20.500.12556/DiRROS-22555 Curvature-dependent adsorption of surfactants in water nanodroplets and nanobubbles Hypothesis. Surfactants, molecules that readily adsorb to liquid interfaces and reduce surface tension, are paramount to numerous natural and technological processes: from cloud formation and climate modeling to the stability and reactivity of nanodroplets and nanobubbles. While surfactant adsorption at planar interfaces has been well-studied, their behavior at curved interfaces remains much less understood. Since curvature modifies interfacial thermodynamic properties, we hypothesize that it will also affect surfactant adsorption. Simulations. To test this hypothesis, we perform molecular dynamics simulations of short-chain surfactants at water–vapor interfaces with varying curvature, examining droplets, bubbles, and planar interfaces. Findings. The outcomes reveal a systematic dependence of adsorption on curvature, which is enhanced at droplet interfaces and reduced at bubble interfaces, with the effect becoming more pronounced for surfactants with longer alkyl tails. We attribute this curvature-dependent behavior to two key mechanisms: Laplace pressure and curvature-dependent surface tension. The breakdown of these contributions allows us to obtain a quantitative understanding and to predict the influence of curvature on adsorption. droplets bubbles molecular dynamics simulation kapljice mehurji simulacija molekularne dinamike true false true Elsevier Nizozemska Angleški jezik Slovenski jezik © 2025 The Authors. Neznano 2025-06-04 08:55:20 2025-06-04 08:55:21 2025-10-24 03:51:33 0000-00-00 00:00:00 2025 0 0 Nasl. z nasl. zaslona; Opis vira z dne 3. 6. 2025; str. 1-9 Vol. 698, [article no.] 137928 Nov. 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2024-10-22 2025-05-18 2025-05-26 53 1095-7103 10.1016/j.jcis.2025.137928 238164483 https://www.sciencedirect.com/science/article/pii/S0021979725013190?via%3Dihub 1 e2dffca2-4110-11f0-963a-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=32608 RAZ_Staniscia_Fabio_2025.pdf RAZ_Staniscia_Fabio_2025.pdf Raziskovalni podatki so na voljo na spletni strani https://zenodo.org/records/15202310. 1 F0841E6049E3EC9B702719C39F95F996 cf309b837621bf6826b185161fd0bdf34115340899ac1ab77f0f67de877efb31 4b5aed1b-4111-11f0-963a-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=32609 Institut Jožef Stefan 0 0 0