Ferroelectric polymer mediated bipolar memristive switching in reduced graphene oxide nanocomposite device
Two-terminal energy-efficient resistive random-access memory (RRAM) devices are key enablers for modern electronic technologies. Graphene based materials have drawn promising attention recently in scientific community due to its phenomenal attributes in electronic memory devices. In this study, graphene oxide (GO) and reduced graphene oxide (rGO) reinforced poly (vinylidene fluoride) (PVDF) nanocomposites were synthesized to develop hybrid memristive devices with tunable electrical characteristics for bipolar switching RRAM technology. Structural, morphological, and spectroscopic analyses confirmed the successful reduction of GO to rGO and its uniform dispersion within the PVDF matrix. Raman, XRD, and FESEM studies revealed strong interfacial coupling between rGO and PVDF, enhancing β-phase crystallinity and improving charge transport pathways. All the fabricated devices exhibited distinct bipolar resistive switching (RS) behaviour. While both GO + PVDF (GPV) and rGO + PVDF (RPV) devices showed non-volatile memory characteristics, the RPV device demonstrated improved performance with a high ON/OFF ratio (∼10 4 ), low switching voltage (−0.30/0.18V), good endurance (>10 2 ), and stable retention over multiple cycles (>10 3 ). The conduction mechanisms, analyzed using double logarithmic I-V characteristics, indicated a transition from Ohmic to space-charge-limited conduction (SCLC) in the high resistance state (HRS) while data fitting to a SPICE based analytical model shows that the HRS region fits a double-exponential function, indicating that current in this range is dominated by the diffusion mechanism as well as recombination current. The device primarily exhibits digital non-volatile resistive switching. Importantly, the digital resistive switching behavior observed in the RPV devices establishes the rGO + PVDF nanocomposite as a promising candidate for potential application in modern electronic devices owing to its excellent uniformity, low power consumption, good endurance, and stable retention characteristics.
Authors
- Himangshu Jyoti Gogoi (ORCID: https://orcid.org/0000-0003-1158-6994)
- Nipom Sekhar Das (ORCID: https://orcid.org/0000-0001-6434-8223)
- Tanmay Dutta (ORCID: https://orcid.org/0000-0002-6637-5185)
Institutions
- Indian Institute of Technology Guwahati (IN)
- Assam Agricultural University (IN)
Publication Details
- Journal
- Materials Science in Semiconductor Processing
- Published
- 2026-10-06
- DOI
- https://doi.org/10.1016/j.mssp.2026.111215
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00