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

Journal Article · · Journal of Colloid and Interface Science
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, pKa1 decreased with increasing SSD while the opposite tendency was observed for pKa2. 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.
Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
Korea Nuclear International Cooperation Foundation (KONICOF); USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1992192
Report Number(s):
LLNL-JRNL-846013; 1070014
Journal Information:
Journal of Colloid and Interface Science, Journal Name: Journal of Colloid and Interface Science Journal Issue: na Vol. 648; ISSN 0021-9797
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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