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

Hogan, Benjamin T.

  • Google
  • 1
  • 4
  • 12

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2019Tuning silicon-rich nitride microring resonances with graphene capacitors for high-performance computing applications12citations

Places of action

Chart of shared publication
Gardes, Frederic Y.
1 / 9 shared
Faneca, Joaquin
1 / 1 shared
Baldycheva, Anna
1 / 2 shared
Diez, Iago R.
1 / 1 shared
Chart of publication period
2019

Co-Authors (by relevance)

  • Gardes, Frederic Y.
  • Faneca, Joaquin
  • Baldycheva, Anna
  • Diez, Iago R.
OrganizationsLocationPeople

article

Tuning silicon-rich nitride microring resonances with graphene capacitors for high-performance computing applications

  • Gardes, Frederic Y.
  • Hogan, Benjamin T.
  • Faneca, Joaquin
  • Baldycheva, Anna
  • Diez, Iago R.
Abstract

We demonstrate the potential of a graphene capacitor structure on silicon-rich nitride micro-ring resonators for multitasking operations within high performance computing. Capacitor structures formed by two graphene sheets separated by a 10 nm insulating silicon nitride layer are considered. Hybrid integrated photonic structures are then designed to exploit the electro-absorptive operation of the graphene capacitor to tuneably control the transmission and attenuation of different wavelengths of light. By tuning the capacitor length, a shift in the resonant wavelength is produced giving rise to a broadband multilevel photonic volatile memory. The advantages of using silicon-rich nitride as the waveguiding material in place of the more conventional silicon nitride (Si3N4) are shown, with a doubling of the device’s operational bandwidth from 31.2 to 62.41 GHz achieved while also allowing a smaller device footprint. A systematic evaluation of the device’s performance and energy consumption is presented. A difference in the extinction ratio between the ON and OFF states of 16.5 dB and energy consumptions of <0.3 pJ/bit are obtained. Finally, it has been demonstrated that increasing the permittivity of the insulator layer in the capacitor structure, the energy consumption per bit can be reduced even further. Overall, the resonance tuning enabled by the novel graphene capacitor makes it a key component for future multilevel photonic memories and optical routing in high performance computing.

Topics
  • impedance spectroscopy
  • nitride
  • Silicon