Amorphous, fully-stoichiometric molybdenum oxide for high performance nonvolatile resistive switching memory: the role of stoichiometry on synaptic plasticity

Transition metal oxides (TMOs) are a promising class of materials for neuromorphic computing and processing systems demonstrating a variety of resistive switching (RS) mechanisms. However, little is known about the correlation between its stoichiometry and RS. This study is focused on the development and characterization of amorphous molybdenum oxide memristors with different stoichiometry. Fully-stoichiometric (MoO3) and hydrogenated sub-stoichiometric (H-MoO3 − x) amorphous molybdenum oxide thin films were developed via a hot-wire chemical vapor deposition system. Both, stoichiometric and hydrogenated sub-stoichiometric molybdenum oxide devices showed good resistive switching behavior. However, the fully-stoichiometric memristor exhibited better RS properties with endurance of 250 cycles, ON/OFF ratio ~ 103 and high retention of almost 3·104 s, compared with the poor RS behavior of the device based on the H-MoO3 − x film. This impressive memristive behavior could be attributed to the excess of oxygen vacancies in the case of fully-stoichiometric memristor in respect to the sub-stoichiometric H-MoO3 − x which play crucial role in the conductive behavior of the device. The high reproducibility observed in MoO3-based memristor highlights their potential for practical applications and scalability. Additionally, the outstanding features of the MoO3 memristor demonstrated through its long-term potentiation (LTP), long-term depression (LTD), and spike-timing dependent plasticity (STDP) indicate that the fully stoichiometric molybdenum oxide memristor has significant potential for simulating biological synapses, opening doors to a new era in neuromorphic computing applications.

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Publication Details

Journal
Discover Materials
Published
2025-12-04
DOI
https://doi.org/10.1007/s43939-025-00452-y
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Amorphous, fully-stoichiometric molybdenum oxide for high performance nonvolatile resistive switching memory: the role of stoichiometry on synaptic plasticity

Michail‐Alexandros Kourtis, Anastasia Soultati, Dimitris Davazoglou, Konstantinos Aidinis et al.
Discover Materials
Advanced Memory and Neural Computing
article

Amorphous, fully-stoichiometric molybdenum oxide for high performance nonvolatile resistive switching memory: the role of stoichiometry on synaptic plasticity

Michail‐Alexandros Kourtis, Anastasia Soultati, Dimitris Davazoglou, Konstantinos Aidinis, Gion Kalemai
article en

Abstract

Transition metal oxides (TMOs) are a promising class of materials for neuromorphic computing and processing systems demonstrating a variety of resistive switching (RS) mechanisms. However, little is known about the correlation between its stoichiometry and RS. This study is focused on the development and characterization of amorphous molybdenum oxide memristors with different stoichiometry. Fully-stoichiometric (MoO3) and hydrogenated sub-stoichiometric (H-MoO3 − x) amorphous molybdenum oxide thin films were developed via a hot-wire chemical vapor deposition system. Both, stoichiometric and hydrogenated sub-stoichiometric molybdenum oxide devices showed good resistive switching behavior. However, the fully-stoichiometric memristor exhibited better RS properties with endurance of 250 cycles, ON/OFF ratio ~ 103 and high retention of almost 3·104 s, compared with the poor RS behavior of the device based on the H-MoO3 − x film. This impressive memristive behavior could be attributed to the excess of oxygen vacancies in the case of fully-stoichiometric memristor in respect to the sub-stoichiometric H-MoO3 − x which play crucial role in the conductive behavior of the device. The high reproducibility observed in MoO3-based memristor highlights their potential for practical applications and scalability. Additionally, the outstanding features of the MoO3 memristor demonstrated through its long-term potentiation (LTP), long-term depression (LTD), and spike-timing dependent plasticity (STDP) indicate that the fully stoichiometric molybdenum oxide memristor has significant potential for simulating biological synapses, opening doors to a new era in neuromorphic computing applications.

Discover MaterialsVol. 5(1)
University of Patras (GR), Ajman University (AE), National Centre of Scientific Research "Demokritos" (GR), Institute of Informatics of the Slovak Academy of Sciences (SK)
Openalex Percentile: Top 61%
Advanced Memory and Neural Computing
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