Engineering the Complex-Valued Constitutive Parameters of Metamaterials for Perfect Absorption

被引:7
|
作者
Wang, Pengwei [1 ]
Chen, Naibo [1 ]
Tang, Chaojun [1 ]
Chen, Jing [2 ,3 ]
Liu, Fanxin [1 ,3 ]
Sheng, Saiqian [1 ]
Yan, Bo [1 ]
Sui, Chenghua [1 ]
机构
[1] Zhejiang Univ Technol, Dept Appl Phys, Ctr Opt & Optoelect Res, Hangzhou 310023, Zhejiang, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Coll Elect Sci & Engn, Nanjing 210023, Jiangsu, Peoples R China
[3] Nanjing Univ, Natl Lab Solid State Microstruct, Nanjing 210093, Jiangsu, Peoples R China
来源
基金
高等学校博士学科点专项科研基金; 中国国家自然科学基金;
关键词
Metamaterials; Perfect absorbers; Anti-reflection coating; Light harvesting; OPTICAL METAMATERIALS; PLASMONIC SENSOR; LIGHT-ABSORPTION; SOLAR-CELLS; ABSORBER; BAND; MULTIBAND; DESIGN; BROAD; INTERFERENCE;
D O I
10.1186/s11671-017-2048-2
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
We theoretically studied how to directly engineer the constitutive parameters of metamaterials for perfect absorbers of electromagnetic waves. As an example, we numerically investigated the necessary refractive index n and extinction coefficient k and the relative permittivity epsilon and permeability mu of a metamaterial anti-reflection layer, which could cancel the reflection from a hydrogenated amorphous silicon (alpha-Si:H) thin film on a metal substrate, within the visible wavelength range from 300 to 800 nm. We found that the metamaterial anti-reflection layer should have a negative refractive index (n < 0) for short-wavelength visible light but have a positive refractive index (n > 0) for long-wavelength visible light. The relative permittivity epsilon and permeability mu could be fitted by the Lorentz model, which exhibited electric and magnetic resonances, respectively.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Engineering the Complex-Valued Constitutive Parameters of Metamaterials for Perfect Absorption
    Pengwei Wang
    Naibo Chen
    Chaojun Tang
    Jing Chen
    Fanxin Liu
    Saiqian Sheng
    Bo Yan
    Chenghua Sui
    Nanoscale Research Letters, 2017, 12
  • [2] Redundancy of the parameters of the complex-valued neural network
    Nitta, T
    NEUROCOMPUTING, 2002, 49 : 423 - 428
  • [3] ESTIMATING THE PARAMETERS OF COMPLEX-VALUED EXPONENTIAL SIGNALS
    KUNDU, D
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 1994, 18 (05) : 525 - 534
  • [4] Is a Complex-Valued Stepsize Advantageous in Complex-Valued Gradient Learning Algorithms?
    Zhang, Huisheng
    Mandic, Danilo P.
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 27 (12) : 2730 - 2735
  • [5] Prediction of Complex-Valued Signals by Using Complex-Valued LMK Algorithm
    Menguc, Engin Cemal
    Acir, Nurettin
    2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2017,
  • [6] Nonlinear adaptive prediction of complex-valued signals by complex-valued PRNN
    Goh, SL
    Mandic, DP
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2005, 53 (05) : 1827 - 1836
  • [7] Complex-Valued Neural Network and Complex-Valued Backpropagation Learning Algorithm
    Nitta, Tohru
    ADVANCES IN IMAGING AND ELECTRON PHYSICS, VOL 152, 2008, 152 : 153 - 220
  • [8] Complex-valued tapers
    Politis, DN
    IEEE SIGNAL PROCESSING LETTERS, 2005, 12 (07) : 512 - 515
  • [9] Complex-valued autoencoders
    Baldi, Pierre
    Lu, Zhiqin
    NEURAL NETWORKS, 2012, 33 : 136 - 147
  • [10] Novel complex-valued neural network for dynamic complex-valued matrix inversion
    Liao B.
    Xiao L.
    Jin J.
    Ding L.
    Liu M.
    2016, Fuji Technology Press (20) : 132 - 138