No abstract

Metamaterial absorbers have attracted considerable attention for applications in the terahertz range. In this Letter, we report the design, fabrication, and characterization of a terahertz dual band metamaterial absorber that shows two distinct absorption peaks with high absorption. By manipulating the periodic patterned structures as well as the dielectric layer thickness of the metal-dielectric-metal structure, significantly high absorption can be obtained at specific resonance frequencies. Finite-difference time-domain modeling is used to design the structure of the absorber. The fabricated devices have been characterized using a Fourier transform IR spectrometer. The experimental results show two distinct absorption peaks at 2.7 and 5:2 THz, which are in good agreement with the simulation. The absorption magnitudes at 2.7 and 5:2 THz are 0.68 and 0.74, respectively.

We present the simulation, implementation, and measurement of a polarization insensitive broadband resonant terahertz metamaterial absorber. By stacking metal-insulator layers with differing structural dimensions, three closely positioned resonant peaks are merged into one broadband absorption spectrum. Greater than 60% absorption is obtained across a frequency range of 1.86 THz where the central resonance frequency is 5 THz. The FWHM of the device is 48%, which is two and half times greater than the FWHM of a single layer structure. Such metamaterials are promising candidates as absorbing elements for bolometric terahertz imaging.

Prognostic performance evaluation has gained significant attention in the past few years.*Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.