A graphene-based metamaterial (GMM) reflectarray antenna with frequency tunable radiation characteristics has been investigated in this study. The unit-cell element consists of graphene split-ring-resonator (SRR) with two gaps printed on a grounded SiO₂ substrate. The electrical properties of the metamaterial unit-cell have been determined at different graphene chemical potentials and different SRR gaps using the waveguide simulator. The metamaterial unit-cell element introduces negative ɛ _r and μ _r over a wide frequency band starting from 390 to 550 GHz. A reflectarray unit-cell element based on the GMM is designed at different frequencies. The phase compensation of the reflected waves is achieved by changing the SRR gap width. Reflection coefficient phase variations for 0°–301° with a variable slope are obtained for different graphene conductivities. Three different 13 × 13 GMM reflectarrays are designed and analysed at different graphene chemical potentials. A maximum gain of 22.6, 19, and 21.5 dB with side lobe level (SLL) is 11.31/9.15, 10.98/5.31, and 7.31/8.45 dB in an E/H-plane for the reflectarray arrangements (I), (II) and (III), respectively. An averaging phase curve is calculated to construct a single structure GMM reflectarray with frequency tunable radiation characteristics. A maximum gain of 21.8 ± 1 dB with improved SLL of 13 dB was achieved.

High-field magnetic resonance imaging (MRI) scans have safety problems because energy is not homogeneously distributed in the human body. A prescan where energy and temperature distributions are calculated for input energy budgeting can significantly lower the risk. Therefore, fast and accurate calculations of the electromagnetic (EM) fields of an MRI system with a subject under scan are needed. Here, the authors present a fast EM solver based on a weak-form volume integral equation (VIE) for solving this problem. The proposed approach calculates the EM field inside the human body at a high speed without sacrificing accuracy. In the proposed approach, the VIE formulation for an inhomogeneous dielectric object is employed for near-field calculations. The operation on a dense matrix resulted by the VIE is accelerated by fast Fourier transform (FFT) in conjunction with the latest efficient iterative method. Numerical experiments are presented to show the speed and accuracy of the proposed EM solver.

In this study, two ultra-wideband (UWB) filters having the fractional bandwidth >120% are designed, analysed and fabricated. The first filter is designed with three quarter-wavelength short-circuited stubs and second by using exponential tapered impedance line stub loaded microstrip resonator. The first filter consists of five transmission poles within the passband. The second filter with tapered inductive loading on quarter-wavelength high impedance line exhibits a sharp notch stopband around 5.5 GHz, to suppress the interference from IEEE 302.11a WLAN band signals with an attenuation level >30 dB. A good agreement between the measured and predicted results is achieved, which validate the authors’ filter designs.

The surface roughness of a machined metal surface is crucial to its appearance and performance. There are hardly any in-situ methods for surface roughness measurement of moving surfaces. A study of the digital speckle patterns generated by rough surfaces illuminated by a laser is performed experimentally. Laser speckle phenomenon can be used to monitor the surface roughness in a non-contact way. By investigating the effect of the surface roughness on the statistical and fractal parameters of the laser speckle pattern, an assessment method for evaluating surface roughness is discussed. The results show that some of the proposed statistical parameters have definite relationships with the surface roughness and can be explored to evaluate the surface roughness. Furthermore, the fractal parameters of the speckle pattern are sensitive to the type of machining process and therefore they can be used to classify the machined surface. The method can be a practical tool to achieve in-situ surface roughness measurement of moving surfaces.