S. A. Guda’s research while affiliated with Southern Federal University and other places

Compounds with the spinel structure present a technologically important class of materials. Spinels show a great variety of magnetic and magnetoelectric phenomena owing to the facile entrance of transition metals in the cationic sublattices. One of such examples is lithium ferrite LiFe5O8 with high ferrimagnetic phase transition temperature and cationic order-disorder transformations. The latter are important as they influence the crystal symmetry, which is crucial for physical properties. In this work we synthesize a series of (1-x)LiFe5O8–(x)LiZn2.5Ti2.5O8 (0≤x≤1) solid solutions and characterize them with various experimental and theoretical methods. The solid solutions experience a series of concentrational phase transformations between atomically ordered (P43(1)32) and disordered (Fd-3m) phases. The variation with concetration x of Fe3+ occupancies in cationic sublattices is studied using Mössbauer spectroscopy. The Mössbauer and magnetic measurements reveal sharp suppression of magnetic properties at x≥0.5 when the number of Fe3+ ions in the A-sublattice vanishes. The magnetic behaviour in the studied series of solid solutions is confirmed by Monte Carlo calculations with magnetic exchange interactions determined using the density functional theory.

X-ray absorption near edge structure (XANES) spectroscopy is a powerful method to probe the oxidation state and local structure of metals in catalytic materials. However, it suffers from the lack of unbiased data analysis protocols. Machine learning (ML) overcomes human-related factors by uncovering relevant spectrum-structure relationships and subsequent cross-validation analysis. The bottlenecks in the automatic processing of experimental data are the lack of chemically diverse XANES reference libraries and systematic differences between theory and experiment. Therefore, compiling experimental reference libraries across the periodic table and rational application of ML methodology to small (in terms of data science) training datasets becomes increasingly important. This work revises the classical XANES fingerprint analysis by database augmentation, feature extraction, cross-validation, and uncertainty analysis. We apply the developed methodology to decipher the oxidation state and local coordination of supported vanadium-oxo species (VOx), which change their structure participating in oxidative dehydrogenation catalysis. The developed library and instruments for analysis may serve as a starting point for a unified platform of fingerprint XANES data analysis.

X-ray absorption spectroscopy (XAS) has been central to the study of the Phillips polymerization catalyst (CrO3/SiO2). As Cr K-edge XAS signatures are sensitive to the oxidation state, geometry and types of ligands on surface (active) sites, the superposition of these effects makes their interpretation challenging. Notably, CO has been particularly used as a reductant to generate low valent Cr sites from CrO3/SiO2 and as a structural IR probe for analysing reduced Cr surface sites. Hence, it is essential to establish a solid understanding of the spectroscopic impact of CO on low-valent Cr sites. We thus built a series of fully characterized low-valent Cr molecular compounds bearing isoelectronic isocyanide ligands in place of CO, with the goal of understanding the effect of the coordination of π-acceptor ligands on the XANES signature of Cr sites. Cr K-edge spectra supplemented with DFT calculations elucidate the effect of the coordination of π-acceptor ligands on XAS signatures, giving a sharp resonance at the white line while modifying the fine structure due to short Cr–C distances and stability of low-spin Cr(ii/iii) species. The isocyanide references allow the deconvolution of the XAS spectra of the reduced CrO3/SiO2 catalyst by evaluating the types of surface species and relative amounts of bound CO at different CO pressures and temperatures.

X-ray absorption spectroscopy (XAS) is one of the most powerful characterization techniques, that has been intensively employed to study the Phillips polymerization catalyst (CrO3/SiO2). While Cr K-edge XAS signatures are used to evaluate the nature of surface (active) sites, they are highly sensitive to oxidation state, geometry and types of ligands, making interpretation challenging. In the specific case of CrO3/SiO2, CO has been particularly used both as a reductant to generate the expected low valent Cr sites and a probe to understand surface Cr sites. Considering the electronic properties of CO, a strong sigma-donor and pi-acceptor ligand, one may wonder the impact of the coordination of CO on Cr on its XAS signature. We herein built a molecular low-valent Cr library bearing isocyanide ligands, which mimic CO as its isoelectronic counterpart, as a model of low-valent Cr sites interacting with pi-acceptor ligand. Cr K-edge XAS augmented with DFT calculations elucidated the profound effect of isocyanide ligand on both XANES and EXAFS regions giving a rise to characteristic features as well as the significant stabilization of low-spin Cr(II/III) species, which potentially alter the ease of interpretation of XAS spectra. Taking the herein demonstrated effect of pi-acceptor ligand into account, experimental Cr K-edge spectra of reduced Phillips catalyst at different temperatures, with/without interaction with CO, were nicely reproduced.

Hard X-ray absorption spectroscopy is a valuable in situ probe for non-destructive diagnostics of metal sites. The low-energy interval of a spectrum (XANES) contains information about the metal oxidation state, ligand type, symmetry and distances in the first coordination shell but shows almost no dependency on the bridged metal–metal bond length. The higher-energy interval (EXAFS), on the contrary, is more sensitive to the coordination numbers and can decouple the contribution from distances in different coordination shells. Supervised machine-learning methods can combine information from different intervals of a spectrum; however, computational approaches for the near-edge region of the spectrum and higher energies are different. This work aims to keep all benefits of XANES and extend its sensitivity towards the interatomic distances in the first and second coordination shells. Using a binuclear bridged copper complex as a case study and cross-validation analysis as a quantitative tool it is shown that the first 170 eV above the edge are already sufficient to balance the contributions of Cu–O/N scattering and Cu–Cu scattering. As a more general outcome this work highlights the trivial but often overlooked importance of using `longer' energy intervals of XANES for structural refinement and machine-learning predictions. The first 200 eV above the absorption edge still do not require parametrization of Debye–Waller damping and can be calculated within full multiple scattering or finite difference approximations with only moderately increased computational costs.