Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

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.

×

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.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Kargin, Nikolai

  • Google
  • 1
  • 5
  • 3

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2019Anisotropy of Assemblies of Densely Packed Co-Alloy Nanoparticles Embedded in Carbon Nanotubes3citations

Places of action

Chart of shared publication
Normand, Francois
1 / 1 shared
Kukharev, Andrei
1 / 1 shared
Prischepa, Serghej
1 / 1 shared
Danilyuk, Alexander
1 / 1 shared
Cojocaru, Costel Sorin
1 / 23 shared
Chart of publication period
2019

Co-Authors (by relevance)

  • Normand, Francois
  • Kukharev, Andrei
  • Prischepa, Serghej
  • Danilyuk, Alexander
  • Cojocaru, Costel Sorin
OrganizationsLocationPeople

article

Anisotropy of Assemblies of Densely Packed Co-Alloy Nanoparticles Embedded in Carbon Nanotubes

  • Kargin, Nikolai
  • Normand, Francois
  • Kukharev, Andrei
  • Prischepa, Serghej
  • Danilyuk, Alexander
  • Cojocaru, Costel Sorin
Abstract

Текст статьи не публикуется в открытом доступе в соответствии с политикой журнала. ; We report on the magnetic properties of an array of binary metal CoFe, CoNi, and CoPt nanoparticles (NPs) embedded inside vertically oriented carbon nanotubes (CNTs). Samples were synthesized by chemical vapor deposition activated by current discharge plasma and hot filaments. Assemblies of Co-based catalytic NPs were prepared on SiO 2 /Si substrates by sputtering ultrathin films followed by reduction in an H 2 /NH 3 mixture. As a result of the CNT growth, each CNT contained only one ferromagnetic NP located at the top. For all samples, the easy axis of magnetization was along the CNT axis. The magnetic parameters, including effective anisotropy constant and the contributions of dipole interactions and shape, magnetocrystalline, and magnetoelastic anisotropies, were estimated based on the experimental data and a random-anisotropy model. The magnetoelastic contribution was decisive. From the magnetoelasticity, the stresses in the NPs embedded in the CNTs were determined. Finally, the magnetization distribution in CoFe, CoNi, and CoPt NPs was simulated considering the magnetoelastic contribution.

Topics
  • nanoparticle
  • Carbon
  • nanotube
  • random
  • magnetization
  • chemical vapor deposition