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Long-afterglow light-emitting transistors (LALETs) represent an efficient platform for neuromorphic computing by integrating in-memory processing, optical output, and noise-filtering functionality within a single device. Here, we have synthesized a series of donor–acceptor (D–A) conjugated copolymers comprising a diketopyrrolopyrrole (DPP) acceptor and oligo-thiophene (T) donors of tunable length to investigate the impact of charge-transport polarity on LALET performance. By terpolymerization, the D:A ratio was adjusted from 4:1 to 6:1, 8:1, and 12:1, yielding DPP4T, DPP6T, DPP8T, and DPP12T copolymers, respectively. Among them, DPP8T exhibited a favorable combination of high hole mobility (0.42 cm2 V–1 s–1) and strongly suppressed electron mobility, enabling high electroluminescence of 1189 cd m–2 while maintaining programming currents below 10 μA. The resulting LALET displayed dual operation mode, long-afterglow, and click-on upon employing the opposite gate stimuli. In long-afterglow mode, both electrical and optical postsynaptic signals enabled reservoir computing system with Fashion-MNIST recognition accuracies exceeding 90%. Furthermore, the intrinsic noise-filtering function of LALET emulated neuronal all-or-none firing, allowing a neuromorphic optocoupler to implement complex “stimulus-computing-decision-action” logic and to be used as the output layer for a reservoir computing framework toward a noise-filtering display. These results highlight the importance of the chemical modulation of the polarity in charge transport for high-performance neuromorphic devices.
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Chen et al. (2026) studied this question.
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