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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Hamburg University of Technology

in Cooperation with on an Cooperation-Score of 37%

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Publications (4/4 displayed)

  • 2023Fabric-like electrospun PVAc-graphene nanofiber webs as wearable and degradable piezocapacitive sensors27citations
  • 2023Fabric-like electrospun PVAc-graphene nanofiber webs as wearable and degradable piezocapacitive sensors27citations
  • 2019Bending of nanoporous thin films under ion radiation5citations
  • 2015Formation of Nanoporous Gold Studied by Transmission Electron Backscatter Diffraction6citations

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Sengupta, Debarun
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Co-Authors (by relevance)

  • Sengupta, Debarun
  • Kottapalli, Ajay Giri Prakash
  • Pei, Yutao T.
  • Jayawardhana, Bayu
  • Lu, Liqiang
  • Pei, Yutao
  • Lu, Ewan
  • Vainchtein, David
  • De Hosson, J. T. M.
  • Turkin, A.
  • Bremen, Rik Van
  • Ocelík, Václav
  • Nijholt, Jorrit E.
  • Hosson, Jeff Th. M. De
  • Jeer, Leo T. H. De
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article

Fabric-like electrospun PVAc-graphene nanofiber webs as wearable and degradable piezocapacitive sensors

  • Sengupta, Debarun
  • Kottapalli, Ajay Giri Prakash
  • Pei, Yutao T.
  • Jayawardhana, Bayu
  • Lu, Liqiang
  • Ribas Gomes, Diego
Abstract

Flexible piezocapacitive sensors utilizing nanomaterial-polymer composite based nanofibrous membranes offer an attractive alternative to more traditional piezoelectric and piezoresistive wearable sensors owing to their ultralow powered nature, fast response, low hysteresis, and insensitivity to temperature change. In this work we propose a facile method of fabricating electrospun graphene dispersed PVAc nanofibrous membrane based piezocapacitive sensors for applications in IoT enabled wearables and human physiological function monitoring. A series of electrical and material characterization experiments were conducted on both the pristine and graphene dispersed PVAc nanofibers to understand the effect of graphene addition on nanofiber morphology, dielectric response, and pressure sensing performance. Dynamic uniaxial pressure sensing performance evaluation tests were conducted on the pristine and graphene loaded PVAc nanofibrous membrane-based sensors for understanding the effect of two-dimensional (2D) nanofiller addition on pressure sensing performance. Almost twofold increase in dielectric constant and pressure sensing performance was observed for graphene loaded nanofiber sensors and subsequently, micro dipole formation model was invoked to explain the nanofiller induced dielectric constant enhancement. The robustness and reliability of the sensor has been underscored by conducting accelerated lifetime assessment experiments entailing at least 3000 cycles of periodic tactile force loading. A series of tests involving human physiological parameters monitoring were conducted to underscore the applicability of the proposed sensor for IoT enabled personalized health care, soft robotics, and next generation prosthetic devices. Finally, easy degradability of the sensing elements is demonstrated to emphasize their suitability for transient electronics applications.

Topics
  • impedance spectroscopy
  • polymer
  • experiment
  • dielectric constant
  • composite
  • two-dimensional