Solving the Structure and Dynamics of Metal Nanoparticles by Combining X-Ray Absorption Fine Structure Spectroscopy and Atomistic Structure Simulations

Abstract

Extended X-ray absorption fine structure (EXAFS) spectroscopy is a premiere method for analysis of the structure and structural transformation of nanoparticles. Extraction of analytical information about the three-dimensional structure and dynamics of metal–metal bonds from EXAFS spectra requires special care due to their markedly non-bulk-like character. In recent decades, significant progress has been made in the first-principles modeling of structure and properties of nanoparticles. In this review, we summarize new approaches for EXAFS data analysis that incorporate particle structure modeling into the process of structural refinement.

In Situ/Operando Electrocatalyst Characterization by X-ray Absorption Spectroscopy

“…While the presence of MS paths complicates significantly the interpretation of EXAFS spectra, the sensitivity of MS paths to bonding angles provides also the possibility to use EXAFS to probe the 3D structure of the material rather than just radial distances. 66 This is especially relevant when advanced approaches to data analysis such as reverse Monte Carlo simulations are used 23 (see Section 4.4 ).…”

“… 162 − 167 It has been demonstrated by Claussen and others that in this case EXAFS data fitting may result in significantly underestimated coordination numbers, interatomic distances, and disorder factors. 23 , 166 − 174 A dramatic illustration of this problem is the analysis of Zn K-edge EXAFS data of a bulk Zn foil, Figure 8 . For this material, EXAFS fitting in Gaussian approximation applied to the first coordination shell contribution provides quite a good description of the experimental data ( Figure 8 a).…”

“…The interpretation of XAS data in these cases is often nontrivial, and the proper choice of data analysis tools can be just as important as the advancements and proper care implemented in the acquisition of the experimental data. 12 , 23 The former aspect is also less well represented in the previous reviews about the in situ XAS method.…”

Linking the evolution of catalytic properties and structural changes in copper–zinc nanocatalysts using operando EXAFS and neural-networks

“…In the latter case, A p and 4 p depend not only on the interatomic distances R, but also on relative positions of the atoms (e.g., bonding angles). 50 The RDFs g p (R) contain key information about the local structure of the materialaverage number of atoms of a given type around the absorbing atom, information about the interatomic distances, crystallographic structure, oxidation state, and disorder. We distinguish between the partial contributions of, e.g., Cu-O and Cu-Cu, because the scattering functions A Cu-O (and 4 Cu-O ) are substantially different from A Cu-Cu (and 4 Cu-Cu ).…”

“…† An important step before we apply the NN for the interpretation of real experimental data of interest is to validate its accuracy by applying it to the analysis of experimental data of reference materials, for which the corresponding structure is known, or can be extracted by other methods. As in our previous works, 39,45,46 for this purpose we rely on reverse Monte Carlo (RMC) simulations, 50,[64][65][66] which for bulk materials with well-dened structures provide an alternative way to t experimental EXAFS data ( Fig. 1(a)) and extract RDFs (Fig.…”