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

Robinson, Donald A.

  • Google
  • 1
  • 12
  • 0

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2022Proton Tunable Analog Transistor for Low Power Computingcitations

Places of action

Chart of shared publication
Schrader, Paul
1 / 1 shared
Cole-Filipiak, Neil
1 / 1 shared
Talin, Albert Alec
1 / 3 shared
Krishnakumar, Raga
1 / 1 shared
Spataru, Catalin D.
1 / 1 shared
Bhandarkar, Austin
1 / 1 shared
Bennett, Christopher H.
1 / 1 shared
Foster, Michael E.
1 / 2 shared
Ramasesha, Krupa
1 / 1 shared
Fuller, Elliot J.
1 / 2 shared
Stavila, Vitalie
1 / 19 shared
Allendorf, Mark D.
1 / 14 shared
Chart of publication period
2022

Co-Authors (by relevance)

  • Schrader, Paul
  • Cole-Filipiak, Neil
  • Talin, Albert Alec
  • Krishnakumar, Raga
  • Spataru, Catalin D.
  • Bhandarkar, Austin
  • Bennett, Christopher H.
  • Foster, Michael E.
  • Ramasesha, Krupa
  • Fuller, Elliot J.
  • Stavila, Vitalie
  • Allendorf, Mark D.
OrganizationsLocationPeople

report

Proton Tunable Analog Transistor for Low Power Computing

  • Schrader, Paul
  • Cole-Filipiak, Neil
  • Talin, Albert Alec
  • Krishnakumar, Raga
  • Spataru, Catalin D.
  • Bhandarkar, Austin
  • Bennett, Christopher H.
  • Foster, Michael E.
  • Robinson, Donald A.
  • Ramasesha, Krupa
  • Fuller, Elliot J.
  • Stavila, Vitalie
  • Allendorf, Mark D.
Abstract

This project was broadly motivated by the need for new hardware that can process information such as images and sounds right at the point of where the information is sensed (e.g. edge computing). The project was further motivated by recent discoveries by group demonstrating that while certain organic polymer blends can be used to fabricate elements of such hardware, the need to mix ionic and electronic conducting phases imposed limits on performance, dimensional scalability and the degree of fundamental understanding of how such devices operated. As an alternative to blended polymers containing distinct ionic and electronic conducting phases, in this LDRD project we have discovered that a family of mixed valence coordination compounds called Prussian blue analogue (PBAs), with an open framework structure and ability to conduct both ionic and electronic charge, can be used for inkjet-printed flexible artificial synapses that reversibly switch conductance by more than four orders of magnitude based on electrochemically tunable oxidation state. Retention of programmed states is improved by nearly two orders of magnitude compared to the extensively studied organic polymers, thus enabling in-memory compute and avoiding energy costly off-chip access during training. We demonstrate dopamine detection using PBA synapses and biocompatibility with living neurons, evoking prospective application for brain - computer interfacing. By application of electron transfer theory to in-situ spectroscopic probing of intervalence charge transfer, we elucidate a switching mechanism whereby the degree of mixed valency between N-coordinated Ru sites controls the carrier concentration and mobility, as supported by density functional theory (DFT) .

Topics
  • density
  • impedance spectroscopy
  • compound
  • phase
  • mobility
  • theory
  • density functional theory
  • biocompatibility
  • polymer blend