Speaker
Description
Neuromorphic computing seeks to replicate the adaptive, parallel, and energy-efficient information processing of biological neural systems. Although existing hardware platforms have demonstrated important progress, many remain constrained by the complexity, size, and power demands of conventional transistor-based architectures. This has motivated the search for compact nanoscale devices capable of integrating memory, switching, and signal-processing functions within a single physical unit.
In this work, we demonstrate a hybrid photoactive nanodevice architecture designed as a functional building block for next-generation neuromorphic systems. The device exhibits light-responsive conductance modulation, non-volatile memory behaviour, and multi-level electronic states, making it well suited to emulate key synaptic operations such as learning, retention, decay, and reset. These characteristics position the device at the intersection of memristive behaviour and single-electron transistor (SET)-like functionality, offering a promising route toward highly compact and energy-efficient neuromorphic hardware.
A key feature of the platform is its ability to use optical stimuli as a control variable, enabling external tuning of device state through light exposure. Repeated illumination produces a persistent and cumulative electrical response, revealing a clear history-dependent memory effect analogous to synaptic potentiation in biological systems. The gradual evolution and retention of conductance states also support multi-valued logic and adaptive state encoding, both of which are highly desirable for artificial neural architectures.
Beyond synaptic emulation, the observed electronic behaviour suggests compatibility with room-temperature SET array concepts, where light may serve as a gating mechanism for controlling charge transport at the nanoscale. This introduces the possibility of hybrid computational platforms in which neuromorphic processing, optical programmability, and single-electron control are co-located within the same device framework.
Overall, this study highlights the potential of photoactive nanoscale devices as compact, multifunctional units for brain-inspired computing, with particular relevance to low-power neuromorphic circuits, adaptive memory systems, and future light-controlled nanoelectronic architectures.
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