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 (1/1 displayed)

  • 2023NonInvasive Glucose Fiber Sensor Based on Self-Imaging Technique: Proof of Conceptcitations

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Cunha, Cristina
1 / 4 shared
Frazão, Orlando
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Novais, Susana
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Chart of publication period
2023

Co-Authors (by relevance)

  • Cunha, Cristina
  • Frazão, Orlando
  • Novais, Susana
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document

NonInvasive Glucose Fiber Sensor Based on Self-Imaging Technique: Proof of Concept

  • Cunha, Cristina
  • Frazão, Orlando
  • Silva, Susana
  • Novais, Susana
Abstract

<jats:p>This paper proposes a proof of concept for a reflective fiber optic sensor based on multimode interference, designed to measure glucose concentrations in aqueous solutions that mimic the range of glucose concentrations found in human saliva. The sensor is fabricated by splicing a short section of coreless silica fiber into a standard single-mode fiber. By studying the principles of multimode interference and Self-imaging it was developed a sensing head that has a total length of 29.1 <jats:italic>mm</jats:italic>, approximately equal to the second self-image cycle. This sensing head allowed us to detect low concentrations of glucose (ranging from 0 to 268 <jats:italic>mg/dl</jats:italic>).</jats:p>

Topics
  • impedance spectroscopy