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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Materials Map under construction

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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1.080 Topics available

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977 Locations available

693.932 PEOPLE
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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2016Cysteine residues reduce the severity of dopamine electrochemical fouling30citations
  • 2014Analysis of liposome model systems by time-of-flight secondary ion mass spectrometry6citations
  • 2009Time-of-flight secondary ion mass spectrometry imaging of subcellular lipid heterogeneity35citations

Places of action

Chart of shared publication
Poulin, Philippe
1 / 55 shared
Harreither, Wolfgang
1 / 2 shared
Safina, Gulnara
1 / 1 shared
Trouillon, Raphaël
1 / 1 shared
Neri, Wilfrid
1 / 21 shared
Lovrić, Jelena
1 / 1 shared
Keighron, Jacqueline D.
1 / 1 shared
Malmberg, Per
1 / 6 shared
Angerer, Tina B.
1 / 2 shared
Fletcher, John S.
1 / 14 shared
Winograd, Nicholas
1 / 3 shared
Davey, Angel M.
1 / 1 shared
Piehowski, Paul D.
1 / 1 shared
Heien, Michael L.
1 / 2 shared
Kurczy, Michael E.
1 / 1 shared
Chart of publication period
2016
2014
2009

Co-Authors (by relevance)

  • Poulin, Philippe
  • Harreither, Wolfgang
  • Safina, Gulnara
  • Trouillon, Raphaël
  • Neri, Wilfrid
  • Lovrić, Jelena
  • Keighron, Jacqueline D.
  • Malmberg, Per
  • Angerer, Tina B.
  • Fletcher, John S.
  • Winograd, Nicholas
  • Davey, Angel M.
  • Piehowski, Paul D.
  • Heien, Michael L.
  • Kurczy, Michael E.
OrganizationsLocationPeople

article

Time-of-flight secondary ion mass spectrometry imaging of subcellular lipid heterogeneity

  • Ewing, Andrew G.
  • Winograd, Nicholas
  • Davey, Angel M.
  • Piehowski, Paul D.
  • Heien, Michael L.
  • Kurczy, Michael E.
Abstract

<p>Mass spectrometric imaging is a powerful tool to interrogate biological complexity. One such technique, time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging, has been successfully utilized for subcellular imaging of cell membrane components. In order for this technique to provide insight into biological processes, it is critical to characterize the figures of merit. Because a SIMS instrument counts individual events, the precision of the measurement is controlled by counting statistics. As the analysis area decreases, the number of molecules available for analysis diminishes. This becomes critical when imaging subcellular features; it limits the information obtainable, resulting in images with only a few counts of interest per pixel. Many features observed in low intensity images are artifacts of counting statistics, making validation of these features crucial to arriving at accurate conclusions. With TOF-SIMS imaging, the experimentally attainable spatial resolution is a function of the molecule of interest, sample matrix, concentration, primary ion, instrument transmission, and spot size of the primary ion beam. A model, based on Poisson statistics, has been developed to validate SIMS imaging data when signal is limited. This model can be used to estimate the effective spatial resolution and limits of detection prior to analysis, making it a powerful tool for tailoring future investigations. In addition, the model allows comparison of pixel-to-pixel intensity and can be used to validate the significance of observed image features. The implications and capabilities of the model are demonstrated by imaging the cell membrane of resting RBL-2H3 mast cells.</p>

Topics
  • impedance spectroscopy
  • spectrometry
  • selective ion monitoring
  • secondary ion mass spectrometry