Abstract
Conducting polymers are proving to be useful for construction of resistive switching devices. This work reports the fabrication of a resistive switching device using Magnetite-Polyaniline (Fe3O4-PANI) nanocomposite. The device showed good non-volatile memory properties and can mimic neuromorphic synaptic behavior. Initially, Fe3O4 nanoparticles were synthesized using the co-precipitation method and PANI by oxidative polymerization and their nanocomposites of different compositions were prepared and fully characterized. The 10% Fe3O4-PANI-based RS device outperforms all others in terms of I–V switching performance. Furthermore, the optimized device (10% Fe3O4-PANI) has tuneable I–V characteristics. The device demonstrated excellent analog switching at ± 1.5 V and digital switching at ± 2.5 V. The memristive behavior of the Ag/10% Fe3O4-PANI/FTO device was confirmed by the pinched hysteresis loop in the I–V curves at different voltages, as well as the double-valued charged-flux characteristics. The device has good cycle-to-cycle reliability for switching voltages and switching currents, as demonstrated by the Weibull distribution and other statistical measures. Moreover, the device can retain memory states up to 6 × 103 s and shows a switching stability of 2 × 104 cycles. The device also showed linear potentiation and depression characteristics and mimicked excitatory post-synaptic current (EPSC) and paired-pulse facilitation (PPF) index properties similar to its biological counterpart. According to the charge transport model fitting results, the Ohmic and Child’s square laws dominated in both analog and digital switching processes, and RS occurs due to the filamentary process.
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IUS: Investigation; Methodology & Writing—original draft SLP: Investigation; Methodology & Writing—original draft SAJ: Visualization; Resources; Writing—review & editing; Supervision TDD: Resources; Writing—review & editing, Supervision RKK: Resources.
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Shah, I.U., Patil, S.L., Jadhav, S.A. et al. Magnetite–Polyaniline Nanocomposite for Non-Volatile Memory and Neuromorphic Computing Applications. Electron. Mater. Lett. (2024). https://doi.org/10.1007/s13391-024-00495-y
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DOI: https://doi.org/10.1007/s13391-024-00495-y