Oscillatory neural networks (ONNs) can handle image processing and combinational optimization problems with high biological plausibility. Coupled oscillators in ONNs mimic the neuronal oscillations and communication in the human brain. In this study, we demonstrate edge detection and graph coloring using a network of oscillatory neuromorphic devices comprising silicon nanosheet (NS)-gated diodes and series resistors. Silicon NS-gated diodes modulate the energy band structure in the channel through electrostatic doping, which tunes the amplitude and frequency of the oscillatory neuromorphic devices. Coupled oscillatory neuromorphic devices with capacitors can be in- or out-of-phase, enabling edge detection. Horizontal and vertical edge detections were performed using the coupling configuration. Furthermore, an ONN using oscillatory neuromorphic devices with resistive and capacitive couplings can solve graph coloring problems by representing the coloring solutions as phase differences. This study provides a method for achieving a compact silicon-based ONN that acts as a solver machine, as well as an image processor.

We synthesized thermoelectric nanocomposites by mixing HgSe nanoparticles (NPs) and Ag NPs in a solution and investigated the thermoelectric properties of the nanocomposite thin films on flexible plastic substrates. The X-ray diffraction patterns and the X-ray photoelectron spectra of the nanocomposites demonstrate that cation-exchange reactions occurred spontaneously in the mixed solution of HgSe and Ag NPs and that the HgSe NPs were completely converted to Ag₂Se when the Ag NP content was 20 vol.%. The maximum power factor and the thermoelectric figure of merit were obtained as 75 μW/mK² and 0.043 at 300 K, respectively, when the Ag NP content was 10 vol.%, which is 100 times higher than that of HgSe NP thin films. In addition, the mechanical stability of the thermoelectric nanocomposite film was confirmed through repeated bending tests.