Production of an EP/PDMS/SA/AlZnO Coated Superhydrophobic Surface through an Aerosol-Assisted Chemical Vapor Deposition Process

In this study, a superhydrophobic coating on glass has been prepared through a single-step aerosol-assisted chemical vapor deposition (AACVD) process. During the process, an aerosolized precursor containing polydimethylsiloxane, epoxy resin, and stearic acid functionalized Al-doped ZnO nanoparticles was deposited onto the glass at 350 °C. X-ray photoelectron spectroscopy, scanning electron microscopy, and atomic force microscopy showed that the precursor was successfully coated and formed a nano/microstructure (surface roughness: 378.0 ± 46.1 nm) on the glass surface. The coated surface had a water contact angle of 159.1 ± 1.2°, contact angle hysteresis of 2.2 ± 1.7°, and rolling off-angle of 1°, indicating that it was superhydrophobic. In the self-cleaning test of the coated surface at a tilted angle of 20°, it was shown that water droplets rolled and washed out dirt on the surface. The stability tests showed that the surface remained superhydrophobic after 120 h of exposure to ultraviolet (UV) irradiation and even after heat exposure at 350 °C. In addition, the surface was highly repellent to water solutions of pH 1–13. The results showed that the addition of the functionalized nanoparticles into the precursor allowed for the control of surface roughness and provided a simplified single-step fabrication process of the superhydrophobic surface. This provides valuable information for developing the manufacturing process for superhydrophobic surfaces

7.2 A 48 ??4013.5 mm Depth Resolution Flash LiDAR Sensor with In-Pixel Zoom Histogramming Time-to-Digital Converter

3D imaging technologies have become prevalent for diverse applications such as user identification, interactive user interfaces with AR/VR devices, and self-driving cars. Direct time-of-flight (D-ToF) systems, LiDAR sensors, are desirable for long-distance measurements in outdoor environments because they offer high sensitivity to weak reflected light and high immunity to background light thanks to the spatiotemporal correlation of SPADs [1], [2]. SPAD-based LiDAR sensors suffer from a large amount of ToF data generated by complicated time-to-digital converters (TDC), resulting in limited spatial resolution and frame rate compared with indirect ToF (I-ToF) sensors. Recently, LiDAR sensors embedding histogramming TDCs have been reported to generate depth information to reduce the required output bandwidth [3]-[6]. However, they still adopt a large number of memories in pixel, a complicated signal processor, or a column-parallel TDC scheme with scanning optics. ?? 2021 IEEE

Performance of Logistic Regression and Support Vector Machines for Seismic Vulnerability Assessment and Mapping: A Case Study of the 12 September 2016 ML5.8 Gyeongju Earthquake, South Korea

In this study, we performed seismic vulnerability assessment and mapping of the ML5.8 Gyeongju Earthquake in Gyeongju, South Korea, as a case study. We applied logistic regression (LR) and four kernel models based on the support vector machine (SVM) learning method to derive suitable models for assessing seismic vulnerabilities; the results of each model were then mapped and evaluated. Dependent variables were quantified using buildings damaged in the 9.12 Gyeongju Earthquake, and independent variables were constructed and used as spatial databases by selecting 15 sub-indicators related to earthquakes. Success and prediction rates were calculated using receiver operating characteristic (ROC) curves. The success rates of the models (LR, SVM models based on linear, polynomial, radial basis function, and sigmoid kernels) were 0.652, 0.649, 0.842, 0.998, and 0.630, respectively, and the prediction rates were 0.714, 0.651, 0.804, 0.919, and 0.629, respectively. Among the five models, RBF-SVM showed the highest performance. Seismic vulnerability maps were created for each of the five models and were graded as safe, low, moderate, high, or very high. Finally, we examined the distribution of building classes among the 23 administrative districts of Gyeongju. The common vulnerable regions among all five maps were Jungbu-dong and Hwangnam-dong, and the common safe region among all five maps was Gangdong-myeon

Production of an EP/PDMS/SA/AlZnO Coated Superhydrophobic Surface through an Aerosol-Assisted Chemical Vapor Deposition Process

In this study, a superhydrophobic coating on glass has been prepared through a single-step aerosol-assisted chemical vapor deposition (AACVD) process. During the process, an aerosolized precursor containing polydimethylsiloxane, epoxy resin, and stearic acid functionalized Al-doped ZnO nanoparticles was deposited onto the glass at 350 °C. X-ray photoelectron spectroscopy, scanning electron microscopy, and atomic force microscopy showed that the precursor was successfully coated and formed a nano/microstructure (surface roughness: 378.0 ± 46.1 nm) on the glass surface. The coated surface had a water contact angle of 159.1 ± 1.2°, contact angle hysteresis of 2.2 ± 1.7°, and rolling off-angle of 1°, indicating that it was superhydrophobic. In the self-cleaning test of the coated surface at a tilted angle of 20°, it was shown that water droplets rolled and washed out dirt on the surface. The stability tests showed that the surface remained superhydrophobic after 120 h of exposure to ultraviolet (UV) irradiation and even after heat exposure at 350 °C. In addition, the surface was highly repellent to water solutions of pH 1–13. The results showed that the addition of the functionalized nanoparticles into the precursor allowed for the control of surface roughness and provided a simplified single-step fabrication process of the superhydrophobic surface. This provides valuable information for developing the manufacturing process for superhydrophobic surfaces

Highly Conductive Tungsten-Doped Tin(IV) Oxide Transparent Electrodes Delivered by Lattice-Strain Control

Alternatives to tin-doped indium oxide transparent electrodes are needed to meet the growing demand for modern electronic devices. Here, we present a chemical vapor deposition route to tungsten-doped SnO2 thin films with resistivities as low as 5.9 × 10–4 Ω cm and electron mobilities as high as 30 cm2 V–1 s–1. Le Bail fitting of the XRD data showed that the substitutional dopant, tungsten(V) causes minimal distortion to the SnO2 unit cell due to its radius closely matching that of tin(IV). Furthermore, crystallographic preferential orientation in the [200] direction that is thought to facilitate a high mobility was also seen. X-ray photoelectron spectroscopy analysis suggests that W is present in the +5 state, as opposed to +6, therefore minimizing ionized impurity scattering, hence also helping achieve the observed high electron mobilities. The tungsten-doped films had optical band gaps of 3.7 eV, thus enabling transparency to visible light

An 80 x 60 Flash LiDAR Sensor With In-Pixel Delta-Intensity Quaternary Search Histogramming TDC

This article presents a flash light detection and ranging (LiDAR) sensor featuring an in-pixel histogramming time-to-digital converter (hTDC) based on a delta-intensity quaternary search (DIQS) technique. The proposed 12-b DIQS hTDC is a two-step converter consisting of a 6-h coarse hTDC and a 7-b fine hTDC with 1-b redundancy. The DIQS hTDC synthesizes depth maps with three subframes from the coarse mode and a single subframe from the fine mode, achieving 100-ps resolution without a clock frequency of a few gigahertz. The DIQS repeats dividing the time range of a current step into four periods and finding the location where a target object is placed by comparing the number of events in each period, which is similar to the binary search method but doubles its operating speed. Two time-of-flight (ToF) bits are consecutively determined in every coarse step, and seven ToF bits are estimated by the indirect ToF technique with photon counts. An up-down counter is employed to reduce the memory size by half and enable the delta-intensity technique that can extend the dynamic range by suppressing the uniform background light. The prototype LiDAR with an 80 x 60 pixel array was fabricated in a 110-nm CMOS image sensor (CIS) process and fully characterized. The maximum detectable range is measured to 45 m with a success rate of 100% at night and 60% under 70-klux background light. The depth accuracy and precision are 2.5 and 1.5 cm from 3 to 4.5 m indoor, respectively, and the precision is maintained to 1.8 cm for the target located at a 1.5-m distance under 60-klux background light. Inherent time-gating and differential signaling of the DIQS hTDC effectively suppress common-mode noise, accomplishing real-time acquisition of depth images with 30 frames/s in a 9-m range at 30-klux background light