{
  "abstract": "On-site quantification of airborne biological agents with low latency is critical for mitigating infection risks, informing ventilation strategies, and enabling rapid responses in high-risk environments. However, most existing aerosol detection approaches rely heavily on off-site laboratory analysis, which limits temporal resolution and hinders early intervention. Here, we report an automated interferential plasmonic system (AIPS) that integrates programmable aerosol collection, embedded microfluidic sample processing, sensitive and specific plasmonic sensing, and fully automated workflow control for in situ detection of bioaerosol. The AIPS combines a humidity-regulated condensation-growth module with an inertial liquid-impingement sampler to achieve high-efficiency capture of coarse and submicron biological particles, followed by an in situ lysis process to release intracellular nucleic acid components from microorganisms. An interferential nano plasmonic assay is subsequently employed to quantify the concentration of target biological agents with high specificity. The system achieves a practical detection limit in the collected liquid and completes the entire “air-sampling-to-result” label-free quantification process within 90 min (30 min sampling and 60 min processing and detection), along with a label-free alarm to target presence as fast as 1 min after completing the air sample. Integration of amplification methods can further enhance sensitivity and support more accurate detection across a wide range of scenarios. Real-world pilot measurements demonstrate that the AIPS enables high-spatiotemporal-resolution monitoring of indoor and outdoor bioaerosol dynamics and supports quantitative exposure assessment. This work establishes AIPS as a next-generation platform for continuous, autonomous surveillance of airborne biological threats and provides a promising solution for early warning of infection risks in healthcare, transportation, and other public environments.",
  "abstract_shown": true,
  "affiliations": [
    "Institute of Environmental Engineering, ETH Zürich, Zürich, 8093, Switzerland; Laboratory for Building Energy Materials and Components, Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, 8600, Switzerland",
    "Animal Nutrition, Institute of Agricultural Sciences, Department of Environmental Systems Science, ETH Zürich, Zürich, 8092, Switzerland",
    "US Army Primary Standards Laboratory, Redstone Arsenal, Alabama, USA; Corresponding author at: US Army Primary Standards Laboratory, Redstone Arsenal, Alabama, USA.",
    "Institute of Environmental Engineering, ETH Zürich, Zürich, 8093, Switzerland; Laboratory for Building Energy Materials and Components, Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, 8600, Switzerland; Corresponding author at: Institute of Environmental Engineering, ETH Zürich, Zürich, 8093, Switzerland."
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Min Gao"
    },
    {
      "affs": [
        0
      ],
      "name": "Zesen Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "Yile Tao"
    },
    {
      "affs": [
        0
      ],
      "name": "Xiangyu Chen"
    },
    {
      "affs": [
        1
      ],
      "name": "Kai Wang"
    },
    {
      "affs": [
        1
      ],
      "name": "Mutian Niu"
    },
    {
      "affs": [
        2
      ],
      "name": "Miles Owen"
    },
    {
      "affs": [
        3
      ],
      "name": "Jing Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/57388znp477j8.bib",
  "cited_by": 0,
  "doi": "10.1016/j.snr.2026.100527",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S2666053926000949",
  "id": "57388znp477j8",
  "issns": [
    "2666-0539"
  ],
  "landing_url": "https://doi.org/10.1016/j.snr.2026.100527",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "QA71-90"
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    [
      "openalex",
      "2204|Biosensors and Analytical Detection"
    ]
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  "openalex": "W7223050410",
  "pdf_url": "https://www.sciencedirect.com/science/article/pii/S2666053926000949/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/57388znp477j8.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:44:58Z",
      "native_id": "cb0ce799d6464887bbff44ac218275a2",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.snr.2026.100527"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "lcc:QA71-90",
      "subfield": "general"
    }
  ],
  "title": "AIPS: an automated interferential plasmonic system for on-site bioaerosol detection",
  "title_text": "AIPS: an automated interferential plasmonic system for on-site bioaerosol detection",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:44:58Z",
  "url": "https://research.draconitic.com/paper/57388znp477j8",
  "venue": "Sensors and Actuators Reports",
  "versions": []
}