The priority of synaptic device researches has been given to prove the device potential for the emulation of synaptic dynamics and not to functionalize further synaptic devices for more complex learning. Here, we demonstrate an optic-neural synaptic device by implementing synaptic and optical-sensing functions together on h-BN/WSe2 heterostructure. This device mimics the colored and color-mixed pattern recognition capabilities of the human vision system when arranged in an optic-neural network. Our synaptic device demonstrates a close to linear weight update trajectory while providing a large number of stable conduction states with less than 1% variation per state. The device operates with low voltage spikes of 0.3 V and consumes only 66 fJ per spike. This consequently facilitates the demonstration of accurate and energy efficient colored and color-mixed pattern recognition. The work will be an important step toward neural networks that comprise neural sensing and training functions for more complex pattern recognition.

A high-performance ReS2 -based thin-film transistor and photodetector with high on/off-current ratio (10(4) ), high mobility (7.6 cm(2) V(-1) s(-1) ), high photoresponsivity (2.5 × 10(7) A W(-1) ), and fast temporal response (rising and decaying time of 670 ms and 5.6 s, respectively) through O2 plasma treatment is reported.

The effects of triphenylphosphine (PPh3 )-based n-doping and hexagonal boron nitride (h-BN) insertion on a tungsten diselenide (WSe2 ) photodetector are systematically studied, and a very high performance WSe2 /h-BN heterostucture-based photodetector is demonstrated with a record photoresponsivity (1.27 × 10(6) A W(-1) ) and temporal photoresponse (rise time: 2.8 ms, decay time: 20.8 ms) under 520 nm wavelength and 5 pW power laser illumination.

Coexistence of threshold and memory switching characteristics of ALD HfO₂ memristor synaptic arrays for energy-efficient neuromorphic computing.

No abstract