Data analysis on the three defect wavelengths of a MoS-based defective photonic crystal using machine learning.

To reduce the dimension of optoelectronic devices, recently, Molybdenum disulfide (MoS) monolayers with direct bandgap in the visible range are widely used in designing a variety of photonic devices. In these applications, adjustability of the working wavelength and bandwidth with optimum absorption value plays an important role. This work proposes a symmetric defective photonic crystal with three defects containing MoS monolayer to achieve triple narrowband defect modes with wavelength adjustability throughout the Photonic Band Gap (PBG) region, 560 to 680 nm.