20.500.12556/DiRROS-25083 The selective detection of individual respiratory droplets in air Preventing the spread of airborne diseases in crowded indoor spaces is a global challenge. Infected individuals release virus-laden respiratory droplets (RDs) that can remain suspended in air and infectious for hours. Current monitoring methods cannot distinguish these droplets from airborne particulate matter (PM) in a real time. Here, we present a capacitive sensor that selectively detects and counts the individual droplets in indoor spaces, regardless the presence of PM. The device exploits the dielectric constant (ε) of water (78.2) to differentiate the droplets from solid PM particles (ε < 15). In a nonventilated conference-room study, RDs concentrations (40–330 RDs/L) were found to be correlated with human occupancy, but not with PM2.5 levels. The developed technology enables a real-time monitoring of number concentration of RDs, which represent a potential health risk when they carry viral or bacterial infections. The detected increase in RD concentration can serve as a trigger for data-driven ventilation and infection-prevention measures, providing an effective tool for mitigating the spread of respiratory diseases in hospitals, schools and other public spaces. respiratory droplets capacitive sensing indor air monitoring infection control kapljice izdihanega zraka zrak v zaprtih prostorih monitoring zraka nadzor okužb true false true American Chemical Society ZDA Angleški jezik Slovenski jezik © 2025 The Authors. Neznano 2026-01-09 10:16:27 2026-01-09 10:16:27 2026-01-10 03:48:48 0000-00-00 00:00:00 2025 0 0 Nasl. z nasl. zaslona; Opis vira z dne 8. 1. 2026; str. A-H iss. Vol. [in press] 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-06-12 2025-12-10 2025-12-16 53 2379-3694 10.1021/acssensors.5c02057 263994627 https://pubs.acs.org/doi/10.1021/acssensors.5c02057 1 e245749f-ed3b-11f0-94a7-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=37719 RAZ_Malok_Matjaz_2025.pdf RAZ_Malok_Matjaz_2025.pdf The data that support the findings of this study are available within the article, its Supporting Information file, and in Zenodo, https://doi.org/10.5281/zenodo.15489441. 1 A55BEE912838ABE102670AAC6E14F3D7 52335e5202a4faed65ee234933da4c819c962c6800adf292122eeff99159cd33 4165bc47-ed3c-11f0-94a7-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=37720 Institut Jožef Stefan 0 0 0