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 (5/5 displayed)

  • 2022Elimination of the carbon-rich layer in Cu2ZnSn(S, Se)4 absorbers prepared from nanoparticle inks1citations
  • 2022Distributed Acoustic Sensing (DAS) for Intelligent In-Motion Transportation Condition Monitoring6citations
  • 2022Ex-situ Ge-doping of CZTS Nanocrystals and CZTSSe Solar Absorber Films8citations
  • 2022Recovery mechanisms in aged kesterite solar cells11citations
  • 2021Impact of Orientational Glass Formation and Local Strain on Photo-Induced Halide Segregation in Hybrid Metal-Halide Perovskitescitations

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Chart of shared publication
Zoppi, Guillaume
3 / 36 shared
Duchamp, Martial
2 / 14 shared
Qu, Yongtao
3 / 11 shared
Barrioz, Vincent
3 / 26 shared
Beattie, Neil
3 / 18 shared
Campbell, Stephen
3 / 9 shared
Taheri, Hossein
1 / 2 shared
Bocanegra, Maria Gonzalez
1 / 1 shared
Taheri, Mohammad
1 / 3 shared
Quan, Suyen Bueso
1 / 1 shared
Naylor, Matthew
2 / 2 shared
Sheppard, Alice
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Laverock, Jude
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Ford, Bethan
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Fox, Neil A.
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Xu, Xinya
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Tiwari, Devendra
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Maiello, Pietro
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Fermin, David J.
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Nguyen, Linh Lan
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Sanchez, Bartomeu Monserrat
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Friend, Richard, H.
1 / 549 shared
Goor, Tim Van De
1 / 1 shared
Neumann, Timo
1 / 11 shared
Bourelle, Sean A.
1 / 7 shared
Feldmann, Sascha
1 / 19 shared
Deschler, Felix
1 / 42 shared
Winkler, Thomas
1 / 12 shared
Kelly, Nicola D.
1 / 6 shared
Liu, Cheng
1 / 10 shared
Dutton, S. E.
1 / 21 shared
Chart of publication period
2022
2021

Co-Authors (by relevance)

  • Zoppi, Guillaume
  • Duchamp, Martial
  • Qu, Yongtao
  • Barrioz, Vincent
  • Beattie, Neil
  • Campbell, Stephen
  • Taheri, Hossein
  • Bocanegra, Maria Gonzalez
  • Taheri, Mohammad
  • Quan, Suyen Bueso
  • Naylor, Matthew
  • Sheppard, Alice
  • Laverock, Jude
  • Ford, Bethan
  • Fox, Neil A.
  • Xu, Xinya
  • Tiwari, Devendra
  • Maiello, Pietro
  • Fermin, David J.
  • Nguyen, Linh Lan
  • Sanchez, Bartomeu Monserrat
  • Friend, Richard, H.
  • Goor, Tim Van De
  • Neumann, Timo
  • Bourelle, Sean A.
  • Feldmann, Sascha
  • Deschler, Felix
  • Winkler, Thomas
  • Kelly, Nicola D.
  • Liu, Cheng
  • Dutton, S. E.
OrganizationsLocationPeople

document

Distributed Acoustic Sensing (DAS) for Intelligent In-Motion Transportation Condition Monitoring

  • Jones, Michael
  • Taheri, Hossein
  • Bocanegra, Maria Gonzalez
  • Taheri, Mohammad
  • Quan, Suyen Bueso
Abstract

<jats:title>Abstract</jats:title><jats:p>Safety is the top priority for every transportation system. Although various aspects of transportation infrastructure’s safety have been studied, in-motion monitoring and detection of defect is still a big concern. Understanding the trend of anomalies, and how to monitor undesired conditions are of high interest in transportation. In this study, the technology of Distributed Acoustic Sensing (DAS) for in-motion rail condition monitoring is studied through experimental testing and simulation modeling. DAS uses fiber optic cables along the track to detect any anomaly indicator. DAS permit the measurement of a desired parameter as a function of length along the fiber. Despite any conventional Nondestructive Testing (NDT) technique where the coverage or scanning area of the sensors are very limited, DAS provides a full, fast and accurate coverage of all section under the test. The objective of this research is to provide an assessment of anomaly detection and monitoring techniques based on DAS for transportation investigation. It presents the experimental evaluations and numerical simulations on the current methodologies in DAS systems. DAS was used to evaluate the transportation traffic condition in a rural area by connecting an available underground dark fiber to the DAS interrogator and system as well as simulated traffic condition in smaller scale in a parking lot. COMSOL Multiphysics software was used to model the interaction of ambient vibration with the fiber optic. Results show that the condition of the transportation can be monitored and detected by DAS with an appropriate accuracy. DAS information can be used for traffic condition monitoring, object tracking and flaw detections in the transportation lines.</jats:p>

Topics
  • impedance spectroscopy
  • simulation
  • defect