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Olenius T, Pichelstorfer L, Stolzenburg D, et al. Robust metric for quantifying the importance of stochastic effects on nanoparticle growth. Sci Rep. 2018;8(1):14160doi: 10.1038/s41598-018-32610-z.
Olenius, T., Pichelstorfer, L., Stolzenburg, D., Winkler, P. M., Lehtinen, K. E. J., & Riipinen, I. (2018). Robust metric for quantifying the importance of stochastic effects on nanoparticle growth. Scientific reports, 8(1), 14160. https://doi.org/10.1038/s41598-018-32610-z
Olenius, Tinja, et al. "Robust metric for quantifying the importance of stochastic effects on nanoparticle growth." Scientific reports vol. 8,1 (2018): 14160. doi: https://doi.org/10.1038/s41598-018-32610-z
Olenius T, Pichelstorfer L, Stolzenburg D, Winkler PM, Lehtinen KEJ, Riipinen I. Robust metric for quantifying the importance of stochastic effects on nanoparticle growth. Sci Rep. 2018 Sep 21;8(1):14160. doi: 10.1038/s41598-018-32610-z. PMID: 30242199; PMCID: PMC6154961.
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Sci Rep. 2018 Sep 21;8(1):14160. doi: 10.1038/s41598-018-32610-z.

Robust metric for quantifying the importance of stochastic effects on nanoparticle growth.

Scientific reports

Tinja Olenius, Lukas Pichelstorfer, Dominik Stolzenburg, Paul M Winkler, Kari E J Lehtinen, Ilona Riipinen

Affiliations

  1. Department of Environmental Science and Analytical Chemistry (ACES) and Bolin Centre for Climate Research, Stockholm University, SE-10691, Stockholm, Sweden. [email protected].
  2. Division of Physics and Biophysics, Department of Materials Research and Physics, University of Salzburg, A-5020, Salzburg, Austria.
  3. Faculty of Physics, University of Vienna, A-1090, Vienna, Austria.
  4. Department of Applied Physics, University of Eastern Finland and Finnish Meteorological Institute, POB 1627, FI-70211, Kuopio, Finland.
  5. Department of Environmental Science and Analytical Chemistry (ACES) and Bolin Centre for Climate Research, Stockholm University, SE-10691, Stockholm, Sweden.

PMID: 30242199 PMCID: PMC6154961 DOI: 10.1038/s41598-018-32610-z

Abstract

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.

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