Three-dimensional (3-D) printing, also known as additive manufacturing, provides a novel and cost-effective approach for implementing microwave devices. With the rapid advancement and improved manufacturing resolution of the 3-D printing technology, additive manufacturing has enabled the design and fabrication of electronic devices in higher terahertz (THz) frequency bands, contributing to bridging the gap between microwaves and photonics. Simultaneously, metalenses have garnered significant attention due to their ability to shape electromagnetic (EM) wavefronts. Metalens technology offers a promising solution for wave focusing, surpassing traditional dielectric lenses with advantages such as reduced weight and low loss, particularly at THz frequencies. In this article, we present an overview of the development of 3-D-printed THz metalenses, ranging from single metalenses to dual-layer and trilayer configurations. The functionality of the metalenses becomes more powerful, from replacing conventional light-focusing dielectric lenses for single-layer metalenses, achieving 2-D beam scanning, holographic imaging, and reconfigurable orbital angular momentum (OAM) for dual-layer metalenses, to enabling 3-D focus scanning for trilayer metalenses. We also discuss practical measurement technologies for THz metalenses and briefly outline the prospective to propel the 3-D-printed metalens technology forward.

This paper presents the analysis and design of an oscillator-doubler architecture which is used to generate THz signals. In this architecture, the doubler obtains the optimum fundamental-frequency load impedance for second harmonic generation without causing problems related to instability. The oscillator creates voltages close to the optimum voltage condition, which leads to maximum power being delivered to the doubler connected to the oscillator tank. Compared to a signal generator composed of an oscillator and a conventional doubler with short-circuit load at the fundamental frequency, the proposed circuit has higher output power and DC-to-THz conversion efficiency. Based on this architecture, a 0.3-THz signal generator is designed in 40-nm CMOS. In this 0.3-THz signal generator, an inductor-sharing configuration is proposed to increase the transistor size in the cross-coupled oscillator, thus increasing the power density of the signal generator. Besides, the impact of the doubler fundamental-frequency load impedance on the conversion gain of the doubler is introduced. Also, a method of suppressing the unwanted mode in the cross-coupled oscillator is proposed. The output of this circuit is radiated through on-chip antennas. The measured radiated power and the DC-to-THz efficiency of the chip are -3.8 dBm and 0.37%, respectively, with an output frequency tuning range of 4.8%.

Bridging the terahertz gap requires synergism between the microwave and photonic communities. Advances in each of these two communities are often complementary but sometimes overlooked. One example is the manipulation of waves, known as anomalous diffraction via the use of metamaterials. This is achieved by controlling the surface impedance of each pixel at the interface of two different materials or alternately the phase and magnitude of the wave diffracted off the pixel. In this paper, a review of developments in wave manipulation from microwave to optical frequencies is presented, together with our new results in the terahertz regime. Generation of phase curves for pixel design requires a priori information on material properties at terahertz frequencies. Fabrication of terahertz devices entails micromachining in the clean room while their experimental validation demands both amplitude and phase information. Through judicial selection of practices in microwave and photonic communities, we can further the exploration of wave phenomena at terahertz frequencies.

The objective of this paper is to provide the context, physical insight, and perspective on antennas in wireless communications. Although it does not mean to be comprehensive, the four key technologies related to small antenna designs to be reviewed and discussed, including multiband planar inverted-F antennas, broadband folded patch antennas, compact differentially fed antennas, and miniature circularly polarized patch antennas, would cover a wide range of topical interests and practical applications. A brief overview of computer software for analyzing these antennas is also provided. Hopefully, this paper will be beneficial for the diverse engineering readership of the IEEE.

This paper proposes improvements in the row and column samplings of the multilevel QR factorization method known as IES/sup 3/, a fast integral equation solver previously proposed for efficient three-dimensional (3-D) parameter extraction. First, a rigorous Gram-Schmidt row sampling is developed to replace the row sampling algorithm in IES/sup 3/, leading to a more stable algorithm. Second, to further enhance the efficiency of column sampling, a new scheme based on the idea of locating the interpolation points is presented. Error analyses indicate that the proposed schemes have higher accuracies than the original sampling in IES/sup 3/, especially when the number of sampled points is small. The IES/sup 3/ that uses one of these improved algorithms is called improved multilevel matrix QR factorization (IMLMQRF). These IMLMQRFs are applied in the magnetoquasistatic analysis of printed circuits on multilayered lossy medium for extractions of inductances and resistances. The frequency dependency of such parameters is also illustrated.

In this paper, a new multilevel Green's function interpolation method (MLGFIM) is presented to solve integral equations for large-scale electrostatic problems. In MLGFIM, the problem domain is first divided into multilevel cubes. Next, the peer-level Green's function interpolation technique is employed, and then, a new lower-to-upper-level Green's function interpolation technique is devised. They are used with the multilevel discretization to speed up the matrix-vector multiplications in the iterative solution in which a computational complexity of O(N) is achieved. The MLGFIM is used to extract the capacitances encountered in radio frequency integrated circuits (RFICs) and microelectromechanical systems. Moreover, to demonstrate its efficiency both in simulation speed and memory storage requirement, MLGFIM is compared with FastCap for free space problems and applied to extract capacitances from multilayered structures. For problems with 375,000 unknowns, the proposed method only requires 343 MB of computer memory.

In the numerical Maxwell-equation model (NMM3D) of rough-surface scattering, we solve Maxwell equations in three dimensions to calculate emissivities for applications in passive microwave remote sensing of soil and ocean surfaces. The difficult cases for soil surfaces are with exponential correlation functions when the surfaces have fine-scale structures of large slopes. The difficulty for ocean surfaces is that because the emissivities are close to that of a flat surface, the emissivities have to be calculated accurately to correctly assess the rough-surface effects. In this paper, the accuracies of emissivity calculations are improved by using Rao-Wilton-Glisson basis functions. We further use sparse matrix canonical method to solve the matrix equation of Poggio-Miller-Chang-Harrington-Wu integral equations. Energy conservation checks are provided for the simulations. Comparisons are made with results from the pulse basis function. Numerical results are illustrated for soil and ocean surfaces respectively with exponential correlation function and ocean spectrum. The emissivities of soil are illustrated at both L- and C-bands and at multiple incidence angles for the same physical roughness parameters. The brightness temperatures for ocean surfaces are illustrated for cases with various wind speeds. We compare results with those from the sparse matrix methods. Comparisons are also made with experimental emissivity measurements of soil surfaces. Parallel computation is also implemented. Lookup tables of emissivities based on NMM3D are provided.

The backscattering coefficient and emissivity of wet soil surface are studied with the 3-dimensional numerical simulations. The study is focused on the angular, frequency, and polarimetric dependence of the scattering and emission. The simulation results are compared with the experimental measurements from real-life soil surface for backscattering coefficients at L and C frequency bands and at the multi-incidence angles. The fairly good agreements are observed for the fixed physical surface roughness parameters at two frequency bands.

Microwave emission of ocean surfaces with full spatial spectrum is studied in this paper. For ocean surfaces with full spectrum, the rms height of roughness can be many wavelengths, and the surface size must be chosen to be larger than the longest scale wave in the spectrum. Due to computer resources, it is not straightforward to conduct numerical simulations of emission from rough surfaces with large rms height and size since a large number of unknowns will be involved. In this paper, the multilevel expansion of the sparse matrix canonical grid (SMCG) method, which is available for surfaces with large rms heights, is used to study the emission of one-dimensional (1-D) ocean surfaces. The computational complexity and the memory requirement are still on the order of O(N log (N)) and O (N), respectively, as in the SMCG method. Ocean surfaces with size 1024 wavelengths (21.9 m at 14 GHz) and spatial spectrum bandwidth between 0.858 rads/m (corresponding to the longest scale of 341.3 wavelengths) and 4691.5 rads/m (corresponding to the shortest scale of 1/16 wavelengths), which is rather wide to be regarded as a full spectrum, are studied. The maximum of the electromagnetic wavenumber-surface rms height product is up to 25.18. The surface is modeled as a lossy dielectric surface with large relative permittivity rather than as a perfectly conducting surface, which is often adopted as an approximation in the active remote sensing of ocean surfaces. A relatively high sampling density is used to ensure accuracy. The effects of the low and high portions of the spectrum on the emissivity are studied numerically. Monte Carlo simulation for ocean surfaces is also performed by exploiting the efficiency of the multilevel expansion method and the use of parallel computing techniques. The convergence of the results with respect to the sampling density is also illustrated.

Simulations of electromagnetic waves scattering from two-dimensional perfectly conducting random rough surfaces are performed using the method of moment (MoM) and the electric field integral equation (EFIE). Using wavelets as basis and testing functions, the resulting moment matrix is generally sparse after applying a threshold truncation. This property makes wavelets particularly useful in simulating large-scale problems, in which reducing memory storage requirement and CPU time are crucial. In this paper, scattering from Gaussian conducting rough surfaces of a few hundred square wavelengths are studied numerically using Haar wavelets. A matrix sparsity less than 10% is achieved for a range of root mean square (RMS) height at eight sampling points per linear wavelength. Parallelization of the code is also performed. Simulation results of the bistatic scattering coefficients are presented for different surface RMS heights up to 1 wavelength. Comparisons with sparse-matrix/canonical-grid approach (SM/CG) and triangular discretized (RWG basis) results are made as well. Depolarization effects are examined for both TE and TM incident waves. The relative merits of the SM/CG method and the present method are discussed.

Wave scattering from two-dimensional (2-D) random rough surfaces [three-dimensional (3-D) scattering problem] has been previously analyzed using the sparse-matrix/canonical grid (SM/CG) method. The computational complexity and memory requirement of the SM/CG method are O(N log N) per iteration and O(N), respectively, where N is the number of surface unknowns. Furthermore, the SM/CG method is FFT based, which facilitates the implementation on parallel processors. In this paper, we present a cost-effective solution by implementing the SM/CG method on a Beowulf system consisting of PCs (processors) connected by a 100 Base TX Ethernet switch. The workloads of computing the sparse-matrix-vector multiplication corresponding to the near interactions and the fast Fourier transform (FFT) operations corresponding to the far interactions in the SM/CG method can be easily distributed among all the processors. Both perfectly conducting and lossy dielectric surfaces of Gaussian spectrum and ocean spectrum are analyzed thereafter. When possible, speedup factors against a single processor are given. It is shown that the SM/CG method for a single realization of rough surface scattering can be efficiently adapted for parallel implementation. The largest number of surface unknowns solved in this paper is over 1.5 million. On the other hand, a problem of 131072 surface unknowns for a PEC random rough surface of 1024 square wavelengths only requires a CPU time of less than 20 min. We demonstrate that analysis of a large-scale 2-D random rough surface feasible for a single realization and for one incident angle is possible using the low-cost Beowulf system.

The simulations of emissivities from a two-dimensional (2D) wet soil with random rough surfaces are studied with numerical solutions of three-dimensional (3D) Maxwell equations. The wet soils have large permittivity. For media with large permittivities, the surface fields can have large spatial variations on the surface. Thus, a dense discretization of the surface is required to implement the method of moment (MoM) for the surface integral equations. Such a dense discretization is also required to ensure that the emissivity can be calculated to the required accuracy of 0.01 for passive remote sensing applications. It has been shown that the physics-based two-grid method (PBTG) can efficiently compute the accurate surface fields on the dense grid. In this paper, the numerical results are calculated by using the PBTG in conjunction with the sparse-matrix canonical grid method (SMCG). The emissivities are illustrated for random rough surfaces with Gaussian spectrum for different soil moisture conditions. The results are calculated for L- and C-bands using the same physical roughness parameters. The numerical solutions of Maxwell's equations are also compared with the popular H and Q empirical model.

Recently, a fast computational technique based on the banded-matrix iterative approach/canonical grid (BMIA/CG) method has been developed for the analysis of random rough surfaces. However, there are situations that the matrix-vector multiplication associated with strong near-field interactions may dominate the CPU and memory storage requirement. In this paper, the wavelet transform method in conjunction with a screening window scheme is used to address these problems. It is noted that the wavelet-transformed matrix for each submatrix is implemented only once for different incident polarizations. Based on the idea of multiresolution analysis, the matrix-vector multiplication in an iterative solver is then efficiently evaluated for its higher sparsity. Numerical simulations are then used to study scattering and emission from the lossy dielectric random rough surfaces. All the four Stokes parameters are calculated in this paper.

With the advent of the microwave radiometer, passive remote sensing of clouds and precipitation has become an indispensable tool in a variety of meteorological and oceanographical applications. There is wide interest in the quantitative retrieval of water vapor, cloud liquid, and ice using brightness temperature observations in scientific studies such as Earth's radiation budget and microphysical processes of winter and summer clouds. Emission and scattering characteristics of hydrometeors depend on the frequency of observation. Thus, a multifrequency radiometer has the capability of profiling cloud microphysics. Sensitivities of vapor, liquid, and ice with respect to 20.6, 31.65 and 90 GHz brightness temperatures are studied. For the model studies, the atmosphere is characterized by vapor density and temperature profiles and layers of liquid and ice components. A parameterized radiative transfer model is used to quantify radiation emanating from the atmosphere. It is shown that downwelling scattering of radiation by an ice layer results in enhancement at 90 GHz brightness temperature. Once absorptive components such as vapor and liquid are estimated accurately, then it is shown that the ice water path can be retrieved using ground-based three-channel radiometer observations. In this paper the authors developed two- and three-channel neural network-based inversion models. Success of a neural network-based approach is demonstrated using a simulated time series of vapor, liquid, and ice. Performance of the standard explicit inversion model is compared with an iterative inversion model. In part II of this paper, actual radiometer, and radar field measurements are utilized to show practical applicability of the inverse models.

For pt.I see ibid., vol.35, no.2, p.224-36 (1997). A neural network-based retrieval technique is developed to infer vapor, liquid, and ice columns using two- and three-channel microwave radiometers. Neural network-based inverse scattering methods are capable of merging various data streams in order to retrieve microphysical properties of clouds and precipitation. The method is calibrated using National Oceanic and Atmospheric Administration (NOAA) results in a cloud-free condition. The performance of two- and three-channel neural network-based techniques is verified by independent NOAA estimates. The estimates of vapor and liquid agree with NOAA values. In the presence of ice, the liquid estimates deviated from NOAA's estimates. One of the major contributions of the three-channel radiometer is the estimation of ice in a winter cloud. The three-channel radiometer not only improves estimates of vapor and liquid, but also retrieves the ice column. Passive remote sensing can be ameliorated with the help of active remote sensing methods. The three-channel radiometer is used for estimating columnar contents of vapor, liquid, and ice in a cloud. It is shown that vertical profiles of median size diameter, number concentration, liquid water content, and ice water content can be inferred by combining radar reflectivity and radiometer observations. The combined remote sensor method is applied to Winter Icing and Storms Project (WISP) data to obtain detailed microphysical properties of clouds and precipitation. The authors also derived Z- Ice Water Content (IWC) and Z- Liquid Water Content (LWC) relationships and they are consistent with the earlier results.

A number of representative techniques for analyzing frequency-selective surfaces (FSSs), which comprise periodic arrays of patches or apertures in a conducting screen and find important applications as filters in microwaves and optics, are discussed. The basic properties of the FSSs are reviewed and several different approaches to predicting their frequency-response characteristics are described. Some recent developments in the treatment of truncated, curved, and doubly periodic screens are mentioned and representative experimental results are included.>