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Robust metric for quantifying the importance of stochastic effects on nanoparticle growth
Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry.
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Number of Authors: 62018 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 8, article id 14160Article in journal (Refereed) Published
Abstract [en]

Comprehensive representation of nanoparticle dynamics is necessary for understanding nucleation and growth phenomena. This is critical in atmospheric physics, as airborne particles formed from vapors have significant but highly uncertain effects on climate. While the vapor-particle mass exchange driving particle growth can be described by a macroscopic, continuous substance for large enough particles, the growth dynamics of the smallest nanoparticles involve stochastic fluctuations in particle size due to discrete molecular collision and decay processes. To date, there have been no generalizable methods for quantifying the particle size regime where the discrete effects become negligible and condensation models can be applied. By discrete simulations of sub-10 nm particle populations, we demonstrate the importance of stochastic effects in the nanometer size range. We derive a novel, theory-based, simple and robust metric for identifying the exact sizes where these effects cannot be omitted for arbitrary molecular systems. The presented metric, based on examining the second- and first-order derivatives of the particle size distribution function, is directly applicable to experimental size distribution data. This tool enables quantifying the onset of condensational growth without prior information on the properties of the vapors and particles, thus allowing robust experimental resolving of nanoparticle formation physics.

Place, publisher, year, edition, pages
2018. Vol. 8, article id 14160
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Other Physics Topics Earth and Related Environmental Sciences
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URN: urn:nbn:se:su:diva-161203DOI: 10.1038/s41598-018-32610-zISI: 000445276000004PubMedID: 30242199OAI: oai:DiVA.org:su-161203DiVA, id: diva2:1258944
Available from: 2018-10-26 Created: 2018-10-26 Last updated: 2018-10-26Bibliographically approved

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Olenius, TinjaStolzenburg, DominikRiipinen, Ilona
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