Highly Stable, Low-Energy-Consumption Block Copolymer Optoelectronic Synaptic Devices Prepared by Vertical Phase Separation
Organic synaptic devices with environmental stability are important for the development of smart electronic systems. However, there are challenges in preparing air-stable synaptic devices due to the sensitivity of organic semiconductors to moisture and oxygen. Here, poly(3-hexylthiophene)-<i>block</i>-poly(phenyl isocyanide) with pentafluorophenyl ester (P3HT-<i>b</i>-PPI(5F)), which combines both carrier transport and charge trapping functions, was selected to be blended with poly(methyl methacrylate) (PMMA) to prepare synaptic devices. Vertical phase separation was generated after deposition of the blended solution, enabling one-step preparation of the active and encapsulated layers of the device. P3HT-<i>b</i>-PPI(5F) and PMMA are the device active layer and encapsulation layer, respectively. The synaptic device has high stability, with the postsynaptic current remaining above 90% after 2 weeks in air. Basic synaptic behavior was successfully simulated under green light stimulation. The energy consumption of a single synaptic event can be as low as 0.6 fJ after reducing the operating voltage. Further, high-pass filtering and optical decoding of "Morse code" were simulated. In addition, biomimetic visual learning and forgetting behaviors were simulated. This work demonstrates a method for preparing air-stable synaptic devices with potential applications in the field of bionic electronics.
Authors
- Shan Wu (ORCID: https://orcid.org/0000-0001-9935-0657)
- Yucong Bao
- X. Wang
- Longlong Jiang
- Longzhen Qiu
- Fan Ni
- Zixiang Lu
Institutions
- Fuyang Normal University (CN)
- Anhui University (CN)
- Hefei University of Technology (CN)
- Anhui East China Institute of Optoelectronic Technology (China) (CN)
Publication Details
- Journal
- The Journal of Physical Chemistry Letters
- Published
- 2026-01-23
- DOI
- https://doi.org/10.1021/acs.jpclett.5c03590
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00