Lowering Off Current in Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate)-Based Resistive Random Access Memory By Modulating Molecular Orientation and Doping Levels
Resistive random-access memory (RRAM) utilizing highly tunable organic materials, such as poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS), has attracted considerable interest for high-density scaling applications due to its simple two-terminal, sandwiched structure, which enables cost-effective integration with flexibility, biocompatibility, and transient functionalities. To extend organic RRAM into integrated circuits for neuromorphic computing, it is crucial to reduce power consumption, particularly by minimizing the off current (Ioff). However, Ioff in vertically stacked PEDOT:PSS-based RRAM remains relatively high due to its inherently high doping level and molecular alignment in the out-of-plane direction. Herein, we introduce a sequential treatment approach to modify the molecular orientation and doping level of PEDOT:PSS thin films by employing sorbitol and potassium hydroxide (KOH), respectively, to achieve reduced Ioff. We found that sorbitol addition hinders electrical conduction in the out-of-plane direction by flattening the PSS domains microscopically, while the subsequent KOH treatment effectively lowers the carrier concentration by dedoping PEDOT chains. As a result, Ioff at a read voltage of 100 mV was dramatically reduced from 1.57 × 10–3 (pristine PEDOT:PSS) to 3.20 × 10–8 A, a value lower than those previously reported. We believe that the methods presented in this work will contribute to future research on modifying the conduction properties of PEDOT and inspire further investigation into reducing Ioff in organic RRAM for practical applications.
Authors
- Yeon Jun Kim (ORCID: https://orcid.org/0000-0002-0325-3797)
- Jeonghun Kwak (ORCID: https://orcid.org/0000-0002-4037-8687)
- Jeong Han Song (ORCID: https://orcid.org/0009-0000-5628-7635)
- Yeunwoo Kwon
Institutions
- Seoul National University (KR)
Publication Details
- Journal
- ACS Applied Electronic Materials
- Published
- 2025-03-25
- DOI
- https://doi.org/10.1021/acsaelm.5c00176
- Citations
- 7
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 5.11
Funders
- National Research Foundation of Korea