Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2022A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking23citations
  • 2022A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking23citations
  • 2001Tungsten-containing formate dehydrogenase from Desulfovibrio gigas: metal identification and preliminary structural data by multi-wavelength crystallography46citations

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Chart of shared publication
Moura, Isabel
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Brondino, Carlos D.
1 / 1 shared
Almendra, Maria João
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Dias, João Miguel
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Raaijmakers, Hans
1 / 1 shared
Moura, José J. G.
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Romao, Maria
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2022
2001

Co-Authors (by relevance)

  • Moura, Isabel
  • Brondino, Carlos D.
  • Almendra, Maria João
  • Dias, João Miguel
  • Raaijmakers, Hans
  • Moura, José J. G.
  • Romao, Maria
OrganizationsLocationPeople

article

A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking

  • Ryan, Timothy M.
  • Teixeira, Susana
  • Zuo, Xiaobing
  • Cleveland, Thomas E.
  • Svergun, Dmitri
  • Porcar, Lionel
  • Chatzimagas, Leonie
  • Rocco, Mattia
  • Gabel, Frank
  • Jeong, Cheol
  • Krueger, Susan
  • Kirby, Nigel
  • Weiss, Thomas M.
  • Whitten, Andrew
  • Wood, Kathleen
  • Vachette, Patrice
  • Hura, Greg L.
  • Hopkins, Jesse B.
  • Cowieson, Nathan
  • Li, Na
  • Huang, Qingqui
  • Blanchet, Clement
  • Graewert, Melissa
  • Brookes, Emre
  • Bierma, Jan
  • Hub, Jochen
  • Gillilan, Richard
  • Grishaev, Alexander
  • Thureau, Aurelien
  • Hammel, Michal
  • Pérez, Javier
  • Prangé, Thierry
  • Franke, Daniel
  • Seifert, Soenke
  • Chakravarthy, Srinivas
  • Martel, Anne
Abstract

<jats:p>Through an expansive international effort that involved data collection on 12 small-angle X-ray scattering (SAXS) and four small-angle neutron scattering (SANS) instruments, 171 SAXS and 76 SANS measurements for five proteins (ribonuclease A, lysozyme, xylanase, urate oxidase and xylose isomerase) were acquired. From these data, the solvent-subtracted protein scattering profiles were shown to be reproducible, with the caveat that an additive constant adjustment was required to account for small errors in solvent subtraction. Further, the major features of the obtained consensus SAXS data over the <jats:italic>q</jats:italic> measurement range 0–1 Å<jats:sup>−1</jats:sup> are consistent with theoretical prediction. The inherently lower statistical precision for SANS limited the reliably measured <jats:italic>q</jats:italic>-range to &lt;0.5 Å<jats:sup>−1</jats:sup>, but within the limits of experimental uncertainties the major features of the consensus SANS data were also consistent with prediction for all five proteins measured in H<jats:sub>2</jats:sub>O and in D<jats:sub>2</jats:sub>O. Thus, a foundation set of consensus SAS profiles has been obtained for benchmarking scattering-profile prediction from atomic coordinates. Additionally, two sets of SAXS data measured at different facilities to <jats:italic>q</jats:italic> &gt; 2.2 Å<jats:sup>−1</jats:sup> showed good mutual agreement, affirming that this region has interpretable features for structural modelling. SAS measurements with inline size-exclusion chromatography (SEC) proved to be generally superior for eliminating sample heterogeneity, but with unavoidable sample dilution during column elution, while batch SAS data collected at higher concentrations and for longer times provided superior statistical precision. Careful merging of data measured using inline SEC and batch modes, or low- and high-concentration data from batch measurements, was successful in eliminating small amounts of aggregate or interparticle interference from the scattering while providing improved statistical precision overall for the benchmarking data set.</jats:p>

Topics
  • size-exclusion chromatography
  • small-angle neutron scattering
  • small angle x-ray scattering
  • elution