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Carbon nanotubes (CNTs) are a type of nanomaterial that have excellent electrical properties such as high carrier mobility, high saturation velocity, and small inherent capacitance, showing great promise in radio frequency (RF) applications. Decades of development have been made mainly on cut-off frequency and amplification; however, frequency conversion for RF transceivers, such as CNT-based mixers, has been rarely reported. In this work, based on randomly oriented carbon nanotube films, we focused on exploring the frequency conversion capability of CNT-based RF mixers. CNT-based RF transistors were designed and fabricated with a gate length of 50 nm and gate width of 100 μm to obtain nearly 30 mA of total current and 34 mS of transconductance. The Champion RF transistor has demonstrated cut-off frequencies of 78 GHz and 60 GHz for fT and fmax, respectively. CNT-based mixers achieve high conversion gain from −11.4 dB to −17.5 dB at 10 to 15 GHz in the X and Ku bands. Additionally, linearity is achieved with an input third intercept (IIP3) of 18 dBm. It is worth noting that the results from this work have no matching technology or tuning instrument assistance, which lay the foundations for the application of Ku band transceivers integrated with CNT amplifiers.

The Photon Counting Histogram Expectation Maximization (PCH-EM) algorithm has recently been reported as a candidate method for the characterization of Deep Sub-Electron Read Noise (DSERN) image sensors. This work describes a comprehensive demonstration of the PCH-EM algorithm applied to a DSERN capable quanta image sensor. The results show that PCH-EM is able to characterize DSERN pixels for a large span of quanta exposure and read noise values. The per-pixel characterization results of the sensor are combined with the proposed Photon Counting Distribution (PCD) model to demonstrate the ability of PCH-EM to predict the ensemble distribution of the device. The agreement between experimental observations and model predictions demonstrates both the applicability of the PCD model in the DSERN regime as well as the ability of the PCH-EM algorithm to accurately estimate the underlying model parameters.

We develop a novel algorithm for characterizing Deep Sub-Electron Read Noise (DSERN) image sensors. This algorithm is able to simultaneously compute maximum likelihood estimates of quanta exposure, conversion gain, bias, and read noise of DSERN pixels from a single sample of data with less uncertainty than the traditional photon transfer method. Methods for estimating the starting point of the algorithm are also provided to allow for automated analysis. Demonstration through Monte Carlo numerical experiments are carried out to show the effectiveness of the proposed technique. In support of the reproducible research effort, all of the simulation and analysis tools developed are available on the MathWorks file exchange (Hendrickson and Haefner, 2022).

This paper compares two in-pixel source follower stage designs for low noise CMOS image sensors embedded both on a same 5 mm by 5 mm chip fabricated in a 180nm CIS process. The presented chip embeds two pixel variants, one based on a body-effect-canceled thin oxide PMOS and the other embeds a native thick oxide NMOS. On the other hand they share the same sense node, same amplification circuit and 11bit single slope analog to digital converter (SS-ADC). The imager characterization demonstrates a histogram peak noise of 0.34e $^{-}_{\text{RMS}}$ with the PMOS SF pixel and 0.47e $^{-}_{\text{RMS}}$ with the NMOS SF at maximum analog gain. This performance is obtained at room temperature and 119 frame per second. Both pixel variants demonstrate a full well capacity over 5600 electrons.

A low voltage, high linearity and gain withlow powerultra-wideband (UWB) CMOS mixer in the RF receiver is proposed. This mixer is designed for a standard of 802.11 for use in Wi-Fi communications. The linearization technique for the third-order transconductance (푔푚3) cancellation with modified derivativesuperposition (MDS) is utilized to enhance the linearity performance of the proposed mixer. The MDS technique employs anauxiliary PMOS transistor in parallel with the NMOS transistor in the lower tree (transconductance stage)for reducing the third-orderintermodulationdistortion (IMD3).Besides, a switched buffer stage and the active loads are employed to improve the conversion gain of the mixer. High gain and high linear mixer is designed by the MDS technique and switched buffer. The proposed mixer is analyzed, and simulated using a 0.18 μm CMOS TSMC process; The LNA achieves 9.1dB conversion gain, maximum input third-order intercept point (IIP3) of +15dBm, double side-band noise figure (DSB NF) of 15.6 dB. This module consumes 2.06 mW DC power from a 1.2 V power supply in the RF frequency of 10 GHz.

This paper presents an investigation of the responsivity of a time-delay integration (TDI) charge-coupled device that employs anti-blooming clocking and uses a varying number of TDI stages. The influence of charge blooming caused by unused TDI stages in a TDI deployed selection scheme is shown experimentally, and an anti-blooming clocking mechanism is analyzed. The impact of blooming on sensor characteristics, such as the responsivity, the conversion gain, and the signal-to-noise ratio, is investigated. A comparison of the measurements with and without this anti-blooming clocking mechanism is presented and discussed in detail.

A stochastic model for characterizing the conversion gain of Active Pixel Complementary metal–oxide–semiconductor (CMOS) image sensors (APS) with at least four transistors is presented. This model, based on the fundamental principles of electronic noise, may provide a reliable calibration of the gain conversion, which is one of the most important parameters of CMOS Image Sensor pixels. The new model revisits the “gold standard” ratio method of the measured variance of the shot noise to the mean value. The model assumes that shot noise is the dominant noise source of the pixel. The microscopic random time-dependent voltage of any shot noise electron charging the junction capacitance C of the sensing node may have either an exponential form or a step form. In the former case, a factor of 1/2 appears in the variance to the mean value, namely, q/2C is obtained. In the latter case, the well-established ratio q/C remains, where q is the electron charge. This correction factor affects the parameters that are based on the conversion gain, such as quantum efficiency and noise. The model has been successfully tested for advanced image sensors with six transistors fabricated in a commercial FAB, applying a CMOS 180 nm technology node with four metals. The stochastic modeling is corroborated by measurements of the quantum efficiency and simulations with advanced software (Lumerical).

Based on the structure of Gilbert，a 24 GHz up-conversion mixer was designed with three-piece balun circuit on-chip. Using the gm/I method to coordinate the transistor size to obtain better conversion gain, isolation degree and circuit dissipation power. The circuit implementation is adopted by the xiamen san-0.5 μm PHEMT process, 5 V voltage power supply, and the conversion gain is 9 dBm when this LO power is 0 dBm. When work at 24 GHz band, 1 dB compressed point is -20 dBm, the maximum output power of the mixer is -10 dBm, RF output port and the LO port isolation degree is more than 32 dB, the whole circuit DC power consumption of 40 MW，chip area is 1 mm ×1.3 mm.

A new method for characterizing deep sub-electron read noise image sensors is reported. This method, based on the photon-counting histogram, can provide easy, independent and simultaneous measurements of the quanta exposure, conversion gain, and read noise. This new method provides a more accurate measure of conversion gain and read noise over conventional characterization techniques for image sensors with read noise from 0.15-0.40e- rms.