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 (2/2 displayed)

  • 2023A computational analysis of a novel therapeutic approach combining an advanced medicinal therapeutic device and a fracture fixation assembly for the treatment of osteoporotic fractures3citations
  • 2020Mechanical Characterization and Modeling of the Porcine Cerebral Meninges11citations

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Mondal, Subrata
1 / 2 shared
Bonatti, Amedeo Franco
1 / 2 shared
Acutis, Aurora De
1 / 1 shared
Chatzinikolaidou, Maria
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Fiorilli, Sonia
1 / 7 shared
Dunne, Nicholas
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Vitale-Brovarone, Chiara
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Dalgarno, Kenny
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Vozzi, Giovanni
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Maria, Carmelo De
1 / 3 shared
Lally, Caitríona
1 / 3 shared
Annaidh, Aisling Ní
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Gaul, Robert
1 / 1 shared
Merle, Florence
1 / 1 shared
Gilchrist, Michael D.
1 / 2 shared
Carroll, Louise
1 / 1 shared
Pierrat, Baptiste
1 / 1 shared
Chart of publication period
2023
2020

Co-Authors (by relevance)

  • Mondal, Subrata
  • Bonatti, Amedeo Franco
  • Acutis, Aurora De
  • Chatzinikolaidou, Maria
  • Fiorilli, Sonia
  • Dunne, Nicholas
  • Vitale-Brovarone, Chiara
  • Dalgarno, Kenny
  • Vozzi, Giovanni
  • Maria, Carmelo De
  • Lally, Caitríona
  • Annaidh, Aisling Ní
  • Gaul, Robert
  • Merle, Florence
  • Gilchrist, Michael D.
  • Carroll, Louise
  • Pierrat, Baptiste
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article

Mechanical Characterization and Modeling of the Porcine Cerebral Meninges

  • Lally, Caitríona
  • Annaidh, Aisling Ní
  • Gaul, Robert
  • Merle, Florence
  • Gilchrist, Michael D.
  • Carroll, Louise
  • Pierrat, Baptiste
  • Macmanus, David B.
Abstract

The cerebral meninges, made up of the dura, arachnoid, and pia mater, is a tri-layer membrane that surrounds the brain and the spinal cord and has an important function in protecting the brain from injury. Understanding its mechanical behavior is important to ensure the accuracy of finite element (FE) head model simulations which are commonly used in the study of traumatic brain injury (TBI). Mechanical characterization of freshly excised porcine dura-arachnoid mater (DAM) was achieved using uniaxial tensile testing and bulge inflation testing, highlighting the dependency of the identified parameters on the testing method. Experimental data was fit to the Ogden hyperelastic material model with best fit material parameters of μ = 450 ± 190 kPa and α = 16.55 ± 3.16 for uniaxial testing, and μ = 234 ± 193 kPa and α = 8.19 ± 3.29 for bulge inflation testing. The average ultimate tensile strength of the DAM was 6.91 ± 2.00 MPa (uniaxial), and the rupture stress at burst was 2.08 ± 0.41 MPa (inflation). A structural analysis using small angle light scattering (SALS) revealed that while local regions of highly aligned fibers exist, globally, there is no preferred orientation of fibers and the cerebral DAM can be considered to be structurally isotropic. This confirms the results of the uniaxial mechanical testing which found that there was no statistical difference between samples tested in the longitudinal and transversal direction (p = 0.13 for μ, p = 0.87 for α). A finite element simulation of a craniotomy procedure following brain swelling revealed that the mechanical properties of the meninges are important for predicting accurate stress and strain fields in the brain and meninges. Indeed, a simulation using a common linear elastic representation of the meninges was compared to the present material properties (Ogden model) and the intracranial pressure was found to differ by a factor of 3. The current study has provided researchers with primary experimental data on the mechanical behavior of the meninges which will further improve the accuracy of FE head models used in TBI.

Topics
  • impedance spectroscopy
  • simulation
  • strength
  • tensile strength
  • isotropic
  • aligned
  • light scattering