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  4. Nitride Ferroelectric Domain Wall Memory for Next-Generation Computing
 
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2026
Journal Article
Title

Nitride Ferroelectric Domain Wall Memory for Next-Generation Computing

Abstract
The emerging nitride ferroelectrics, such as Al1-xScxN promise to significantly advance our current information technology. In particular, two-terminal memristive devices are ideal candidates for artificial intelligence accelerators and in-memory computing due to their simplicity in design, non-volatility and non-destructive readout. The recent discovery of conductive domain walls in Al1-xScxN is a promising enabler for such technology, offering several benefits compared to barrier height modulation- or tunneling-based devices. First, domain walls can be highly conductive and feature high read currents (required for aggressive lateral scaling and fast access times), also in non-epitaxial films without being restricted to the technologically challenging ultrathin thickness regime (< 10 nm). Second, nitride ferroelectrics are fully compatible with silicon and GaN technology on which the ferroelectric domain wall memory (FeDMEM) can be integrated with logic circuitry. Third, excellent scalability and temperature resistance of ferroelectric Al1-xScxN were demonstrated, enabling scaled, low-latency edge computing under extreme environmental conditions. In this study, a FeDMEM device consisting of a Pt/Al0.72Sc0.28N/Pt capacitor grown on Si substrates is electrically characterized in-depth, revealing unique peculiarities in the memristive response. A read current density of 350 A/m2 and an ON/OFF ratio of 20 is achieved, allowing for consistent storing of up to eight levels of information.
Author(s)
Schönweger, Georg
Fraunhofer-Institut für Siliziumtechnologie ISIT  
Dasenbrook, Deik
Christian-Albrechts-Universität zu Kiel
Kyoushi, Niklas
Fraunhofer-Institut für Siliziumtechnologie ISIT  
Guido, Roberto
NaMLab gGmbH
Petraru, Adrian
Christian-Albrechts-Universität zu Kiel
Mikolajick, Thomas
NaMLab gGmbH
Schröder, Uwe
NaMLab gGmbH
Kohlstedt, Hermann H.
Christian-Albrechts-Universität zu Kiel
Fichtner, Simon  
Fraunhofer-Institut für Siliziumtechnologie ISIT  
Journal
Advanced electronic materials  
Open Access
File(s)
Download (2.43 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.1002/aelm.202500616
10.24406/publica-6918
Additional link
Full text
Language
English
Fraunhofer-Institut für Siliziumtechnologie ISIT  
Keyword(s)
  • domain wall conduction

  • Keywords: aluminum scandium nitride

  • memristive device

  • neuromorphic computing

  • nitride ferroelectrics

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