A novel ultracompact 2/spl times/2 wavelength division multiplexer (WDM) for 1.55-/spl mu/m operation based on highly dispersive two-mode interference (TMI) was designed, theoretically modeled, and verified using a finite-difference-time-domain (FDTD) method. A two-moded waveguide assisted with a dispersive tooth-shaped grating provided a mode-dependent reflection band of central wavelength at 1.55 /spl mu/m. The wavelengths of 1538 and 1572 nm that were at the band edges and had the lowest reflection losses and relatively high dispersion were selected for wavelength multiplexing. The result showed that the wavelengths were separated by grating dispersion in a coupler length of 75 /spl mu/m which was much shorter than the required length of 1.1 mm in a regular TMI multiplexer of no grating. Insertion loss of about 1.7 dB and channel contrast of about 12 dB were achieved. 相似文献
Graphdiyne (GDY) is emerging as a promising material for various applications owing to its unique structure and fascinating properties. However, the application of GDY in electronics and optoelectronics are still in its infancy, primarily owing to the huge challenge in the synthesis of large-area and uniform GDY film for scalable applications. Here a modified van der Waals epitaxy strategy is proposed to synthesize wafer-scale GDY film with high uniformity and controllable thickness directly on graphene (Gr) surface, providing an ideal platform to construct large-scale GDY/Gr-based optoelectronic synapse array. Essential synaptic behaviors have been realized, and the linear and symmetric conductance-update characteristics facilitate the implementation of neuromorphic computing for image recognition with high accuracy and strong fault tolerance. Logic functions including “NAND” and “NOR” are integrated into the synapse which can be executed in an optical pathway. Moreover, a visible information sensing-memory-processing system is constructed to execute real-time image acquisition, in situ image memorization and distinction tasks, avoiding the time latency and energy consumption caused by data conversion and transmission in conventional visual systems. These results highlight the potential of GDY in applications of neuromorphic computing and artificial visual systems.
