Overall
- Language
- English
- Conflict of Interest
- In relation to this article, we declare that there is no conflict of interest.
- Publication history
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Received October 11, 2025
Revised October 27, 2025
Accepted October 30, 2025
Available online February 25, 2026
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Most Cited
Artificial Synaptic Devices Based on P-type and N-type Organic Materials for Advanced Neuromorphic Computing
https://doi.org/10.1007/s11814-025-00596-w
Abstract
Neuromorphic computing offers a promising alternative by mimicking the human brain, where memory and computation
are co-located. Artificial synaptic devices play a central role in this paradigm by emulating key brain-like functions such
as plasticity, learning, and signal modulation. While both inorganic and organic materials have been explored for such
devices, organic semiconductors are particularly attractive due to their low cost, mechanical flexibility, CMOS compatibility,
and biocompatibility. Among device structures, three-terminal configurations such as organic electrochemical transistors
(OECTs) and organic field-effect transistors (OFETs) allow for precise modulation of synaptic weights. Organic
semiconductors are generally categorized as p-type and n-type, each offering distinct charge transport characteristics
and processing advantages. Representative p-type materials include conjugated polymers such as poly(3-hexylthiophene)
(P3HT) and diketopyrrolopyrrole (DPP)-based polymers, whereas n-type semiconductors based on perylene or naphthalene
diimide derivatives have recently attracted attention despite their limited air stability. This review discusses both
p-type and n-type organic materials, their fabrication strategies, and their applications in artificial synaptic devices mimicking
brain, visual, tactile, and auditory functions, aiming to provide guidance for future advances in organic neuromorphic
technologies.

