Design of multilayer antireflection coatings made from co-sputtered and low-refractive-index materials by genetic algorithm

Martin F Schubert,E Fred Schubert,David J Poxson,Jong Kyu Kim,Sameer Chhajed,Frank W Mont

doi:10.1364/oe.16.005290

Abstract

Designs of multilayer antireflection coatings made from co-sputtered and low-refractive-index materials are optimized using a genetic algorithm. Co-sputtered and low-refractive-index materials allow the fine-tuning of refractive index, which is required to achieve optimum anti-reflection characteristics. The algorithm minimizes reflection over a wide range of wavelengths and incident angles, and includes material dispersion. Designs of antireflection coatings for silicon-based image sensors and solar cells, as well as triple-junction GaInP/GaAs/Ge solar cells are presented, and are shown to have significant performance advantages over conventional coatings. Nano-porous low-refractive-index layers are found to comprise generally half of the layers in an optimized antireflection coating, which underscores the importance of nano-porous layers for high-performance broadband and omnidirectional antireflection coatings.

Highlights

Minimizing optical reflection at dielectric interfaces is a fundamental challenge, and is vital for many applications in optics
A material with the required refractive index may not exist, and omni-directional and broadband antireflection characteristics are often required for applications such as solar cells or image sensors
Several methods exist that allow the tuning of refractive index for optical thin films

Summary

Introduction

Minimizing optical reflection at dielectric interfaces is a fundamental challenge, and is vital for many applications in optics. Well-known refractive index profiles for antireflection coatings include the quintic or modified-quintic profiles, which are continuous functions that vary between the substrate refractive index and the index of the ambient material [5,6]. These profiles do not give the optimum profile when a finite number of layers is used. The parameter space generally includes many local minima, which makes deterministic optimization schemes that find the local minima unsuitable [7] To meet these challenges, genetic algorithms have previously been applied in order to optimize a variety of optical coatings [7,8,9,10]. The calculations consider coatings composed of co-sputtered and low-n materials and take material dispersion into account

Numerical approach

Silicon image sensor

Silicon solar cell

Findings

Conclusion