Preparation and Characterization of WORM Resistive Memory Switching Using an Organic Dye Trypan Blue (TB) and Its Application to Study Synaptic Behavior for Neuromorphic Computation
This study presents a detailed investigation of the write-once-read-many (WORM) resistive switching characteristics observed in thin films of Trypan Blue (TB), a commercial organic dye. These characteristics were consistently observed under both positive and negative voltage sweep polarities. A theoretical model, based on the relative alignment of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels of the Trypan Blue active layer with the work functions of the top (Au) and bottom (indium tin oxide (ITO)) electrodes, has been proposed to elucidate the WORM behavior. The fabricated device demonstrated robust performance metrics, including a large memory window (on/off ratio), decent data retention lifetime, and high endurance. Furthermore, the potential for neuromorphic applications was explored by investigating the device’s capacity to emulate fundamental synaptic functionalities, such as the learning (potentiation) and forgetting (depression) processes. Such synaptic emulation through WORM-type resistive switching is one of the very few findings to date. The artificial synaptic plasticity was systematically examined by modulating key parameters of the input voltage pulses, including their amplitude, width, and interval. The collective results strongly indicate that this Trypan Blue-based WORM resistive memory device holds significant promise as a foundational component for advanced neuromorphic computing systems.
Authors
- Syed Arshad Hussain (ORCID: https://orcid.org/0000-0002-3298-6260)
- K. Naha
- Debajyoti Bhattacharjee (ORCID: https://orcid.org/0000-0003-2105-1889)
- Shirsendu Das (ORCID: https://orcid.org/0000-0002-6000-675X)
Institutions
- Tripura University (IN)
Publication Details
- Journal
- ACS Applied Electronic Materials
- Published
- 2025-11-11
- DOI
- https://doi.org/10.1021/acsaelm.5c01886
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00