Applications of X-ray Absorption Spectroscopy in Heterogeneous Catalysis: EXAFS, Atomic XAFS, and Delta XANES

Koningsberger, D.C.; Ramaker, David E.

doi:10.1002/9783527610044.hetcat0040

Cited by 10 publications

(19 citation statements)

References 68 publications

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“…The chemical bonding within the F-NiFe-A was analyzed by the Fourier-transform (FT) extended X-ray absorption fine structure (EXAFS) spectroscopy (Figure i). The peaks at 2.2, 4.0, and 4.7 Å are attributed to Ni–Ni metal bonds (Ni m –Ni m ), which are the reduced distances (due to the energy dependence of the phase factors during the Fourier transform) . The lowest Ni m –Ni m peak intensity of F-NiFe-A among all samples indicates its surface is covered with the thickest “reformed” Ni(Fe)O x H y layer. , The Fe K-edge XANES and EXAFS of F-NiFe-A (Figure S7) are in accordance with this interpretation.…”

Section: Resultsmentioning

confidence: 99%

Fluorination-enabled Reconstruction of NiFe Electrocatalysts for Efficient Water Oxidation

et al. 2020

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Developing low-cost and efficient electrocatalysts to accelerate oxygen evolution reaction (OER) kinetics is vital for water and carbon-dioxide electrolyzers. The fastest-known water oxidation catalyst, Ni(Fe)O x H y , usually produced through an electrochemical reconstruction of precatalysts under alkaline condition, has received substantial attention. However, the reconstruction in the reported catalysts usually leads to a limited active layer and poorly controlled Feactivated sites. Here, we demonstrate a new electrochemistry-driven Fenabled surface-reconstruction strategy for converting the ultrathin NiFeO x F y nanosheets into an Fe-enriched Ni(Fe)O x H y phase. The activated electrocatalyst shows a low OER overpotential of 218 ± 5 mV at 10 mA cm −2 and a low Tafel slope of 31 ± 4 mV dec −1 , which is among the best for NiFe-based OER electrocatalysts. Such superior performance is caused by the effective formation of the Fe-enriched Ni(Fe)O x H y active-phase that is identified by operando Raman spectroscopy and the substantially improved surface wettability and gas-bubble-releasing behavior.

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Section: Resultsmentioning

confidence: 99%

Fluorination-enabled Reconstruction of NiFe Electrocatalysts for Efficient Water Oxidation

et al. 2020

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“…In XAFS, because the radial distance obtained from the Fourier transformation is not always equal to the real one due to the phase problem, the analysis by the imaginary part was performed and showed a good coincidence (Figure B). Finally, based on our analysis, the FEFF evaluation strongly suggests that the catalytic solution predominately contains the mononuclear species 6a ·2H 2 O (Figure A–C).…”

Section: Results and Discussionmentioning

confidence: 96%

Pd/Cu-Catalyzed Dehydrogenative Coupling of Dimethyl Phthalate: Synchrotron Radiation Sheds Light on the Cu Cycle Mechanism

et al. 2020

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Pd/Cu-catalyzed dehydrogenative coupling of dimethyl phthalate is an important industrial process for the production of aromatic polyimide precursors. Nonetheless, the detailed mechanism of the Cu cycle has remained unclear. The present study describes the detailed mechanism of the Cu cycle in the [Pd(OAc) 2 ]/Cu(OAc) 2 /1,10-phenanthroline (phen) system. The solution-phase X-ray absorption fine structure analysis of the catalyst solutions and the FEFF fitting as well as the evaluation of the catalytic and stoichiometric reactions reveal the following observations: (i) the major intermediate in the catalytic cycle is a mononuclear divalent [Cu(OAc) 2 ]•2H 2 O species, (ii) coordination of the phen ligand to the Cu catalyst significantly inhibits the catalytic activity, (iii) 2 equiv of Cu(OAc) 2 •H 2 O oxidizes the zerovalent "Pd(phen)" species to divalent [Pd(OAc) 2 (phen)], and (iv) the divalent [Cu(OAc) 2 ] 2 •2AcOH species is regenerated by the treatment of monovalent Cu(OAc) with AcOH in air.

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“…where T is a is a square invertible matrix, called transformation matrix. Because the matrix product TT −1 is equal to the identity matrix I, the variation of each element t ij of T does not have any kind of impact on the decomposition shown by Equation (11). However, the abstract spectra and concentration profiles can be grouped in the following way: S = S abs T and C T = T −1 C T abs .…”

Section: Transformation Matrix Approach (Tm)mentioning

confidence: 99%

“…The XAS signal exclusively stems from the absorber-containing species in the system, but it is averaged over all such species simultaneously present in the sample volume probed by the X-ray beam, weighted by their relative abundance. On the one hand, element selectivity represents a key advantage in the field of catalysis, especially for the characterisation of heterogeneous catalysts where highly diluted active sites are often distributed without long-range order over a much more abundant (crystalline or amorphous) support/matrix [2,[11][12][13]. On the other hand, the average response of the technique poses important challenges in situations where multiple absorber-containing species (e.g., active and inactive/spectator species) coexist and dynamically evolve along the experiment.…”

Section: Introductionmentioning

confidence: 99%

Spectral Decomposition of X-ray Absorption Spectroscopy Datasets: Methods and Applications

Martini

Borfecchia

2020

Crystals

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X-ray absorption spectroscopy (XAS) today represents a widespread and powerful technique, able to monitor complex systems under in situ and operando conditions, while external variables, such us sampling time, sample temperature or even beam position over the analysed sample, are varied. X-ray absorption spectroscopy is an element-selective but bulk-averaging technique. Each measured XAS spectrum can be seen as an average signal arising from all the absorber-containing species/configurations present in the sample under study. The acquired XAS data are thus represented by a spectroscopic mixture composed of superimposed spectral profiles associated to well-defined components, characterised by concentration values evolving in the course of the experiment. The decomposition of an experimental XAS dataset in a set of pure spectral and concentration values is a typical example of an inverse problem and it goes, usually, under the name of multivariate curve resolution (MCR). In the present work, we present an overview on the major techniques developed to realize the MCR decomposition together with a selection of related results, with an emphasis on applications in catalysis. Therein, we will highlight the great potential of these methods which are imposing as an essential tool for quantitative analysis of large XAS datasets as well as the directions for further development in synergy with the continuous instrumental progresses at synchrotron sources.

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Applications of X-ray Absorption Spectroscopy in Heterogeneous Catalysis: EXAFS, Atomic XAFS, and Delta XANES

Cited by 10 publications

References 68 publications

Fluorination-enabled Reconstruction of NiFe Electrocatalysts for Efficient Water Oxidation

Fluorination-enabled Reconstruction of NiFe Electrocatalysts for Efficient Water Oxidation

Pd/Cu-Catalyzed Dehydrogenative Coupling of Dimethyl Phthalate: Synchrotron Radiation Sheds Light on the Cu Cycle Mechanism

Spectral Decomposition of X-ray Absorption Spectroscopy Datasets: Methods and Applications

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