Recent Advances in Cerium Oxide-Based Memristors for Neuromorphic Computing

This review article attempts to provide a comprehensive review of the recent progress in cerium oxide (CeO2)-based resistive random-access memories (RRAMs). CeO2 is considered the most promising candidate because of its multiple oxidation states (Ce3+ and Ce4+), remarkable resistive-switching (RS) uniformity in DC mode, gradual resistance transition, cycling endurance, long data-retention period, and utilization of the RS mechanism as a dielectric layer, thereby exhibiting potential for neuromorphic computing. In this context, a detailed study of the filamentary mechanisms and their types is required. Accordingly, extensive studies on unipolar, bipolar, and threshold memristive behaviors are reviewed in this work. Furthermore, electrode-based (both symmetric and asymmetric) engineering is focused for the memristor's structures such as single-layer, bilayer (as an oxygen barrier layer), and doped switching-layer-based memristors have been proved to be unique CeO2-based synaptic devices. Hence, neuromorphic applications comprising spike-based learning processes, potentiation and depression characteristics, potentiation motion and synaptic weight decay process, short-term plasticity, and long-term plasticity are intensively studied. More recently, because learning based on Pavlov's dog experiment has been adopted as an advanced synoptic study, it is one of the primary topics of this review. Finally, CeO2-based memristors are considered promising compared to previously reported memristors for advanced synaptic study in the future, particularly by utilizing high-dielectric-constant oxide memristors.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:13

Enthalten in:

Nanomaterials (Basel, Switzerland) - 13(2023), 17 vom: 28. Aug.

Sprache:

Englisch

Beteiligte Personen:

Ali, Sarfraz [VerfasserIn]
Ullah, Muhammad Abaid [VerfasserIn]
Raza, Ali [VerfasserIn]
Iqbal, Muhammad Waqas [VerfasserIn]
Khan, Muhammad Farooq [VerfasserIn]
Rasheed, Maria [VerfasserIn]
Ismail, Muhammad [VerfasserIn]
Kim, Sungjun [VerfasserIn]

Links:

Volltext

Themen:

Capping layers
CeO2
Filamentary mechanisms
Journal Article
Neuromorphic learning systems
RRAM memristive devices
Review
Switching layers
Symmetric and asymmetric electrodes
Synaptic devices

Anmerkungen:

Date Revised 11.09.2023

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/nano13172443

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM361844425