Janis Timoshenko

Identification of carbon-encapsulated iron nanoparticles as active species in non-precious metal oxygen reduction catalysts

The widespread use of fuel cells is currently limited by the lack of efficient and cost-effective catalysts for the oxygen reduction reaction. Iron-based non-precious metal catalysts exhibit promising activity and stability, as an alternative to state-of-the-art platinum catalysts. However, the identity of the active species in non-precious metal catalysts remains elusive, impeding the development of new catalysts. Here we demonstrate the reversible deactivation and reactivation of an iron-based non-precious metal oxygen reduction catalyst achieved using high-temperature gas-phase chlorine and hydrogen treatments. In addition, we observe a decrease in catalyst heterogeneity following treatment with chlorine and hydrogen, using Mössbauer and X-ray absorption spectroscopy. Our study reveals that protected sites adjacent to iron nanoparticles are responsible for the observed activity and stability of the catalyst. These findings may allow for the design and synthesis of enhanced non-precious metal oxygen reduction catalysts with a higher density of active sites.

Wavelet data analysis of EXAFS spectra

Abstract The application of wavelet transform to the analysis of the extended X-ray absorption fine structure (EXAFS) from perovskite-type compounds is presented on the example of the Re L 3 -edge in ReO 3 and Co K-edge in LaCoO 3 . We propose a modified wavelet transform procedure, which allows better discrimination of the overlapped contributions into the EXAFS signal.

Reverse Monte Carlo modeling of thermal disorder in crystalline materials from EXAFS spectra

Abstract In this work we present the Reverse Monte Carlo (RMC) modeling scheme, designed to probe the local structural and thermal disorder in crystalline materials by fitting the wavelet transform (WT) of the EXAFS signal. Application of the method to the analysis of the Ge K-edge and Re L3-edge EXAFS signals in crystalline germanium and rhenium trioxide, respectively, is presented with special attention to the problem of thermal disorder and related phenomena.

Nanoporous Copper–Silver Alloys by Additive-Controlled Electrodeposition for the Selective Electroreduction of CO2 to Ethylene and Ethanol

Electrodeposition of CuAg alloy films from plating baths containing 3,5-diamino-1,2,4-triazole (DAT) as an inhibitor yields high surface area catalysts for the active and selective electroreduction of CO2 to multicarbon hydrocarbons and oxygenates. EXAFS shows the co-deposited alloy film to be homogeneously mixed. The alloy film containing 6% Ag exhibits the best CO2 electroreduction performance, with the Faradaic efficiency for C2H4 and C2H5OH production reaching nearly 60 and 25%, respectively, at a cathode potential of just -0.7 V vs RHE and a total current density of ∼ - 300 mA/cm2. Such high levels of selectivity at high activity and low applied potential are the highest reported to date. In situ Raman and electroanalysis studies suggest the origin of the high selectivity toward C2 products to be a combined effect of the enhanced stabilization of the Cu2O overlayer and the optimal availability of the CO intermediate due to the Ag incorporated in the alloy.

Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles

Tracking the structure of heterogeneous catalysts under operando conditions remains a challenge due to the paucity of experimental techniques that can provide atomic-level information for catalytic metal species. Here we report on the use of X-ray absorption near-edge structure (XANES) spectroscopy and supervised machine learning (SML) for refining the 3D geometry of metal catalysts. SML is used to unravel the hidden relationship between the XANES features and catalyst geometry. To train our SML method, we rely on ab initio XANES simulations. Our approach allows one to solve the structure of a metal catalyst from its experimental XANES, as demonstrated here by reconstructing the average size, shape, and morphology of well-defined platinum nanoparticles. This method is applicable to the determination of the nanoparticle structure in operando studies and can be generalized to other nanoscale systems. It also allows on-the-fly XANES analysis and is a promising approach for high-throughput and time-dependent studies.

Analysis of extended x-ray absorption fine structure data from copper tungstate by the reverse Monte Carlo method

The static disorder and lattice dynamics of crystalline materials can be efficiently studied using reverse Monte Carlo simulations of extended x-ray absorption fine structure spectra (EXAFS). In this work we demonstrate the potentiality of this method on an example of copper tungstate CuWO4. The simultaneous analysis of the Cu K and W L3 edges EXAFS spectra allowed us to follow local structure distortion as a function of temperature.

Determination of bimetallic architectures in nanometer-scale catalysts by combining molecular dynamics simulations with x-ray absorption spectroscopy

Here we present an approach for the determination of an atomic structure of small bimetallic nanoparticles by combining extended X-ray absorption fine structure spectroscopy and classical molecular dynamics simulations based on the Sutton-Chen potential. The proposed approach is illustrated in the example of PdAu nanoparticles with ca 100 atoms and narrow size and compositional distributions. Using a direct modeling approach and no adjustable parameters, we were able to reproduce the size and shape of nanoparticles as well as the intra-particle distributions of atoms and metal mixing ratios and to explore the influence of these parameters on the local structure and dynamics in nanoparticles.

Molecular dynamics simulations of EXAFS in germanium

Classical molecular dynamics simulations have been performed for crystalline germanium with the aim to estimate the thermal effects within the first three coordination shells and their influence on the single-scattering and multiple-scattering contributions to the Ge K-edge extended x-ray absorption fine structure (EXAFS).

The Use of X-ray Absorption Spectra for Validation of Classical Force-Field Models

Abstract Extended X-ray absorption fine structure (EXAFS) spectroscopy and molecular dynamics (MD) simulations are two complementary techniques widely used to study the atomic structure of materials. Their combined use, known as the MD-EXAFS approach, allows one to access the structural information, encoded in EXAFS, far beyond the nearest coordination shells and to validate the accuracy of the interaction potential models. In this study we demonstrate the use of the MD-EXAFS method for a validation of several force-field models on an example of the cubic-perovskite SrTiO3 and hexagonal wurtzite-type ZnO crystals.

Local Structure of Cobalt Tungstate Revealed by EXAFS Spectroscopy and Reverse Monte Carlo/Evolutionary Algorithm Simulations

Abstract EXAFS spectroscopy is an element-specific method that can provide perhaps the most extensive information on the local atomic structure and lattice dynamics for a broad class of materials. Conventional methods of EXAFS data treatment are often limited to the nearest coordination shells of the absorbing atom due to the difficulties in accurate accounting for the large number of correlated structural parameters that have to be included in the analysis. In this study we overcome this problem by applying novel simulation-based method: reverse Monte Carlo simulations, coupled with the evolutionary algorithm and with a powerful signal processing technique – wavelet transform. This complex approach was applied to the analysis of the W L3-edge and Co K-edge EXAFS spectra of crystalline CoWO4, which exists in antiferromagnetic state below 55 K. Temperature dependence of the local environment up to 4.3 Å around both metal ions was reconstructed in the range from 10 K to 300 K, and the rigidity of the tungstate structure due to zigzag chains of WO6 and CoO6 octahedra was analyzed.