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 (8/8 displayed)

  • 2023VO2 stabilization on Si for memristor in neuromorphic computing applicationscitations
  • 2023Interplay between Strain and Defects at the Interfaces of Ultra‐Thin Hf 0.5 Zr 0.5 O 2 ‐Based Ferroelectric Capacitors15citations
  • 2023Thermal information processing using phase change materialscitations
  • 2021Electrical Characterisation of HfZrO2 Ferroelectric Tunnel Junctions for Neuromorphic Applicationcitations
  • 2021Développement d’un capteur environnemental ultra-basse consommation à base de SnO2 en technologie CMOS FDSOIcitations
  • 2021Structure, chemical analysis, and ferroelectric properties of chemical solution derived epitaxial PbZr$_{0.2}$Ti$_{0.8}$O$_3$ films for nanomechanical switchingcitations
  • 2021Impact of a dielectric layer at TiN/HfZrO2 interface for ferroelectric tunnel junctions applicationscitations
  • 2021Role of ultra-thin Ti and Al interfacial layers in HfZrO2 ferroelectric tunnel junctionscitations

Places of action

Chart of shared publication
Sahoo, Swayam
2 / 6 shared
Bugnet, Matthieu
3 / 32 shared
Méchin, Laurence
2 / 24 shared
Frechette, Luc
2 / 7 shared
Lamirand, Anne
2 / 9 shared
Pierron, Victor
2 / 10 shared
Vilquin, Bertrand
8 / 68 shared
Deleruyelle, Damien
4 / 26 shared
Barhoumi, Rabei
4 / 22 shared
Nirantar, Shruti
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Romeo, Pedro Rojo
5 / 18 shared
Mayes, Edwin
1 / 3 shared
Blanchard, Nicholas
1 / 20 shared
Segantini, Greta
4 / 23 shared
Manchon, Benoît
1 / 9 shared
Sriram, Sharath
3 / 16 shared
Baboux, Nicolas
3 / 38 shared
Drouin, Dominique
1 / 8 shared
Alibart, F.
1 / 7 shared
Manchon, Benoit
3 / 15 shared
Resende, João
1 / 3 shared
Pelissier, Bernard
1 / 5 shared
Souifi, Abdelkader
1 / 1 shared
Salem, Bassem
1 / 19 shared
Theo, Levert
1 / 1 shared
Assaf, Antonio
1 / 1 shared
Barnes, Jean-Paul
1 / 17 shared
Canut, Bruno
1 / 13 shared
Albertini, David
1 / 10 shared
Brottet, Solène
1 / 6 shared
Gautier, Brice
1 / 15 shared
Casal, Sergio Gonzalez
1 / 2 shared
Bai, Xiaofei
1 / 5 shared
Chart of publication period
2023
2021

Co-Authors (by relevance)

  • Sahoo, Swayam
  • Bugnet, Matthieu
  • Méchin, Laurence
  • Frechette, Luc
  • Lamirand, Anne
  • Pierron, Victor
  • Vilquin, Bertrand
  • Deleruyelle, Damien
  • Barhoumi, Rabei
  • Nirantar, Shruti
  • Romeo, Pedro Rojo
  • Mayes, Edwin
  • Blanchard, Nicholas
  • Segantini, Greta
  • Manchon, Benoît
  • Sriram, Sharath
  • Baboux, Nicolas
  • Drouin, Dominique
  • Alibart, F.
  • Manchon, Benoit
  • Resende, João
  • Pelissier, Bernard
  • Souifi, Abdelkader
  • Salem, Bassem
  • Theo, Levert
  • Assaf, Antonio
  • Barnes, Jean-Paul
  • Canut, Bruno
  • Albertini, David
  • Brottet, Solène
  • Gautier, Brice
  • Casal, Sergio Gonzalez
  • Bai, Xiaofei
OrganizationsLocationPeople

document

VO2 stabilization on Si for memristor in neuromorphic computing applications

  • Sahoo, Swayam
  • Bugnet, Matthieu
  • Méchin, Laurence
  • Frechette, Luc
  • Lamirand, Anne
  • Pierron, Victor
  • Infante Ingrid, C.
  • Vilquin, Bertrand
Abstract

Neuromorphic computing is being seen as a solution to address the memory bottleneck persistent with the present computing paradigm. To realize such an architecture, artificial synapses and neurons need to be built. One way to emulate a bio-synapse requires a material with an metal-insulator phase transition (MIT). VO2 undergoes a structural phase transformation (SPT) from monoclinic structure at room temperature to tetragonal at approximately 70°C. The SPT is accompanied by an IMT leading to a large variation in its electrical (about 4 orders of magnitude of its resistivity) and optical properties, in particular, in its complex refractive index in the mid-IR frequency range.To keep with the current trends of the microelectronic industry, it is imperative to integrate VO2 on silicon. However, the higher lattice mismatch and formation of oxides and silicates at the interface between VO2 and crystalline Si degrade the quality and functionality of VO2 film. Additionally, VO2(M1) is a challenging material to integrate into patterned heterostructures because it can exist not only as multiple polymorphs (A, B, M1) but the high-temperature depositions can lead to the formation of various oxidation states phases that are present in the V-O system (VnO2n-1, VnO2n+1).This work was conducted to study the growth of VO2 on silicon with oxide buffer layers using RF magnetron sputtering of a V2O5 ceramic target in argon atmosphere. We studied the structure-property relationships, specifically electrical and optical properties as a function of temperature across the Tc. Structural and compositional characterization are carried out using x-ray diffraction, atomic force microscopy (AFM), and x-ray photoemission spectroscopy (XPS) respectively, optical responses are studied using FTIR and electrical characterizations are performed using the four-point probe method. With the use of a very thin metal oxide buffer layer between silicon substrate and VO2 film, we demonstrate a high resistivity ratio (of the order 3 between the two phases) and investigate the scope of improvement. The results show the influence of substrates temperature, VO2 grain size and strain on the transition temperature, amplitude of transition and the lowering the thermal hysteresis of VO2 to 4°C. The preliminary findings mentioned here are being utilized to improve the electrical bistability, thus allowing us to improve the reproducibility in operational modes (switching, memory, logical operations, etc.) of neuromorphic devices.

Topics
  • Deposition
  • impedance spectroscopy
  • grain
  • resistivity
  • grain size
  • phase
  • x-ray diffraction
  • x-ray photoelectron spectroscopy
  • atomic force microscopy
  • phase transition
  • Silicon
  • ceramic