ArticleAdvanced materials (Deerfield Beach, Fla.)2026
Revisiting Ferroelectric-Gated Phototransistors: A Tripartite Synapse-Inspired Approach to In-Sensor Image Processing.
Article in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Emerging Multimodal Artificial Sensory Fusion Paradigms Toward Advanced Embodied Intelligence.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Ferroelectric Devices for In-Memory and In-Sensor Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- An On-Demand Neuromorphic Vision System Enabled by a Multi-Paradigm Neuromorphic Device and Hierarchical Reconfigurability Designed from Device to System Level.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Revisiting Ferroelectric-Gated Phototransistors: A Tripartite Synapse-Inspired Approach to In-Sensor Image Processing.Advanced materials (Deerfield Beach, Fla.) · 2026Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Neuromorphic devices inspired by the tripartite synapse system offer enhanced modulation of synaptic weight via a third terminal. However, using an electrically independent terminal for memorizing and processing optical information remains unexplored. Here, a ferroelectric-gated phototransistor (FGPT) incorporating ferroelectric polymers and organic photoactive channels is revisited for neuromorphic vision systems. It is demonstrated that partial polarization switching in the ferroelectric gate insulator enables linear control of the photoactive channel. Furthermore, the photogating effect induced by charge trapping at the ferroelectric insulator/photoactive channel interface further enhances the photonic non-volatile (PNV) characteristics of the FGPT. This allows memorized visual information, expressed as photoconductance, to be incrementally potentiated or depressed. The modulated photoconductance fully spans the current level within the dynamic range of the device (153 dB). Finally, the feasibility of the device for all-day face recognition is shown by in-sensor processing of visual information obtained from unstructured environments into the pre-trained range. This approach results in up to a ≈40% improvement in recognition accuracy.
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Registered trials
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