Search Results (6)

This paper aims to investigate the quality of thin alumina films deposited on glass samples using magnetron sputtering in the reactive modulated pulsed power mode (MPPMS) and evaluate the process productivity. The aluminum target was sputtered in Ar/O₂ gas mixtures with different fractions of oxygen in the total gas flow, in the fixed pulsed voltage mode. The pulse-on duration was varied between 5 and 10 ms, while the pulse-off time was 100 or 200 ms. The dependences of mass deposition rate and discharge current on the oxygen flow were measured, and the specific deposition rate values were calculated. Prepared coatings had a thicknesses of 100–400 nm. Their quality was assessed by scratch testing and by measuring density, refractory index, and extinction coefficient for different power management strategies. The strong influence of pulse parameters on the coating properties was observed, resulting in a maximum density of 3.6 g/cm³ and a refractive index of 1.68 for deposition modes with higher duty cycle values. Therefore, adjusting the pulse-on and pulse-off periods in MPPMS can be used not only to optimize the deposition rate but also as a tool to tune the optical characteristics of the films. The performance of the studied deposition method was evaluated by comparing the specific growth rates of alumina coatings with the relevant data for other magnetron discharge modes. In MPPMS, a specific deposition rate of 200 nm/min/kW was obtained for highly transparent Al₂O₃, without using any dedicated feedback loop system for oxygen pressure stabilization, which makes MPPMS superior to short-pulse high-power impulse magnetron sputtering (HiPIMS) modes. Full article

High-quality measurements of air quality are the highest priority for understanding widespread air pollution. Visibility has been widely suggested to be a good alternative to PM_2.5 concentration as a measure. In this study, the similarities and differences between visibility and PM_2.5 measurements in China are checked and the results reveal the potential application of visibility observation to the study of air quality. Based on the quality-controlled PM_2.5 and visibility data from 2016 to 2018, the nonparametric Spearman correlation coefficient (ρ) values between stations for PM_2.5 and visibility-derived surface extinction coefficient (b_ext) decrease as the station distance (R) increases. Some relatively low ρ values (<0.4) occur in regions characterized by the lowest (background) levels of PM_2.5 and b_ext values, for example, the Tibetan and Yungui Plateau. The relatively lower ρ for b_ext compared to PM_2.5 is probably caused by the predefined maximum threshold of visibility measurements (generally 30 km). A significant correlation between PM_2.5 and b_ext is derived in most stations and relatively larger ρ values are evident in eastern China (Northeast China excluded) and in winter (the national median ρ is 0.67). The abrupt changes in specific mass extinction efficiency (α_ext) imply a potentially large influence of alternation of visibility sensors or recalibrations on visibility measurements. The b_ext data are thereafter corrected by comparison to the reference measurements at the adjacent stations, which leads to a three-year quality assured of visibility and b_ext datasets. Full article

A series of cone calorimetry experiments and simultaneous gravimetric sampling and light extinction (GSLE) measurements were performed to determine the optical properties (light obscuration and extinction characteristics) of smoke particulates produced from burning polymers. The polymer selected in the present study was acrylonitrile-butadiene styrene (ABS), which has a moderate smoke yield during combustion, and unplasticized polyvinyl chloride (UPVC), which has a lower smoke yield than ABS. The experiments show that the measured light obscuration for UPVC smoke particles is much lower than that for ABS smoke particles because of the low rate of smoke production during combustion. Results from the simultaneous GSLE measurements demonstrate more clearly that UPVC smoke particles represent a lower efficiency of light obscuration on a per-unit smoke mass basis, resulting in a 41.3% reduction in a mass specific extinction coefficient compared to the ABS smoke particles. Numerical analysis was performed to further elucidate the effect of optical properties on the smoke behavior using the Fire Dynamics Simulator (FDS) (Version 6.7.1, National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA). The numerical results clearly demonstrated that the UPVC combustion, with its relatively low heat release rate and mass specific extinction coefficient, caused a significant delay in detecting a fire with a smoke detector compared to ABS combustion. Full article

A remote sensing-integrated crop model (RSCM) able to simulate crop growth processes using proximal or remote sensing data was formulated for simulation of soybean through estimating parameters required for modelling. The RSCM-soybean was then evaluated for its capability of simulating leaf area index (LAI), above-ground dry mass (AGDM), and yield, utilising the proximally sensed data integration into the modelling procedure. Field experiments were performed at two sites, one in 2017 and 2018 at Chonnam National University, Gwangju, and the other in 2017 at Jonnam Agricultural Research and Extension Services in Naju, Chonnam province, South Korea. The estimated parameters of radiation use efficiency, light extinction coefficient, and specific leaf area were 1.65 g MJ⁻¹, 0.71, and 0.017 m² g⁻¹, respectively. Simulated LAI and AGDM values agreed with the measured values with significant model efficiencies in both calibration and validation, meaning that the proximal sensing data were effectively integrated into the crop model. The RSCM reproduced soybean yields in significant agreement with the measured yields in the model assessment. The study results demonstrate that the well-calibrated RSCM-soybean scheme can reproduce soybean growth and yield using simple input requirement and proximal sensing data. RSCM-soybean is easy to use and applicable to various soybean monitoring projects. Full article

Particulate matter (PM) has a substantial influence on the environment, climate change and public health. Due to the limited spatial coverage of a ground-level PM_2.5 monitoring system, the ground-based PM_2.5 concentration measurement is insufficient in many circumstances. In this paper, a Specific Particle Swarm Extinction Mass Conversion Algorithm (SPSEMCA) using remotely sensed data is introduced. Ground-level observed PM_2.5, planetary boundary layer height (PBLH) and relative humidity (RH) reanalyzed by the European Centre for Medium-Range Weather Forecasts (ECMWF) and aerosol optical depth (AOD), fine-mode fraction (FMF), particle size distribution, and refractive indices from AERONET (Aerosol Robotic Network) of the Beijing area in 2015 were used to establish this algorithm, and the same datasets for 2016 were used to test the performance of the SPSEMCA. The SPSEMCA involves four steps to obtain PM_2.5 values from AOD datasets, and every step has certain advantages: (I) In the particle correction, we use η_2.5 (the extinction fraction caused by particles with a diameter less than 2.5 μm) to make an accurate assimilation of AOD_2.5, which is contributed to by the specific particle swarm PM_2.5. (II) In the vertical correction, we compare the performance of PBLHc retrieved by satellite Lidar CALIPSO data and PBLHe reanalysis by ECMWF. Then, PBLHc is used to make a systematic correction for PBLHe. (III) For extinction to volume conversion, the relative humidity and the FMF are used together to assimilate the AVEC (averaged volume extinction coefficient, μm²/μm³). (IV) PM_2.5 measured by ground-based air quality stations are used as the dry mass concentration when calculating the AMV (averaged mass volume, cm³/g) in humidity correction, that will avoid the uncertainties derived from the estimation of the particulate matter density ρ. (V) Multi-Angle Implementation of Atmospheric Correction (MAIAC) 1 km × 1 km AOD was used to retrieve high resolution PM_2.5, and a LookUP Table-based Spectral Deconvolution Algorithm (LUT-SDA) FMF was used to avoid the large uncertainties caused by the MODIS FMF product. The validation of PM_2.5 from the SPSEMCA algorithm to the AERONET observation data and MODIS monitoring data achieved acceptable results, R = 0.70, RMSE (root mean square error) = 58.75 μg/m³ for AERONET data, R = 0.75, RMSE = 43.38 μg/m³ for MODIS data, respectively. Furthermore, the trend of the temporal and spatial distribution of Beijing was revealed. Full article

High-resolution X-ray computed tomography is employed to obtain the exact 3D geometrical configuration of porous anisotropic ceria applied in solar-driven thermochemical cycles for splitting H2O and CO2. The tomography data are, in turn, used in direct pore-level numerical simulations for determining the morphological and effective heat/mass transport properties of porous ceria, namely: porosity, specific surface area, pore size distribution, extinction coefficient, thermal conductivity, convective heat transfer coefficient, permeability, Dupuit-Forchheimer coefficient, and tortuosity and residence time distributions. Tailored foam designs for enhanced transport properties are examined by means of adjusting morphologies of artificial ceria samples composed of bimodal distributed overlapping transparent spheres in an opaque medium. Full article