2 research outputs found

    Genetic algorithm for optimizing Bragg and hybrid metal-dielectric reflectors

    Get PDF
    Highly efficient reflectors are in demand in the rapidly developing optoelectronics. At the moment, distributed Bragg reflectors made of semiconductor materials are mainly used in this capacity. A lot of time and financial resources are spent on their production. Reducing the thickness of the reflector while maintaining its reflectivity would make these devices more affordable and extend their lifetime by reducing thermal noise. With the help of genetic optimization algorithms, the structures of multilayer semiconductor and combined metal-semiconductor reflectors were obtained, having a smaller thickness and equal optical characteristics than those of classical analogues. In particular, a 29% reduction in the thickness of the silicon/silica Bragg reflector was achieved without compromising performance.The work has been supported by the Russian Science Foundation 21-12-00304. This work is financially supported by the Government of the Russian Federation (The federal academic leadership program Priority 2030)

    Genetic algorithm for optimizing Bragg and hybrid metal-dielectric reflectors

    No full text
    Highly efficient reflectors are in demand in the rapidly developing optoelectronics. At the moment, distributed Bragg reflectors made of semiconductor materials are mainly used in this capacity. A lot of time and financial resources are spent on their production. Reducing the thickness of the reflector while maintaining its reflectivity would make these devices more affordable and extend their lifetime by reducing thermal noise. With the help of genetic optimization algorithms, the structures of multilayer semiconductor and combined metal-semiconductor reflectors were obtained, having a smaller thickness and equal optical characteristics than those of classical analogues. In particular, a 29% reduction in the thickness of the silicon/silica Bragg reflector was achieved without compromising performance
    corecore