By Balamati Choudhury, Arya Menon, Rakesh Mohan Jha
This e-book describes a metamaterial-based energetic absorber for strength biomedical engineering functions. Terahertz (THz) spectroscopy is a vital software for imaging within the box of biomedical engineering, end result of the non-invasive, non-ionizing nature of terahertz radiation coupled with its propagation features in water, which permits the operator to acquire high-contrast photographs of dermis cancers, burns, and so forth. with no hazardous results. for you to faucet this large strength, you will need to construct hugely effective biomedical imaging structures through introducing terahertz absorbers into biomedical detectors. the largest problem confronted within the fulfilment of this target is the shortcoming of certainly taking place dielectrics, that is triumph over with using artificially engineered resonant fabrics, viz. metamaterials. This booklet describes this type of metamaterial-based lively absorber. The layout has been optimized utilizing particle swarm optimization (PSO), finally leading to an ultra-thin energetic terahertz absorber. The absorber indicates close to harmony absorption for a tuning variety of terahertz (THz) application.
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Extra resources for Active Terahertz Metamaterial for Biomedical Applications
14 Multi-band metamaterial absorber Table 3 Dimensions of multi-band absorber (Fig. 018 A Matlab code was written in order to calculate Eq. (8) at different frequencies, and the absorption characteristics of the multi-band absorber was plotted as given in Fig. 15. 25 GHz is due to the three different square rings, and near unity absorption was observed at these three frequencies as shown in Fig. 15. The electric ﬁeld intensities at the three different frequencies were respectively plotted for each as shown in Fig.
8 THz. The angles of rotation for various frequencies can be obtained using the PSO computational engine and stored as a database into the memory of a micro-controller in an active absorber array system. The absorber array can then be controlled from the processor for the resonance at the desired frequency. This concept would form the basis of the adaptive array and is depicted pictorially in Fig. 28. Sensitivity Analysis: The output of the PSO computational engine (while determining the optimal dimensions) is highly accurate real numbers with the fractional part extending up to the fourth decimal.
Guodos and Sahalos (2006) designed and optimized multi-layer planar absorptive coatings using multi-objective particle swarm optimization (MOPSO). The designed coating showed wide band and wide angle characteristics. Further, a comparison between MOPSO and multi-objective GA revealed that MOPSO was more efﬁcient and required lesser computing time. Therefore, it is well established that soft computing can be used as an effective tool for electromagnetic designs. As mentioned above, compared to conventional soft computing techniques like neural networks and genetic algorithm, PSO is found to require lesser memory, is simple and efﬁcient, and has inherent techniques to prevent the algorithm from falling into a local minimum.