Metamaterial for Microwave Applications

Description

Metamaterials are geometrically patterned new materials that are arranged in periodic way on top of dielectric substrates to exhibit properties unobtainable naturally. This book discusses artificially engineered structures for the development of metamaterials and meta surfaces in the advancement of microwave sensors in sensing technology, non-invasive microwave-based imaging system, antenna performance improvement with miniaturization, flexible materials for microwave applications and finally metamaterials in antennas for its use in nanosatellites. The book serves as a reference for designing industrial applications of metamaterials in 5G wireless communication system and healthcare technology using metamaterials and meta surfaces. This well illustrated book will be a useful resource for students, engineers, physicists, and other researchers for various microwave applications. It provides newcomers with fundamental knowledge of metamaterials and their prospective applications. The researchers will benefit from thought-provoking perspectives that will enhance their knowledge and steer them to modern day innovation. Cover Title Page Copyright Page Preface Acknowledgements Table of Contents 1. Metamaterial and Sensing 1.1 Introduction 1.2 Concept of metamaterial & microwave sensing 1.3 Metamaterial based microwave sensor design Principle: resonator structure 1.4 Geometry design, fabrication and performances 1.5 Measurement method for metamaterial properties assessment 1.6 Metamaterial based microwave sensor design Principle: sandwich structure 1.7 Unit cell design with circuit modelling and performance 1.8 Sensitivity performance with absorption and polarization affects 1.9 Stacked DNG metamaterial for biosensing 1.10 Stacked DNG MTM scattering parameters and dielectric characteristics 1.11 Blood glutamate concentration sensing performance of the MTM unit cell 1.12 Summary 2. Liquid and Solid Material Sensing Using Metamaterial 2.1 Introduction 2.2 Metamaterials and microwave sensing 2.3 Importance of metamaterial sensor 2.4 Tri Circle SRR (TCSRR) shape metamaterial sensor design and analysis 2.5 Electric field and surface current distribution investigation 2.6 Double negative (DNG) metamaterial characteristics investigation 2.7 Parametric study 2.8 Mathematical modelling of the TCSRR based metamaterial sensor 2.9 Sensing performance evaluation 2.9.1 Dielectric constant investigation of oil samples 2.9.2 Loss tangent analysis of oil samples 2.9.3 Detection and evaluation of different LUTS using TCSRR structure 2.10 Design and analysis of complementary square SRR-based metamaterial 2.11 Effective parameters extraction methods 2.11.1 Metamaterial characteristics of the designed unit cell 2.11.2 Surface current, E-field, and H-field analysis 2.12 Equivalent circuit analysis 2.13 Parametric analysis 2.13.1 Effect of change of split gap 2.13.2 Effect of change of resonator width 2.13.3 Effect of change of substrate material 2.13.4 Metamaterial structure fabrication and experimental results analysis 2.13.5 Effective medium ratio (EMR) analysis 2.14 Materials and thickness sensing using the proposed sensor 2.14.1 Quality factor and sensitivity analysis 2.15 Summary 3. Metamaterial for Future Generation Wireless Communications 3.1 Introduction 3.2 Metamaterial’s background 3.3 Metamaterial based mm-wave 3.4 Metamaterial particle design 3.4.1 Principle of metamaterial working 3.4.2 Metamaterial properties extraction 3.5 Metamaterial based Sub 6 GHz 3.5.1 Metamaterial example 3.6 Analysis, design and simulation of 5G metamaterial 3.7 Emerging metamaterial applications 3.7.1 Antennas - gain improving 3.7.2 Miniaturizing of the size of antennas 3.7.3 Antenna’s bandwidth enhancement 3.7.4 Metamaterials for multiband generation 3.7.5 Metasurface 3.8 Summary of existing research related to DNG metamaterial 3.9 Summary 4. Metamaterial Structure Exploration for Wireless Communications 4.1 Introduction 4.2 Metamaterial with asymmetrical resonator 4.3 Metamaterial with single axis symmetric resonator with applications 4.3.1 Design of MTM unit cell 4.3.2 Result analysis of the metamaterial 4.3.3 Application of metamaterial in antenna for performance enhancement 4.3.4 Application of the metamaterial as an absorber 4.4 Two axes symmetric metamaterial and it’s application 4.4.1 MTM design and result analysis 4.4.2 Antenna gain enhancement using MTM superstrate 4.5 Mirror symmetric resonator based tuned metamaterial 4.5.1 Design of the metamaterial 4.5.2 Frequency tuning of the metamaterial 4.6 Rotating symmetric resonator based metamaterial absorber 4.6.1 Metamaterial absorber (MMA) design 4.6.2 Frequency tuning of the MMA 4.6.3 Metamaterial property analysis of the MMA 4.6.4 Power and current distribution analysis of MMA 4.6.5 Angular stability and polarization insensitivity study of MMA 4.6.6 Experimental result of the MMA 4.7 Summary 5. Metamaterial Antennas for Ultra-wideband Applications 5.1 Introduction 5.2 Metamaterial and UWB antennas 5.2.1 Metamaterials 5.2.2 Ultra wideband (UWB) technology 5.3 Metamaterial based antenna design 5.3.1 Unit cell configuration 5.3.2 Antenna geometry 5.3.3 Experimental validation 5.3.4 Surface current distribution 5.3.5 Time domain performance 5.4 Summary 6. Flexible Metamaterials for Microwave Application 6.1 Introduction 6.2 Importance of flexible substrate materials for microwave application 6.3 Development of flexible substrate material 6.3.1 Synthesis of MgxZn(1–x)Fe2O4 nanoparticles 6.4 Characterization of MgxZn(1–x)Fe2O4 nanoparticles 6.4.1 Structural analysis 6.4.2 Morphological analysis 6.4.3 Dielectric properties analysis 6.4.4 Optical and photoluminescence analysis 6.4.5 Magnetic properties analysis 6.5 Flexible metamaterial design technique 6.5.1 Metamaterials on MgxZn(1–x)Fe2O4 nanoparticles-based flexible substrate 6.5.2 Metamaterial measurement method 6.5.3 Performance of flexible metamaterial with MgxZn(1–x)Fe2O4 nanoparticles with Mg40 6.5.4 Electromagnetic properties analysis of the flexible metamaterial with Mg40 6.5.5 Electromagnetic field interaction of the metamaterial properties with Mg40 6.5.6 Performance analysis of flexible metamaterial properties with Mg60 6.5.7 Comparison of MgxZn(1–x)Fe2O4 nanoparticles-based proposed flexible metamaterials with Mg40 and Mg60 6.5.8 Comparison of MgxZn(1–x)Fe2O4 nanoparticles-based proposed flexible metamaterials with existing metamaterials 6.6 Summary 7. Microwave Head Imaging and 3D Metamaterial-inspired Antenna 7.1 Introduction 7.2 CCSRR based metamaterial structure design 7.2.1 Design and analysis of CCSRR unit cell structure 7.2.2 Effective medium parameters of CCSRR unit cell 7.2.3 Equivalent circuit model of CCSRR unit cell structure 7.2.4 Parametric study of CCSRR unit cell structure 7.2.5 Design and analysis of CCSRR loaded 3D antenna 7.2.6 Mathematical modeling of the CCSRR loaded 3D antenna 7.2.7 Parametric study of CCSRR loaded 3D antenna 7.2.8 Antenna fabrication and measurement 7.2.9 Head phantom fabrication and measurements 7.2.10 Preparation and fabrication of tissue mimicking head phantom 7.2.11 Electrical properties measurement technique 7.3 EM head imaging system 7.3.1 Imaging setup with nine antennas 7.3.2 Antenna phase center optimization 7.4 Image reconstruction technique 7.4.1 IC-CF-DMAS image reconstruction algorithm 7.4.2 Matching medium consideration 7.4.3 Internet of things framework for em head imaging system 7.5 CCSRR loaded 3D antenna with head model 7.5.1 Specific absorption rate (SAR) analysis 7.5.2 SAR analysis of CCSRR loaded 3D antenna 7.5.3 Measurements of CCSRR loaded 3D antenna fabricated prototype 7.6 Electrical properties of tissue mimicking head phantom 7.7 Em imaging results 7.7.1 Imaging results with CCSRR loaded 3D antenna setup 7.8 Sensitivity analysis 7.8.1 Internet of things based image transfer 7.9 Summary 8. Metamaterial Inspired Stacked Antenna Based Microwave Brain Imaging 8.1 Introduction 8.2 Importance of deep learning in current brain imaging technologies 8.3 Metamaterial loaded stacked antenna 8.3.1 Stacked antenna structure design and analysis 8.3.2 Stacked antenna geometry and design evolution analysis 8.3.3 Parametric analysis of MTM loaded stacked antenna 8.4 Stacked antenna prototype fabrication and performance analysis 8.5 Radiation characteristic analysis of the stacked antenna 8.6 Performance analysis of the stacked antenna with head model 8.7 Specific absorption rate (SAR) analysis of stacked antenna 8.8 Microwave brain imaging (MBI) system implementation method 8.9 Image data collection pre-processing and augmentation techniques 8.9.1 Image data collection 8.9.2 Image pre-processing and input size requirement 8.9.3 Image augmentation technique 8.10 Deep learning based tumor segmentation and classification models 8.11 Microwave segmentation network (MSegNet)-brain tumor segmentation model 8.11.1 Architecture of MSegNet segmentation model 8.11.2 Training experiment of MSegNet model 8.11.3 Evaluation matrix for the MSegNet segmentation model 8.11.4 Brain tumor segmentation performances 8.12 BrainImageNet (BINet)-brain tumor classification model 8.12.1 Mathematical analysis of the classification model 8.13 Architecture of BINet classification model 8.14 Training experiment of BINet classification model 8.15 Evaluation matrix for the BINet classification model 8.16 Brain images classification performances of the BINet model 8.17 Receiver operating characteristic of BINet model 8.18 Miss classification performance analysis of BINet model 8.19 Summary 9. Lower UHF Metamaterial Antenna for Nanosatellite Communication System 9.1 Introduction 9.2 Antennas for nanosatellite 9.3 EMNZ metamaterial design and characterization 9.4 EMNZ inspired UHF antenna 9.5 Summary Index