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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1.080 Topics available

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977 Locations available

693.932 PEOPLE
693.932 People People

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IMDEA Materials

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (4/4 displayed)

  • 20244D printed shape-shifting biomaterials for tissue engineering and regenerative medicine applications35citations
  • 20244D printed shape-shifting biomaterials for tissue engineering and regenerative medicine applications35citations
  • 20244D Printing for Biomedical Applications65citations
  • 2022Additive manufacturing of bioactive and biodegradable porous iron-akermanite composites for bone regeneration39citations

Places of action

Chart of shared publication
Kalogeropoulou, Maria
2 / 2 shared
Zadpoor, Amir Abbas
1 / 1 shared
Mirzaali, Mohammad J.
2 / 16 shared
Fratila-Apachitei, Lidy
2 / 11 shared
Osch, Gerjo J. V. M. Van
1 / 1 shared
Zadpoor, Amir A.
1 / 7 shared
Fratila-Apachitei, Lidy E.
1 / 3 shared
Van Osch, Gerjo J. V. M.
1 / 1 shared
Zadpoor, Amir, A.
2 / 38 shared
Yarali, Ebrahim
1 / 7 shared
Mirzaali, Mohammad, J.
1 / 24 shared
Ghalayaniesfahani, Ava
1 / 2 shared
Accardo, Angelo
1 / 9 shared
Mol, Arjan
1 / 64 shared
Klimopoulou, Maria
1 / 4 shared
Putra, Niko Eka
1 / 8 shared
Leeflang, M. A.
1 / 25 shared
Zhou, Jie
1 / 31 shared
Taheri, Peyman
1 / 16 shared
Borg, K. G. N.
1 / 2 shared
Chart of publication period
2024
2022

Co-Authors (by relevance)

  • Kalogeropoulou, Maria
  • Zadpoor, Amir Abbas
  • Mirzaali, Mohammad J.
  • Fratila-Apachitei, Lidy
  • Osch, Gerjo J. V. M. Van
  • Zadpoor, Amir A.
  • Fratila-Apachitei, Lidy E.
  • Van Osch, Gerjo J. V. M.
  • Zadpoor, Amir, A.
  • Yarali, Ebrahim
  • Mirzaali, Mohammad, J.
  • Ghalayaniesfahani, Ava
  • Accardo, Angelo
  • Mol, Arjan
  • Klimopoulou, Maria
  • Putra, Niko Eka
  • Leeflang, M. A.
  • Zhou, Jie
  • Taheri, Peyman
  • Borg, K. G. N.
OrganizationsLocationPeople

document

4D Printing for Biomedical Applications

  • Zadpoor, Amir, A.
  • Díaz-Payno, Pedro J.
  • Yarali, Ebrahim
  • Mirzaali, Mohammad, J.
  • Ghalayaniesfahani, Ava
  • Accardo, Angelo
Abstract

<p>4D (bio-)printing endows 3D printed (bio-)materials with multiple functionalities and dynamic properties. 4D printed materials have been recently used in biomedical engineering for the design and fabrication of biomedical devices, such as stents, occluders, microneedles, smart 3D-cell engineered microenvironments, drug delivery systems, wound closures, and implantable medical devices. However, the success of 4D printing relies on the rational design of 4D printed objects, the selection of smart materials, and the availability of appropriate types of external (multi-)stimuli. Here, this work first highlights the different types of smart materials, external stimuli, and design strategies used in 4D (bio-)printing. Then, it presents a critical review of the biomedical applications of 4D printing and discusses the future directions of biomedical research in this exciting area, including in vivo tissue regeneration studies, the implementation of multiple materials with reversible shape memory behaviors, the creation of fast shape-transformation responses, the ability to operate at the microscale, untethered activation and control, and the application of (machine learning-based) modeling approaches to predict the structure–property and design–shape transformation relationships of 4D (bio)printed constructs.</p>

Topics
  • activation
  • machine learning