High performance memristor device from solution processed MnO2 nanowires: Tuning of resistive switching from analog to digital and underlying mechanism
This study reports the synthesis of manganese dioxide (MnO 2 ) nanowires via the hydrothermal method and the fabrication of high-performance memristor devices using solution-processed MnO 2 nanowires. Microstructural characterizations, viz , XRD, SEM, EDAX and XPS of synthesized sample revealed highly crystalline structures of MnO 2 nanowires. As synthesized MnO 2 nanowires, mixed in different weight percentages with poly(methyl methacrylate) (PMMA) solution were deposited on Al electrode to form thin film memristor devices. Resistive switching with both analog and digital behaviors have been realized in Al/MnO 2 -PMMA/Al device by controlling the weight percentage (wt %) of MnO 2 in the composite. When the MnO 2 wt % in the composite was low (PMMA: MnO 2 = 1:1), the device exhibited analog type switching, while, the higher concentration of MnO 2 produced digital types of switching. The On/Off current ratio of the device increased gradually with increase in MnO 2 wt %, reaching the highest switching ratio, ca. 10 6 and excellent endurance (>10 4 s) for PMMA:MnO 2 = 1:8. Temperature dependent charge transport behavior and impedance spectroscopy was further carried out to explain the underlying resistive switching mechanism of the device. • Solution processed α-MnO2 nanowires/PMMA composite act as resistive memory layer. • Tuning from analog to digital behavior in bipolar resistive switching is accomplished. • MnO 2 wt% in PMMA matrix controls device performances. • High On/Off current ratio (10 6 ) and low operating voltage (1 V) is achieved in the device. • Formation and rupture of oxygen vacancies drive resistive switching.
Authors
- Biswanath Mukherjee (ORCID: https://orcid.org/0000-0001-6140-6088)
- Rajkumar Mandal
- Arka Mandal
- Rajib Nath (ORCID: https://orcid.org/0000-0002-3781-6906)
- Nayan Pandit
Institutions
- Sidho-Kanho-Birsha University (IN)
Publication Details
- Journal
- Memories - Materials Devices Circuits and Systems
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1016/j.memori.2024.100120
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.21