Reverse Monte Carlo modeling for local structures of noble metal nanoparticles using high-energy XRD and EXAFS

Abstract

3-Dimensional atomic-scale structure of metal nanoparticles obtained by RMC-based simulations using HEXRD and EXAFS data.

There's no place like real-space: elucidating size-dependent atomic structure of nanomaterials using pair distribution function analysis

“…[71][72][73] While widely applied for fully amorphous and disordered crystalline materials, this approach has been less used for nanomaterials, although recent examples have shown its application to nanoparticles. [74][75][76] Independent of the approach to modelling, the quality of a t to a PDF is oen analyzed through the R w -factor, which is a measure of the difference between the calculated (G calc ) and experimental PDF (G obs ) that is calculated as:…”

“…62,73,243 This makes the models and rened parameters more reliable, as they have been constrained by structural information obtained from techniques with different strengths and weaknesses, such as when combining PDF or total scattering with SAXS 95,187,244 or EXAFS data. 74,245 The interest and development of advanced computational techniques such as database mining and machine learning are very likely to impact PDF analysis as well as many other dataheavy elds in the coming years. 246 For example, machine learning methods have already been applied to PDF in regards to component analysis 123,[247][248][249][250] and in identifying symmetry and extracting distance lists.…”

Building Practical Descriptors for Defect Engineering of Electrocatalytic Materials

“…The PDF is thus sensitive to microstrain; however, its effect is combined to thermal displacement and instrumental broadening, from which it is difficult to extract. The PDF can also be used with Reverse Monte Carlo minimization of large atomic assemblies, which allows a statistical description of samples from liquids and amorphous to crystalline nanoparticles …”

“…The PDF can also be used with Reverse Monte Carlo minimization of large atomic assemblies, which allows a statistical description of samples from liquids and amorphous to crystalline nanoparticles. 16 From Bulk Microstrain to Surface Distortion. The main reason to correct microstrain values is related to the definition of microstrain itself, which links a local variation of the interplanar distance d between d−Δd and d+Δd according to: In practice, there is a distribution of Δd/d within and across the coherent domains.…”

Probing the Local Atomic Structure of In and Cu in Sphalerite by XAS Spectroscopy Enhanced by Reverse Monte Carlo Algorithm

“…According to quantum chemical Density Functional Theory (DFT) calculations, such deformation can be observed in the case of the close arrangement of impurities (In and Cu), or the atom of In and the vacancy. Nonetheless, the conventional method of EXAFS spectra approximation, realized in the IFEFFIT software package [3], usually provides less accurate results for the disordered or amorphous materials than for the structures of high symmetry [4,5]. To improve the quality of the EXAFS spectra fittings, we employed the reverse Monte Carlo (RMC) method, which is highly informative in exploring the distortion of crystal structure around impurities [6,7].…”