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Title: NaCl nucleation from brine in seeded simulations: Sources of uncertainty in rate estimates

Abstract

This work reexamines seeded simulation results for NaCl nucleation from a supersaturated aqueous solution at 298.15 K and 1 bar pressure. We present a linear regression approach for analyzing seeded simulation data that provides both nucleation rates and uncertainty estimates. Our results show that rates obtained from seeded simulations rely critically on a precise driving force for the model system. The driving force vs. solute concentration curve need not exactly reproduce that of the real system, but it should accurately describe the thermodynamic properties of the model system. We also show that rate estimates depend strongly on the nucleus size metric. We show that the rate estimates systematically increase as more stringent local order parameters are used to count members of a cluster and provide tentative suggestions for appropriate clustering criteria.

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3]; ORCiD logo [4]; ORCiD logo [5];  [3]; ORCiD logo [3];  [6]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of Lincoln (United Kingdom)
  3. Universidad Complutense de Madrid (Spain)
  4. Univ. of Warwick (United Kingdom)
  5. Univ. of Guelph, ON (Canada)
  6. Univ. of California, Santa Barbara, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22), Materials Sciences & Engineering Division (SC- 22.2)
OSTI Identifier:
1506316
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 148; Journal Issue: 22; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Zimmermann, Nils. E. R., Vorselaars, Bart, Espinosa, Jorge R., Quigley, David, Smith, William R., Sanz, Eduardo, Vega, Carlos, and Peters, Baron. NaCl nucleation from brine in seeded simulations: Sources of uncertainty in rate estimates. United States: N. p., 2018. Web. doi:10.1063/1.5024009.
Zimmermann, Nils. E. R., Vorselaars, Bart, Espinosa, Jorge R., Quigley, David, Smith, William R., Sanz, Eduardo, Vega, Carlos, & Peters, Baron. NaCl nucleation from brine in seeded simulations: Sources of uncertainty in rate estimates. United States. doi:10.1063/1.5024009.
Zimmermann, Nils. E. R., Vorselaars, Bart, Espinosa, Jorge R., Quigley, David, Smith, William R., Sanz, Eduardo, Vega, Carlos, and Peters, Baron. Wed . "NaCl nucleation from brine in seeded simulations: Sources of uncertainty in rate estimates". United States. doi:10.1063/1.5024009. https://www.osti.gov/servlets/purl/1506316.
@article{osti_1506316,
title = {NaCl nucleation from brine in seeded simulations: Sources of uncertainty in rate estimates},
author = {Zimmermann, Nils. E. R. and Vorselaars, Bart and Espinosa, Jorge R. and Quigley, David and Smith, William R. and Sanz, Eduardo and Vega, Carlos and Peters, Baron},
abstractNote = {This work reexamines seeded simulation results for NaCl nucleation from a supersaturated aqueous solution at 298.15 K and 1 bar pressure. We present a linear regression approach for analyzing seeded simulation data that provides both nucleation rates and uncertainty estimates. Our results show that rates obtained from seeded simulations rely critically on a precise driving force for the model system. The driving force vs. solute concentration curve need not exactly reproduce that of the real system, but it should accurately describe the thermodynamic properties of the model system. We also show that rate estimates depend strongly on the nucleus size metric. We show that the rate estimates systematically increase as more stringent local order parameters are used to count members of a cluster and provide tentative suggestions for appropriate clustering criteria.},
doi = {10.1063/1.5024009},
journal = {Journal of Chemical Physics},
issn = {0021-9606},
number = 22,
volume = 148,
place = {United States},
year = {2018},
month = {5}
}

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