Determination of the Mo surface environment of Mo/TiO2 catalysts by EXAFS, XANES and PCA

Fay, Martin J.; Proctor, Andrew; Hoffmann, Douglas P.; Houalla, Marwan; Hercules, David M.

doi:10.1007/bf01242483

Cited by 45 publications

(31 citation statements)

References 26 publications

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“…The authors proposed this Mo-X distance to correspond with a Mo-Al contribution in a Mo-O-Al configuration. The average distance of 2.87 ± 0.035Å found in the titania catalysts for Mo-Ti agrees with proposed Mo-Ti contributions in the spectra of MoO 3 /TiO 2 by Fay et al (52) and Shimada et al (53). The absence of a Mo-Ti contribution in Mo/TiO 2 (nc) can be explained by the poor interaction between the surface of the TiO 2 -support and the molybdenum precursor.…”

Section: Structure Of the Molybdenum Oxide Phasesupporting

confidence: 77%

A Mo–K Edge XAFS Study of the Metal Sulfide-Support Interaction in (Co)Mo Supported Alumina and Titania Catalysts

Leliveld

Dillen

Geus

et al. 1997

Journal of Catalysis

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Section: Structure Of the Molybdenum Oxide Phasesupporting

confidence: 77%

A Mo–K Edge XAFS Study of the Metal Sulfide-Support Interaction in (Co)Mo Supported Alumina and Titania Catalysts

Leliveld

Dillen

Geus

et al. 1997

Journal of Catalysis

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“…The sterical arrangement of the two phenolic OH groups is the reason for the strong complexation capability of PCA toward uranium(VI). Although eigenanalysis has been applied previously to X-ray absorption spectra [21,33,34,35,36,37,38], our algorithm allowed to extract the spectral components contained in a series of EXAFS measurements for the first time. For the implementation of the proposed factor analysis algorithm, we wrote a computer code in the programming language FORTRAN90.…”

Section: Discussionmentioning

confidence: 99%

Complexation of uranium(VI) with protocatechuic acid?application of iterative transformation factor analysis to EXAFS spectroscopy

Roßberg¹,

Reich

Bernhard

2003

Analytical and Bioanalytical Chemistry

153

100

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The speciation of 1 mM uranium(VI) in carbonate-free aqueous solutions of 50 mM protocatechuic acid (PCA, 3,4-dihydroxybenzoic acid) was studied in the pH range of 4.0 to 6.8 using EXAFS spectroscopy. The uranium L(III)-edge EXAFS spectra were analyzed using a newly developed computer algorithm for iterative transformation factor analysis (FA). Two structural different uranium(VI) complexes were observed. The speciation in the pH range of 4.0 to 4.8 is dominated by a 1:2 or 1:3 uranium(VI)/PCA complex with bidentate coordination of the carboxyl group to the uranium(VI) moiety. Already at pH 4.6 significant amounts of a second species are formed. This uranium(VI) species contains two PCA ligands that are bound to the uranium via their neighboring phenolic hydroxyl groups under formation of five-member rings.

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“…Deviation from the real number of chemical species (r) notably occurs when the experimental noise is close to the variation in the data, the data normalized inconsistently from a spectrum to another, and some component species either minor, their fractional weight statistically constant in the dataset, or their spectral features indistinct (Fay et al, 1992;Beauchemin et al, 2002;Manceau et al, 2002;Rossberg & Scheinost, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…, m ). The jth component is accepted as a PC ( jth = x) if the percentage of significance level (%SL) for the F-test is lower than some test level, generally 5% (Fernandez-Garcia et al, 1995;Má rquez-Alvarez et al, 1997;Iglesias-Juez et al, 2004;Anunziata et al, 2011;Fay et al, 1992;Menacherry et al, 1997;Ruitenbeek et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

“…Although the three dimensionality estimators have been applied successfully in several studies (Fay et al, 1992;Ruitenbeek et al, 2000;Ciuparu et al, 2005;Jalilehvand et al, 2006;Kirpichtchikova et al, 2006;Mah & Jalilehvand, 2008Breynaert et al, 2010;Manceau & Matynia, 2010;Wieland et al, 2010), they frequently run into difficulties with over-or under-estimation of PCs Panfili et al, 2005;Sarret et al, 2004;Má rquez-Alvarez et al, 1997;Conti et al, 2010). Deviation from the real number of chemical species (r) notably occurs when the experimental noise is close to the variation in the data, the data normalized inconsistently from a spectrum to another, and some component species either minor, their fractional weight statistically constant in the dataset, or their spectral features indistinct (Fay et al, 1992;Beauchemin et al, 2002;Manceau et al, 2002;Rossberg & Scheinost, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Estimating the number of pure chemical components in a mixture by X-ray absorption spectroscopy

Manceau

Marcus

Lenoir³

2014

J Synchrotron Rad

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Principal component analysis (PCA) is a multivariate data analysis approach commonly used in X-ray absorption spectroscopy to estimate the number of pure compounds in multicomponent mixtures. This approach seeks to describe a large number of multicomponent spectra as weighted sums of a smaller number of component spectra. These component spectra are in turn considered to be linear combinations of the spectra from the actual species present in the system from which the experimental spectra were taken. The dimension of the experimental dataset is given by the number of meaningful abstract components, as estimated by the cascade or variance of the eigenvalues (EVs), the factor indicator function (IND), or the F-test on reduced EVs. It is shown on synthetic and real spectral mixtures that the performance of the IND and F-test critically depends on the amount of noise in the data, and may result in considerable underestimation or overestimation of the number of components even for a signal-to-noise (s/n) ratio of the order of 80 (σ = 20) in a XANES dataset. For a given s/n ratio, the accuracy of the component recovery from a random mixture depends on the size of the dataset and number of components, which is not known in advance, and deteriorates for larger datasets because the analysis picks up more noise components. The scree plot of the EVs for the components yields one or two values close to the significant number of components, but the result can be ambiguous and its uncertainty is unknown. A new estimator, NSS-stat, which includes the experimental error to XANES data analysis, is introduced and tested. It is shown that NSS-stat produces superior results compared with the three traditional forms of PCA-based component-number estimation. A graphical user-friendly interface for the calculation of EVs, IND, F-test and NSS-stat from a XANES dataset has been developed under LabVIEW for Windows and is supplied in the supporting information. Its possible application to EXAFS data is discussed, and several XANES and EXAFS datasets are also included for download.

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Determination of the Mo surface environment of Mo/TiO2 catalysts by EXAFS, XANES and PCA

Cited by 45 publications

References 26 publications

A Mo–K Edge XAFS Study of the Metal Sulfide-Support Interaction in (Co)Mo Supported Alumina and Titania Catalysts

A Mo–K Edge XAFS Study of the Metal Sulfide-Support Interaction in (Co)Mo Supported Alumina and Titania Catalysts

Complexation of uranium(VI) with protocatechuic acid?application of iterative transformation factor analysis to EXAFS spectroscopy

Estimating the number of pure chemical components in a mixture by X-ray absorption spectroscopy

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