Jul 2026· Chemistry of Materials· Vol 38, pp. 7649-7661· 0 citations· 71 references
Abstract
Surface properties of metal oxides are determined by their atomic structures, which can be exceedingly complex, including different surface terminations, chemistries and phase precipitates. First-principles studies have advanced our understanding of oxide surface reconstructions, but often face challenges due to the limited exploration of surface compositional and configurational spaces. To overcome this limitation, this study integrates bulk and surface thermodynamics consistently to effectively sample surface configurations. Our method is Grand Canonical Monte Carlo (GCMC) calculations, accelerated by a machine-learning interatomic potential. This approach is applied to a model perovskite oxide, La0.6Sr0.4FeO3–δ (LSF), a state-of-the-art oxygen electrode material for solid oxide cells. To make GCMC calculations computationally feasible, we first assessed the competing bulk phases in equilibrium with LSF. We used these phases as initial guesses at the surfaces of LSF. GCMC then refined these surface structures to identify equilibrium surface structures on LSF under different thermodynamic conditions. In calculating surface energies, the chemical potentials of the cations were evaluated as functions of the oxygen partial pressure, the bulk oxygen and cation vacancy concentrations, and the overall bulk composition. Surface segregations of SrO2, SrO, La2O3, Fe, and Ruddlesden–Popper (RP) phases were found at different oxygen chemical potentials. Surface phase diagrams of LSF (001) show that SrO-terminated RP phase segregation dominates under moderate oxygen environment, while oxidizing and reducing environments favor SrO2 formation and Fe exsolution, respectively. A decrease in temperature reduces the oxygen partial pressure window for RP segregation on the LSF (001) surface. The results provide useful insights into the surface thermodynamics of LSF (001), and the method can be leveraged to investigate surface atomic structures across a broader range of complex oxides.
High-entropy alloys (HEAs) provide compositionally diverse surfaces for electrocatalysis, yet how their surface atomic arrangements dictate active-site ensembles and catalytic activity remains unclear. Here, we develop a dropwise deposition strategy to synthesize Pd@Pd0.2Pt0.2Ir0.2Ru0.2Rh0.2 core–shell nanocrystals w...
Kuan-Fang Lee, Liang Hou, Yueh-Chun Hsiao et al.· Journal of the American Chem...· 0 citations
Metal surfaces undergo structural, compositional, and morphological changes in response to their chemical environment. Tuning the surfaces'function and stability for a given application correspondingly necessitates an understanding of how this surface evolution couples to external conditions. Here, we demonstrate the f...
F. Riccius, Karsten Reuter, H. Heenen et al.· 0 citations
Amorphous aluminosilicates are essential components of fluid catalytic cracking (FCC) catalysts, where they provide structural support, hierarchical porosity, and acid functionality within the mesoporous matrix. A molecular-level description of the active acid site ensemble remains challenging because these materials...
Kaustubh J. Sawant, D. Stockwell, Anthony D. Debellis et al.· ACS Catalysis· 0 citations
The surface chemistry of additively manufactured aluminum alloys plays a critical role in corrosion resistance and joining with external materials. In this work, the near-surface elemental composition of a laser powder bed fusion (PBF-LB/M) processed Al-Mg-Si-Zr alloy was characterized by glow discharge optical emissio...
Zheng-Qing Wei, Philip Grimm, Inna Plyushchay et al.· 0 citations
Oxide surfaces play a crucial role in large-scale applications, including catalysis and electronics. Despite their common use, their surface stability remains a subject of ongoing debate, particularly in computational studies where pristine bulk-terminated models are often used instead of reconstructed, defective, or c...
Bader A. Alayyoub, Jin-Yu Xu, Majd Ayyad et al.· Physical Chemistry, Chemical...· 0 citations
This review aims to provide a comprehensive perspective on the ongoing transition from conventional DFT-based simulations toward scalable, statistically rigorous, and predictive atomistic modeling frameworks for HEAs and related compositionally complex materials.
Yuji Ikeda, Xiang Xu, Pranav Kumar et al.· Journal of Materials Science· 1 citation
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