Computational design and optimization of nanostructured AlN deep-UV grating reflectors

Area of Science:

• Materials Science
• Optoelectronics
• Nanotechnology

Background:

• Deep-ultraviolet (DUV) optoelectronics face challenges in wall-plug efficiency, necessitating advanced light management techniques.
• Current DUV systems require improved light collimation and extraction for enhanced performance.

Purpose of the Study:

• To computationally investigate AlN-based periodic nanostructures for intense, wavelength-tunable DUV reflection.
• To identify suitable low-index underlayers and analyze optical resonance mechanisms in AlN/MgF2 nanostructures.
• To establish a rational design space for optimizing DUV reflectors across a broad wavelength range.

Main Methods:

• Computational survey of material limitations for DUV reflection.
• Analysis of optical resonances (Fano modes, Mie-like dipole resonances) in AlN/MgF2 nanostructures by varying geometric parameters.
• Development of a thickness-to-pitch ratio (TPR) parameter to characterize reflectance behavior.
• Optimization of TPR for DUV wavelengths (200-320 nm).

Main Results:

• MgF2 identified as a suitable low-index underlayer material.
• Optical resonances were categorized and linked to specific geometric parameters and resonant mechanisms.
• A nearly wavelength-invariant behavior was observed, related to the TPR parameter.
• Achieved maximum reflectance of 85% at 211 nm and >97% at 320 nm.

Conclusions:

• AlN-based periodic nanostructures offer a viable route to high-performance DUV reflectors.
• The developed TPR parameter provides a rational design approach for tunable DUV optics.
• These findings pave the way for improved efficiency in DUV optoelectronic devices.