Probing Compositional Order in Atomic Columns: STEM Simulations Beyond the Virtual Crystal Approximation.

Area of Science:

• Materials Science
• Computational Materials Science
• Solid-State Chemistry

Background:

• Compositional disorder in complex oxides impacts material properties.
• The virtual crystal approximation (VCA) is a common but potentially inaccurate method for modeling disorder.
• Experimental techniques like HAADF-STEM are sensitive to atomic arrangements.

Purpose of the Study:

• To investigate compositional disorder in Mo,V-oxide bronze using advanced computational methods.
• To compare simulation results with experimental data and identify limitations of the VCA.
• To determine the influence of atomic ordering on high-angle annular dark-field (HAADF) imaging.

Main Methods:

• Multislice frozen-phonon calculations utilizing parallel computing.
• Modeling compositional disorder in metal-oxygen atomic columns.
• Analysis of high-angle annular dark-field (HAADF) imaging simulations and experimental data.

Main Results:

• The virtual crystal approximation underestimates V content in Mo,V-oxide bronze compared to simulations considering cation ordering.
• Discrepancies between VCA and simulations exceed the variability caused by different atomic configurations.
• HAADF-STEM imaging can distinguish between ordered and random atomic arrangements along columns.
• Simulated intensity variations qualitatively match experimental HAADF-STEM data for Mo,V-oxide bronze.

Conclusions:

• The VCA is insufficient for accurately modeling compositional disorder in this system.
• Atomic ordering significantly influences HAADF-STEM image intensities.
• A limited number of random configurations can effectively represent intensity variations, improving simulation accuracy.