Search Results (5)

Electrochemical migration (ECM) on the surface of printed circuit boards (PCBs) continues to pose a significant reliability risk in electronics. Nevertheless, the existing literature lacks studies that address the solder mask and solder pad design aspects in the context of ECM. Therefore, the objective of this study was to assess the impact of solder mask type with varying roughness and solder pad design on the susceptibility to ECM using a water drop test and thermal humidity bias test. Hot air solder leveling-coated PCBs were tested. Furthermore, the ECM tests were conducted on PCBs with applied no-clean solder paste to evaluate the influence of flux residues on the resulting ECM behavior. The results indicated that the higher roughness of the solder mask significantly contributes to ECM inhibition through the creation of a mechanical barrier for the dendrites. Furthermore, lower ECM susceptibility was also observed for copper-defined pads, where a similar effect is presumed. However, the influence of the no-clean flux residues can prevail over the effects of the solder mask. Therefore, the use of a rough solder mask and a copper-defined pad design is recommended if the PCB is to be washed from flux residues after the soldering process. Full article

Gallium Nitride (GaN) power devices can offer better switching performance and higher efficiency than Silicon Carbide (SiC) and Silicon (Si) devices in power electronics applications. GaN has extensively been incorporated in electric vehicle charging stations and power supplies, subjected to harsh environmental conditions. Many reliability studies evaluate GaN power devices through thermal stresses during current conduction or pulsing, with a few focusing on high blocking voltage and high humidity. This paper compares GaN-on-Si High-Electron-Mobility Transistors (HEMT) device characteristics under a High Humidity, High Temperature, Reverse Bias (H³TRB) Test. Twenty-one devices from three manufacturers were subjected to 85 °C and 85% relative humidity while blocking 80% of their voltage rating. Devices from two manufacturers utilize a cascade configuration with a silicon metal-oxide-semiconductor field-effect transistor (MOSFET), while the devices from the third manufacturer are lateral p-GaN HEMTs. Through characterization, three sample devices have exhibited degraded blocking voltage capability. The results of the H³TRB test and potential causes of the failure mode are discussed. Full article

Radiosoundings are essential for weather and climate applications, as well as for calibration and validation of remote sensing observations. Vaisala RS92 radiosondes have been widely used on a global scale until 2016; although in the fall of 2013, Vaisala introduced the RS41 model to progressively replace the RS92. To ensure the highest quality and homogeneity of measurements following the transition from RS92 to RS41, intercomparisons of the two radiosonde models are needed. A methodology was introduced to simultaneously test and compare the two radiosonde models inside climatic chambers, in terms of noise, calibration accuracy, and bias in temperature measurements. A pair of RS41 and RS92 radiosondes has been tested at ambient pressure under very different temperature and humidity conditions, reproducing the atmospheric conditions that a radiosonde can meet at the ground before launch. The radiosondes have also been tested before and after fast (within ≈ 10 s) temperature changes of about ±20 °C, simulating a scenario similar to steep thermal changes that radiosondes can meet when passing from indoor to outdoor environment during the pre-launch phase. The results show that the temperature sensor of RS41 is less affected by noise and more accurate than that of RS92, with noise values less than 0.06 °C for RS41 and less than 0.1 °C for RS92. The deviation from the reference value, referred to as calibration error, is within ±0.1 °C for RS41 and the related uncertainty (hereafter with coverage factor k = 1) is less than 0.06 °C, while RS92 is affected by a cold bias in the calibration, which ranges from 0.1 °C up to a few tenths of a degree, with a calibration uncertainty less than 0.1 °C. The temperature bias between RS41 and RS92 is within ±0.1 °C, while its uncertainty is less than 0.1 °C. The fast and steep thermal changes that radiosondes can meet during the pre-launch phase might lead to a noise increase in temperature sensors during radiosoundings, up to 0.1 °C for RS41 and up to 0.3 °C for RS92, with a similar increase in their calibration uncertainty, as well as an increase in the uncertainty of their bias up to 0.3 °C. Full article

Concrete cracks can threaten the usability of structures and degrade the aesthetics of buildings. Furthermore, minor cracks can develop into large-scale cracks that may lead to structural failure when exposed to excessive external loads. In addition, the concrete crack width and depth should be precisely measured to investigate the effects of concrete cracks on the stability of structures. Thus, a nondestructive and noncontact testing method was introduced for detecting concrete crack depth using thermal images and machine learning. The thermal images of the cracked specimens were obtained using a constant test setup for several months under daylight conditions, which provided sufficient heat for measuring the temperature distributions of the specimens, with recording parameters such as air temperature, humidity, and illuminance. From the thermal images, the crack and surface temperatures were obtained depending on the crack widths and depths using the parameters. Four machine-learning algorithms (decision tree, extremely randomized tree, gradient boosting, and AdaBoost) were selected, and the results of crack depth prediction were compared to identify the best algorithm. In addition, data bias analysis using principal component analysis, singular value decomposition, and independent component analysis were conducted to evaluate the efficiency of machine learning. Full article

There is an increasing demand for a land surface temperature (LST) dataset with both fine spatial and temporal resolutions due to the key role of LST in the Earth’s land–atmosphere system. Currently, the technique most commonly used to meet the demand is thermal infrared (TIR) remote sensing. However, cloud contamination interferes with TIR transmission through the atmosphere, limiting the potential of space-borne TIR sensors to provide the LST with complete spatio-temporal coverage. To solve this problem, we developed a two-step integrated method to: (i) estimate the 10-km LST with a high spatial coverage from passive microwave (PMW) data using the multilayer perceptron (MLP) model; and (ii) downscale the LST to 1 km and fill the gaps based on the geographically and temporally weighted regression (GTWR) model. Finally, the 1-km all-weather LST for cloudy pixels was fused with Aqua MODIS clear-sky LST via bias correction. This method was applied to produce the all-weather LST products for both daytime and nighttime during the years 2013–2018 in South China. The evaluations showed that the accuracy of the reproduced LST on cloudy days was comparable to that of the MODIS LST in terms of mean absolute error (2.29–2.65 K), root mean square error (2.92–3.25 K), and coefficients of determination (0.82–0.92) against the in situ measurements at four flux stations and ten automatic meteorological stations with various land cover types. The spatial and temporal analysis showed that the MLP-GTWR LST were highly consistent with the MODIS, in situ, and ERA5-Land LST, with the satisfactory ability to present the LST pattern under cloudy conditions. In addition, the MLP-GTWR method outperformed a gap-filling method and another TIR-PMW integrated method due to the local strategy in MLP and the consideration of temporal non-stationarity relationship in GTWR. Therefore, the test of the developed method in the frequently cloudy South China indicates the efficient potential for further application to other humid regions to generate the LST under cloudy condition. Full article