {
      "name": "Zixuan Peng Zhongnan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6hpzzsnkncfd5.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15010836/v1",
  "fulltext_url": null,
  "id": "6hpzzsnkncfd5",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010836/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",
      "1602|Spectroscopy and Chemometric Analyses"
    ]
  ],
  "openalex": "W7223178909",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010836/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-22",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/6hpzzsnkncfd5.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:24Z",
      "native_id": "10.26434/chemrxiv.15010836",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010836/v1"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "openalex:1602|Spectroscopy and Chemometric Analyses",
      "subfield": "analytical"
    }
  ],
  "title": "Risk-Priced Radio Resources for In-Line Spectroscopy and Reaction Monitoring in Chemical Plants",
  "title_text": "Risk-Priced Radio Resources for In-Line Spectroscopy and Reaction Monitoring in Chemical Plants",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:24Z",
  "url": "https://research.draconitic.com/paper/6hpzzsnkncfd5",
  "venue": "ChemRxiv",
  "versions": []
}