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For millimeter-wave power applications, GaN high-electron mobility transistors (HEMTs) are often grown epitaxially on a high-purity semi-insulating c-axis 4H-SiC substrate. For these anisotropic hexagonal materials, the design and modeling of microstrip and coplanar interconnects require detailed knowledge of both the ordinary permittivity ε⊥ and the extraordinary permittivity εǁ perpendicular and parallel, respectively, to the c-axis. However, conventional dielectric characterization techniques make it difficult to measure εǁ alone or to separate εǁ from ε⊥. As a result, there is little data for εǁ, especially at millimeter-wave frequencies. This work demonstrates techniques for characterizing εǁ of 4H SiC using substrate-integrated waveguides (SIWs) or SIW resonators. The measured εǁ on seven SIWs and eleven resonators from 110 to 170 GHz is within ±1% of 10.2. Because the SIWs and resonators can be fabricated on the same SiC substrate together with HEMTs and other devices, they can be conveniently measured on-wafer for precise material-device correlation. Such permittivity characterization techniques can be extended to other frequencies, materials, and orientations. 

Many recent efforts in the diagnostic field address the accessibility of cancer diagnosis. Typical histological staining methods identify cancer cells visually by a larger nucleus with more condensed chromatin. Machine learning (ML) has been incorporated into image analysis for improving this process. Recently, impedance spectrometers have been shown to generate all-inclusive lab-on-a-chip platforms to detect nucleus abnormities. In this paper, a wideband electrical sensor and data analysis paradigm that can identify nuclear changes shows the realization of a single-cell microfluidic device to detect nuclei of altered sizes. To model cells of altered nucleus, Jurkat cells were treated to enlarge or shrink their nucleus followed by broadband sensing to obtain the S-parameters of single cells. The ability to deduce important frequencies associated with nucleus size is demonstrated and used to improve classification models in both binary and multiclass scenarios, despite a heterogeneous and overlapping cell population. The important frequency features match those predicted in a double-shell circuit model published in prior work, demonstrating a coherent new analytical technique for electrical data analysis. The electrical sensing platform assisted by ML with impressive accuracy of cell classification looks forward to a label-free and flexible approach to cancer diagnosis. 

Currently, lacking suitable test structures, little data exist for the permittivity of hexagonal materials such as GaN and SiC at millimeter-wave frequencies, especially for the extraordinary permittivity ε || as opposed to the ordinary permittivity ε ⊥ . This paper demonstrates for the first time that it is possible to characterize ε || of c-axis 4H SiC using on-wafer measurements of substrate-integrated-waveguide resonators. In fact, measurements on eleven resonators yield a relative ε || of 10.27 ± 0.03 and a loss tangent tanδ<0.02 over the D band (110-170 GHz). The on-wafer measurements of resonators and other devices fabricated on the same SiC substrate can allow material property to be closely correlated with device performance. The present approach can be extended to materials of other types and orientations. 

Single-connection in situ calibration using biocompatible solutions is demonstrated in single-cell sensing from 0.5 to 9 GHz. The sensing is based on quickly trapping and releasing a live cell by dielectrophoresis on a coplanar transmission line with a little protrusion in one of its ground electrodes. The same transmission line is used as the calibration standard when covered by various solutions of known permittivities. The results show that the calibration technique may be precise enough to differentiate cells of different nucleus sizes, despite the measured difference being less than 0.01 dB in the deembedded scattering parameters. With better accuracy and throughput, the calibration technique may allow broadband electrical sensing of live cells in a high-throughput cytometer. 

Gallium nitride high-electron-mobility transistors (GaN HEMTs) are at a point of rapid growth in defense (radar, SATCOM) and commercial (5G and beyond) industries. This growth also comes at a point at which the standard GaN heterostructures remain unoptimized for maximum performance. For this reason, we propose the shift to the aluminum nitride (AlN) platform. AlN allows for smarter, highly-scaled heterostructure design that will improve the output power and thermal management of III-nitride amplifiers. Beyond improvements over the incumbent amplifier technology, AlN will allow for a level of integration previously unachievable with GaN electronics. State-of-the-art high-current p-channel FETs, mature filter technology, and advanced waveguides, all monolithically integrated with an AlN/GaN/AlN HEMT, is made possible with AlN. It is on this new AlN platform that nitride electronics may maximize their full high-power, high-speed potential for mm-wave communication and high-power logic applications.