A resonator consisting of a microstrip spiral, with a reversal in winding direction, is used for a narrowband superconducting filter. The fields are tightly confined, leading to the required small coupling coefficients, without a large separation between resonators. Nevertheless, tunability and power-handling capacity are better than some other resonators with localized fields. A quality factor exceeding a million was achieved. A 148 MHz, 0.1% bandwidth sixth-order quasi-elliptic filter is demonstrated

The total ionizing dose irradiation effects are investigated in Si vertical diffused MOSFETs (VDMOSs) with different gate dielectrics including single SiO₂ layer and double Si₃N₄/SiO₂ layer. Radiation-induced holes trapping is greater for single SiO₂ layer than for double Si₃N₄/SiO₂ layer. Dielectric oxidation temperature dependent TID effects are also studied. Holes trapping induced negative threshold voltage shift is smaller for SiO₂ at lower oxidation temperature. Gate bias during irradiation leads to different VTH shift for different gate dielectrics. Single SiO₂ layer shows the worst negative VTH at VG=0 V, while double Si₃N₄/SiO₂ shows negative VTH shift at VG=-5 V, positive VTH shift at VG=10 V, and negligible VTH shift at VG=0 V.

This paper proposes a multichannel wavelet kernel network (MWKN) modeling technique with a two-stage training technique for high-dimensional inverse modeling of microwave filters. The real and imaginary parts of the transmission and reflection characteristics are used as the model inputs, while the geometric parameters of the filter are designated as the outputs. Since the electrical signal in microwave inverse modeling encompasses multiple frequency components and complex information arising from the subtle dimensional changes in the metal pattern, the wavelet transform is introduced by leveraging its powerful multi-scale and approximate detail features to form the discrete wavelet convolution layer in the proposed MWKN. To adapt to the learning of approximate detailed features at different scales, the learnable parameters of this layer and the weights of the backbone network are adjusted in stages through a two-stage training strategy based on particle swarm optimization (PSO), which jointly promotes the rapid convergence of the model. Three numerical examples demonstrate the effectiveness and robustness of the proposed MWKN model. Compared with the traditional design method using electromagnetic (EM) simulation, this approach significantly and substantially reduces the repeated calculation time and is capable of predicting the geometry that meets the design specifications within 0.42 s.

This letter proposes a MOS-current-mode-logic (MCML) driver with an active inductor structure to provide large voltage swing with linear response. This design is implemented in 45 nm CMOS with 1.2V supply. Compared with conventional active-inductor-based circuits, this topology enlarges the available single-ended output voltage swing from less than 350 mV to 600 mV. The MCML driver occupies a chip area of 0.0264 mm(2). Operating at 10 Gb/s over a channel with 3.5 dB loss at 5 GHz, the eye height is measured as 351 mV with 600 mV single-ended voltage swing, and the peak-to-peak jitter is 14.9 ps (0.149 UI).