A model towards understanding stabilities and crystallization pathways of iron (oxyhydr)oxides in redox-dynamic environments. (1st November 2022)

• Record Type: Journal Article
• Authors: Li, Xiaoxu; Sheng, Anxu; Ding, Yuefei; Liu, Juan
• Is Part Of: Geochimica et cosmochimica acta. Volume 336(2022)
• Page Start: 92
• Page End: 103
• Publication Date: 2022-11-01
• Subjects: Iron (oxyhydr)oxides -- Crystallization pathway -- Nucleation energy barrier -- Phase transformation -- Metastable phases; Geochemistry -- Periodicals; Meteorites -- Periodicals; Géochimie -- Périodiques; Météorites -- Périodiques; Geochemie; Astrochemie; Electronic journals; 551.905
• DOI: 10.1016/j.gca.2022.09.002
• Languages: English
• ISSNs: 0016-7037

Abstract

Abstract: Crystallization and transformation of iron (oxyhydr)oxides occur widely in redox-dynamic environments, which are closely linked to iron cycling, (im)mobilization of co-associated elements, and microbial iron metabolisms. Although numerous studies have been conducted to investigate the occurrence and fate of iron (oxyhydr)oxides under various redox conditions, the mechanism controlling these processes is still incompletely understood. Here, we present a theoretical model, based on Classical Nucleation Theory (CNT), that can be used to predict and rationalize phase-selection and crystallization pathways of iron (oxyhydr)oxides under different redox conditions. By calculating the energy landscapes of dissolved or solid-phase iron species in a Fe-H2 O system as a function of Eh, pH, and particle size, we show how the stability regions of iron (oxyhydr)oxides change with geochemical environments (pH and redox potential) and initial properties of precursors (particle size and crystallinity). Through the calculation of thermodynamic driving forces and energy barriers for the nucleation of different metastable phases, the crystallization pathways of iron (oxyhydr)oxides via hydrolysis of Fe 3+ (aq), oxidation of Fe 2+ (aq), and Fe(II)-catalyzed ferrihydrite transformation can be predicted. The computational results show good agreement with previously reported experimental data. This study provides a unified model to predict and understand relative stability, transformation, and persistence of iron (oxyhydr)oxides under varying pH and redox conditions in natural environments.