The effect of atomic steps on adsorption and desorption of CO on Ru()

Zubkov, Tykhon; Morgan, Gregg A.; Yates, John T.; Kühlert, O.; Lisowski, M; Schillinger, R.; Fick, D.; Jänsch, H.J.

doi:10.1016/s0039-6028(02)02655-9

Cited by 105 publications

(137 citation statements)

References 55 publications

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“…In the second case when implementing a new analysis method like the linear programming it is necessary to define input parameters that can be entered in the form of a query, to process the request and read data from the database and hand the results to possibly further filters or a visualization tools. To get the linear programming working we had to retrieve the data from the database, write them to files and execute an external Python program puLP [65] to solve the linear programming problem. The output of puLP then had to be read again.…”

Section: 12c Technical Aspectsmentioning

confidence: 99%

The Computational Materials Repository

et al. 2012

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The ongoing growth in computing power enables researchers to perform such a large number of simulations that cannot be analyzed with paper and pencil any more. Simple approaches of processing data: ordering the calculations in directories and using a script to create a spreadsheet or a small database have to be redesigned for every new project. Sharing intermediate data with collaborators can be cumbersome and when publishing on the Internet specially tailored infrastructure has to be set up.Due to the diverse and changing landscape of electronic structure codes and methods there is no unique way of storing, collecting and presenting results. However there are many partial solutions: VMDF (paper D) a tool to filter and analyze aggregated sets of electronic structure data presents a first step towards user-friendly analysis of data. The Inorganic Crystal Structure Database ICSD [1, 2], collects very specific data and makes it accessible through a web interface; AflowLib (Ab-initio Electronic Structure Library) [3] provides access to structure properties of many compounds on the Internet.What is missing is a system that is Open Source Software, generic enough to support different codes, different abstraction levels and enables users to analyze their own results, and allows to share data with collaborators.The approach of the Computational Materials Repository (CMR) is to convert data to an internal format that maintains the original variable names without insisting on any semantics. Imported data can be implicitly grouped by user criteria and therefore maintain their natural connection in the database as well. Automatic data analysis is enabled through agents that analyze and group data based on predefined rules. Small projects can be handled without the need of database software while bigger projects one can use to improve performance.ii CMR enables one to create templates for the collection and analysis of data independently of the electronic structure code, simplifies screenings involving a lot of calculations, allows one to perform automatic analysis of data based on taxonomy, tags and keywords, provides the ability to share data with collaborators and maintains the link from the derived to the original data. ResuméDen igangvaerende vaekst i computerkraft gør det muligt for forskere at udføre et såstort antal simuleringer, at det ikke laengere er muligt at analysere med papir og blyant. Enkle tilgange til behandling af data: samling af beregninger i mapper og brug af et script til at generere et regneark eller en lille database måredesignes for hvert nyt projekt. Deling af intermediaer data med samarbejdspartnere kan vaere besvaerligt og ved publikation påinternettet skal specifikt skraeddersyede infrastrukturer opsaettes.Grundet det mangeartede og foranderlige landskab af koder og metoder til elektronstruktur-beregninger findes ingen unik måde at gemme, samle og praesentere resultater på. Der findes imidlertid mange delvise løsninger: VMDF (paper D) er et vaerktøj til filtrering og analyse af aggreger...

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Section: 12c Technical Aspectsmentioning

confidence: 99%

The Computational Materials Repository

et al. 2012

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“…6(b), and shows two desorption features at B390 K and B450 K. An additional, smaller peak can be seen at B530 K. This spectrum agrees well with the typical desorption spectrum obtained from the Ru(001) facet. 18,22,[30][31][32] The two principal peaks can be attributed to desorption of molecularly adsorbed CO from the terraces (a peaks), while the smaller peak can be attributed to desorption of dissociatively adsorbed CO from step sites (b peak). 13,22 B Ru (0 1 54) surface Fig.…”

Section: A Ru Nanoparticles On Hopgmentioning

confidence: 99%

“…18,22,[30][31][32] The two principal peaks can be attributed to desorption of molecularly adsorbed CO from the terraces (a peaks), while the smaller peak can be attributed to desorption of dissociatively adsorbed CO from step sites (b peak). 13,22 B Ru (0 1 54) surface Fig. 7(a) and (b) show STM images of the non-sputtered Ru (0 1 54) surface and the same surface after sputtering for 5 min, respectively.…”

Section: A Ru Nanoparticles On Hopgmentioning

confidence: 99%

“…13,19,21,22,32 This was demonstrated by Shincho et al, 13 Yamada et al 19 and Zubkov et al 21,22 using isotopic scrambling experiments, which rely on the recombination and desorption of atomic carbon and oxygen originating from the dissociative adsorption of CO. It was furthermore demonstrated that deposition of carbon at surface steps blocked them for dissociative adsorption of CO and resulted in the disappearance of the b peak from CO desorption spectra.…”

Section: Introductionmentioning

confidence: 96%

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Probing the crossover in CO desorption from single crystal to nanoparticulate Ru model catalysts

Murphy

Strebel

Vendelbo

et al. 2011

Phys. Chem. Chem. Phys.

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“…The same effect has been found for a number of other molecules. [35][36][37][38][39][40][41] Such effects are clearly important in determining the activity of a catalyst. For reactions where steps have a high reactivity, the density of such sites on the supported nanoparticle catalysts is a crucial parameter.…”

Section: The Geometrical and Electronic Factor In Catalysismentioning

confidence: 99%

A molecular view of heterogeneous catalysis

Christensen

Nørskov

2008

The Journal of Chemical Physics

120

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The establishment of a molecular view of heterogeneous catalysis has been hampered for a number of reasons. There are, however, recent developments, which show that we are now on the way towards reaching a molecular-scale picture of the way solids work as catalysts. By a combination of new theoretical methods, detailed experiments on model systems, and synthesis and in situ characterization of nano-structured catalysts, we are witnessing the first examples of complete atomic-scale insight into the structure and mechanism of surface-catalyzed reactions. This insight has already proven its value by enabling a rational design of new catalysts. We illustrate this important development in heterogeneous catalysis by highlighting recent examples of catalyst systems for which it has been possible to achieve such a detailed understanding. In particular, we emphasize examples where this progress has made it possible to propose entirely new catalysts, which have then been proven experimentally to exhibit improved performance in terms of catalytic activity or selectivity.

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The effect of atomic steps on adsorption and desorption of CO on Ru()

Cited by 105 publications

References 55 publications

The Computational Materials Repository

The Computational Materials Repository

Probing the crossover in CO desorption from single crystal to nanoparticulate Ru model catalysts

A molecular view of heterogeneous catalysis

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