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 (2/2 displayed)

  • 2023Design and characterization of reversible thermodynamic SMPU-based fabrics with improved comfort properties5citations
  • 2023Polyurethane shape memory filament yarns: Melt spinning, carbon-based reinforcement, and characterization17citations

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Chart of shared publication
González, Marta
2 / 5 shared
Jovančić, Petar
2 / 7 shared
Rodriguez, Rosa
2 / 3 shared
Ardanuy, Mònica
2 / 7 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • González, Marta
  • Jovančić, Petar
  • Rodriguez, Rosa
  • Ardanuy, Mònica
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article

Polyurethane shape memory filament yarns: Melt spinning, carbon-based reinforcement, and characterization

  • González, Marta
  • Gonzalez, Judit
  • Jovančić, Petar
  • Rodriguez, Rosa
  • Ardanuy, Mònica
Abstract

<jats:p> The aim of this work was to develop and characterize polyurethane-based shape memory polymer filament yarns of a suitable diameter and thermo-mechanical performance for use in tailored multi-sectorial applications. Different polymer compositions – pure shape memory polyurethane and shape memory polyurethane composites with 0.3 and 0.5 wt.% of multi-walled carbon nanotubes or carbon black as additives – were studied. Filaments were obtained using a melt spinning process that allowed the production of the permanent and temporary shape of the shape memory polyurethane filament. Two drawing speeds (20 and 32 m/min) were studied. Characterization techniques such as the tensile test, differential scanning calorimetry, and dynamic mechanical analysis were used to investigate the shape-memory effect of the filaments. Pure and additive shape memory polyurethane filament yarns of a controlled diameter were produced. The results indicated that the pure shape memory polyurethane on the temporary shape had the highest tensile strength (234 MPa). Filaments with carbon black revealed a significant strain (335%) in the permanent shape with respect to the other filaments. The melt spinning process influenced the soft segment glass transition temperature (T<jats:sub>gs</jats:sub>) significantly, with a decrease in the temporary shape (first heating) as compared to the permanent shape (second and third heating). However, only the 0.5% multi-walled carbon nanotubes additive clearly influenced the filament, increasing the T<jats:sub>gs</jats:sub> by 10°C. The additives also influenced the shape-memory effect, obtaining an increased fixity ratio (up to 97%) with the multi-walled carbon nanotubes additive and an increased recovery ratio (up to 86%) with the carbon black additive. </jats:p>

Topics
  • polymer
  • Carbon
  • nanotube
  • melt
  • glass
  • glass
  • strength
  • composite
  • glass transition temperature
  • differential scanning calorimetry
  • tensile strength
  • drawing
  • melt spinning
  • dynamic mechanical analysis