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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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2017Budgeting of Systematic Versus Stochastic Errors in Sensor Fusion for Piezo Electric Transducers3citations

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Kohl, D.
1 / 2 shared
Schitter, G.
1 / 3 shared
Saathof, Rudolf
1 / 1 shared
Chart of publication period
2017

Co-Authors (by relevance)

  • Kohl, D.
  • Schitter, G.
  • Saathof, Rudolf
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article

Budgeting of Systematic Versus Stochastic Errors in Sensor Fusion for Piezo Electric Transducers

  • Hoser, S.
  • Kohl, D.
  • Schitter, G.
  • Saathof, Rudolf
Abstract

<p>Inherent non-linearity of piezo electric transducers, used in atomic force microscopy limits the position accuracy. In order to improve linearity, the elongation can be estimated by charge measurements. To extend the frequency range to DC, strain gauges are added by means of sensor fusion. This paper addresses the challenge of choosing the filter parameters for a first order complimentary filter used for sensor fusion. After identifying stochastic and systematic errors of charge and strain gauge measurements, the optimal parameters of a first order complimentary filter is computed. Depending on the application different filter parameters are found for the same nano-positioning system, by minimizing either stochastic errors, systematic errors or a combination of both. By this method the positioning uncertainty of charge monitoring (234.1 nm) and strain gauge measurement (347.1 nm) is reduced to 140.6 nm for a commercial tube piezo.</p>

Topics
  • impedance spectroscopy
  • atomic force microscopy