Development of Organic-Inorganic Tandem Resistive Random Access Memory for Biodegradable Electronics
Abstract This work investigates resistive switching in chitosan-based ReRAM devices using single-layer and bilayer structures incorporating SiO2, ZnO, and TiO2 for the resistive random access memory (ReRAM) and non-volatile memory applications. The single chitosan device exhibits bipolar switching with ohmic conduction at low voltages and transitions to a low-resistance state consistent with conductive filament formation under positive bias, while bilayers show signatures of space-charge-limited current (SCLC) with trap participation, depending on the oxide layer and morphology. Within the present dataset, devices demonstrate repeatable switching over multiple cycles with ON/OFF resistance ratios extracted at a fixed read voltage, comprehensive long-term endurance and retention are identified as future work. The material composition influences switching thresholds and stability via trap distributions and surface roughness, suggesting routes to optimize hybrid organic–inorganic stacks for sustainable electronics. Recent advances in biodegradable resistive memories further motivate such hybrid approaches for eco-friendly and neuromorphic applications, while emphasizing the need for standardized reliability testing in subsequent studies.
Authors
- Bhekie B. Mamba (ORCID: https://orcid.org/0000-0003-2534-2579)
- Tebogo Sfiso Mahule (ORCID: https://orcid.org/0000-0001-6387-8169)
- Nandu B. Chaure (ORCID: https://orcid.org/0000-0002-4134-5019)
- Fhulufhelo Nemangwele (ORCID: https://orcid.org/0000-0003-2008-5833)
- Sachin V. Desarada (ORCID: https://orcid.org/0000-0003-1243-6517)
- Patrice Umenne (ORCID: https://orcid.org/0000-0001-5911-6073)
- S. Vallabhpurapu
- Thabo Mdletshe
- Vijaya Vallabhpurapu
Institutions
- University of South Africa (ZA)
- University of Venda (ZA)
- Savitribai Phule Pune University (IN)
Publication Details
- Journal
- Transactions on Electrical and Electronic Materials
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1007/s42341-025-00681-1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of South Africa