Application of community data to surface complexation modeling framework development: Iron oxide protolysis.

Autor: Han SC; Seaborg Institute, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550, United States., Chang E; Seaborg Institute, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550, United States., Zechel S; Institute of Resource Ecology, Actinide Thermodynamics Department (FWOA), Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328 Dresden, Germany., Bok F; Institute of Resource Ecology, Actinide Thermodynamics Department (FWOA), Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328 Dresden, Germany., Zavarin M; Seaborg Institute, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550, United States. Electronic address: zavarin1@llnl.gov.
Jazyk: angličtina
Zdroj: Journal of colloid and interface science [J Colloid Interface Sci] 2023 Oct 15; Vol. 648, pp. 1015-1024. Date of Electronic Publication: 2023 Jun 10.
DOI: 10.1016/j.jcis.2023.06.054
Abstrakt: This study presents a comprehensive community data-driven surface complexation modeling framework for simulating potentiometric titration of mineral surfaces. Compiled community data for ferrihydrite, goethite, hematite, and magnetite are fit to produce representative protolysis constants that can reproduce potentiometric titration data collected from multiple literature sources. Using this framework, the impact of surface complexation model type and surface site density (SSD) on the fit quality and protolysis constants can be readily evaluated. For example, the non-electrostatic model yielded a poor data fit compared to diffuse double layer model and constant capacitance models due to the absence of known surface charge effects. Regardless of the choice of iron oxide mineral, pK a1 decreased with increasing SSD while the opposite tendency was observed for pK a2 . This newly developed framework demonstrates a method to reconcile community data-wide potentiometric titration data using Findable, Accessible, Interoperable, Reusable data principles to produce mineral protolysis constants that improve robustness of surface complexation models for applications in metal sorption and reactive transport modeling. The framework is readily expandable (as community data increase) and extensible (as the number of minerals increase). The framework provides a path forward for developing self-consistent, comprehensive, and updateable surface complexation databases for surface complexation and reactive transport modeling.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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