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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Delft University of Technology

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (7/7 displayed)

  • 2023Feasibility of On-demand Additive Manufacturing of Spare Partscitations
  • 2022Nonlinear coarse-graining models for 3D printed multi-material biomimetic composites11citations
  • 2020Mechanics of bioinspired functionally graded soft-hard composites made by multi-material 3D printing110citations
  • 2019Fracture Behavior of Bio-Inspired Functionally Graded Soft–Hard Composites Made by Multi-Material 3D Printing37citations
  • 2018Hatching for 3D prints17citations
  • 20173D hatching11citations
  • 2016Investigating the links between the process parameters and their influence on the aesthetic evaluation of selective laser melted partscitations

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Chart of shared publication
Oudheusden, A. A. Van
1 / 1 shared
Buijserd, A. J.
1 / 1 shared
Faludi, Jeremy
1 / 3 shared
Flipsen, Sebastiaan
1 / 1 shared
Balkenende, Ruud
1 / 7 shared
Zadpoor, Amir, A.
3 / 38 shared
Saldívar, Mauricio Cruz
1 / 1 shared
Mirzaali, Mohammad, J.
3 / 24 shared
Gunashekar, D.
1 / 3 shared
Nouri-Goushki, Mahdiyeh
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Ghatkesar, Murali Krishna
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Veeger, R. P. E.
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Grossman, Q.
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Angeloni, Livia
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Fratila-Apachitei, Lidy
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Ruffoni, D.
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Nava, A. Herranz De La
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Gunashekar, Deepthishre
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Nava, Alba Herranz De La
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Elkhuizen, Willemijn
1 / 1 shared
Verlinden, Jouke Casper
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Kuipers, Tim
2 / 2 shared
Verlinden, Jouke
1 / 1 shared
Previtali, B.
1 / 23 shared
Guagliano, M.
1 / 3 shared
Galimberti, G.
1 / 1 shared
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2022
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Co-Authors (by relevance)

  • Oudheusden, A. A. Van
  • Buijserd, A. J.
  • Faludi, Jeremy
  • Flipsen, Sebastiaan
  • Balkenende, Ruud
  • Zadpoor, Amir, A.
  • Saldívar, Mauricio Cruz
  • Mirzaali, Mohammad, J.
  • Gunashekar, D.
  • Nouri-Goushki, Mahdiyeh
  • Ghatkesar, Murali Krishna
  • Veeger, R. P. E.
  • Grossman, Q.
  • Angeloni, Livia
  • Fratila-Apachitei, Lidy
  • Ruffoni, D.
  • Nava, A. Herranz De La
  • Gunashekar, Deepthishre
  • Nava, Alba Herranz De La
  • Elkhuizen, Willemijn
  • Verlinden, Jouke Casper
  • Kuipers, Tim
  • Verlinden, Jouke
  • Previtali, B.
  • Guagliano, M.
  • Galimberti, G.
OrganizationsLocationPeople

article

Nonlinear coarse-graining models for 3D printed multi-material biomimetic composites

  • Zadpoor, Amir, A.
  • Saldívar, Mauricio Cruz
  • Doubrovski, Eugeni
  • Mirzaali, Mohammad, J.
Abstract

<p>Bio-inspired composites are a great promise for mimicking the extraordinary and highly efficient properties of natural materials. Recent developments in voxel-by-voxel 3D printing have enabled extreme levels of control over the material deposition, yielding complex micro-architected materials. However, design complexity, very large degrees of freedom, and limited computational resources make it a formidable challenge to find the optimal distribution of both hard and soft phases. To address this, a nonlinear coarse-graining approach is developed, where foam-based constitutive equations are used to predict the elastoplastic mechanical behavior of biomimetic composites. The proposed approach is validated by comparing coarse-grained finite element predictions against full-field strain distributions measured using digital image correlation. To evaluate the degree of coarse-graining on model accuracy, pre-notched specimens decorated with a binarized version of a renowned painting were modeled. Subsequently, coarse-graining is used to predict the fracture behavior of bio-inspired composites incorporating complex designs, such as functional gradients and hierarchical organizations. Finally, as a showcase of the proposed approach, the inverse coarse-graining is combined with a theoretical model of bone tissue adaptation to optimize the microarchitecture of a 3D-printed femur. The predicted properties were in exceptionally good agreement with the corresponding experimental results. Therefore, the coarse-graining method allows the design of advanced architected materials with tunable and predictable properties.</p>

Topics
  • Deposition
  • impedance spectroscopy
  • phase
  • composite
  • fracture behavior