Optical Surface Reflectance Research Articles

Rapid anisotropic chemical etching for quick formation of novel octagonal pyramids on silicon surface for photovoltaics

A novel octagonal micro pyramid structure was formed by etching a monocrystalline silicon wafer (100) by employing a wet chemical anisotropic etching process. The main objective is to reduce the silicon wafer's front surface reflectance, improve surface morphology, enhance wettability, and increase the coverage area of the octagonal pyramids on the surface of silicon wafers. The reaction time of the etching process was kept precise under strict observation and control. The experimental results demonstrate a significant reduction in silicon wafers' optical surface reflectance, achieving the lowest reflectance of 8.87%, along with improved surface morphology, periodicity, and coverage of more than 88%. While adding hydrofluoric acid together with magnetic stirring (mechanical agitation) at 300 rpm was advantageous in forming the octagonal silicon pyramid with a high etch rate of 0.41 um/min and significantly reducing the reaction time.

Deep-learning-based burned area mapping using the synergy of Sentinel-1&2 data

Around 350 million hectares of land are affected by wildfires every year influencing the health of ecosystems and leaving a trail of destruction. Accurate information over burned areas (BA) is essential for governments and communities to prioritize recovery actions. Prior research over the past decades has established the potentials and limitations of space-borne earth observation for mapping BA over large geographic areas at various scales. The operational deployment of Sentinel-1 and Sentinel-2 constellations significantly improved the quality and quantity of the imagery from the microwave (C-band) and optical regions on the spectrum. Based on that, this study set to investigate whether the existing coarse BA products can be further improved by the synergy of optical surface reflectance (SR), radar backscatter coefficient (BS), and/or radar interferometric coherence (COR) data with higher spatial resolutions. A Siamese Self-Attention (SSA) classification strategy is proposed for the multi-sensor BA mapping and a multi-source dataset is constructed at the object level for the training and testing. Results are analyzed by test sites, feature sources, and classification strategies to appraise the improvements achieved by the proposed method.

Estimation of root zone soil moisture from ground and remotely sensed soil information with multisensor data fusion and automated machine learning

Root zone soil moisture (RZSM) estimation and monitoring based on high spatial resolution remote sensing information such as obtained with an Unmanned Aerial System (UAS) is of significant interest for field-scale precision irrigation management, particularly in water-limited regions of the world. To date, there is no accurate and widely accepted model that relies on UAS optical surface reflectance observations for RZSM estimation at high spatial resolution. This study is aimed at the development of a new approach for RZSM estimation based on the fusion of high spatial resolution optical reflectance UAS observations with physical and hydraulic soil information integrated into Automated Machine Learning (AutoML). The H2O AutoML platform includes a number of advanced machine learning algorithms that efficiently perform feature selection and automatically identify complex relationships between inputs and outputs. Twelve models combining UAS optical observations with various soil properties were developed in a hierarchical manner and fed into AutoML to estimate surface, near-surface, and root zone soil moisture. The addition of independently measured surface and near-surface soil moisture information to the hierarchical models to improve RZSM estimation was investigated. The accuracy of soil moisture estimates was evaluated based on a comparison with Time Domain Reflectometry (TDR) sensors that were deployed to monitor surface, near-surface and root zone soil moisture dynamics. The obtained results indicate that the consideration of physical and hydraulic soil properties together with UAS optical observations improves soil moisture estimation, especially for the root zone with a RMSE of about 0.04 cm3 cm−3. Accurate RZSM estimates were obtained when measured surface and near-surface soil moisture data was added to the hierarchical models, yielding RMSE values below 0.02 cm3 cm−3 and R and NSE values above 0.90. The generated high spatial resolution RZSM maps clearly capture the spatial variability of soil moisture at the field scale. The presented framework can aid farm scale precision irrigation management via improving the crop water use efficiency and reducing the risk of groundwater contamination.

A tidal correction model for near-infrared (NIR) reflectance over tidal flats

We examined the temporal variation of near-infrared (NIR) reflectance over tidal flats by proposing a tidal correction model for NIR reflectance. Sediment type, exposure time and interstitial and remnant surface waters play a key role in the optical surface reflectance of tidal flats. We established a tidal correction model for NIR reflectance by analysing 1015 scenes from the Geostationary Ocean Color Imager (GOCI), which is the first ocean colour sensor mounted on a geostationary satellite. The GOCI provides eight scenes per day with a 500-m resolution. Our results yielded two main findings. First, the reflectance model shows an asymmetric shape between ebb and flood tides. As the surface reflectance increases gradually during the ebb tide, the slope decreases steeply during the flood tide. Second, at least two models showing surface sediment are required. The tidal correction models for sand- and mixed-flats were similar; however, the one for mud-flats differed significantly. Our models work to correct for the tidal flat reflectance shown in optical images that were acquired under different tidal conditions.

Post and <i>In Situ</i> Characterization of Strain Control and Crystal Quality in Quantum Well Solar Cell Structure

To improve current matching in a tandem solar cell, a strain-compensated InGaAs/GaAsP multiple quantum-wells (MQWs) structure was grown within the middle GaAs PN junction, using metal organic vapor phase epitaxy (MOVPE) on GaAs substrate. Aiming at an accurate design of adsorption edge and precise control of crystal quality in MQWs, post- and in situ characterization was applied in such a fabrication process. Here, we report some applications of some post-characterization such as: X-ray scanning and reciprocal mapping in clarifying composition and crystal quality in these structures; photoluminescence (PL) and FTIR in determining adsorption edge and even indicate some irradiative recombination features as well. By employing an in situ optical surface reflectivity measurement, we established a way of and evaluating an instant of strain relaxation in the course of MOVPE, which deteriorates crystal quality significantly. When strain balancing was incomplete, surface reflectivity dropped during the growth of MQWs, indicating lattice relaxation. The accumulated strain, which is defined as the average strain per period of QW multiply the number of stacking for MQWs , was roughly constant for all the MQWs samples in our experiment. Therefore, it may indicate that this overall strain may be used as a tentative criterion of critical value for lattice relaxation or to predict the maximum number of MQWs for a given value of the average strain per QW period. Combining both post and in situ characterizations, we can effectively adjust the overall strain to get defects free growth for MQWs, and also significant features can be observed for better understanding the heterostructure management.

In situ reflectance monitoring for the MOVPE of strain-balanced InGaAs/GaAsP quantum-wells

A strain-balanced InGaAs/GaAsP multiple quantum-wells (MQWs) structure was grown by metal organic vapor phase epitaxy (MOVPE) on GaAs substrate, aiming at a middle cell that improves current matching in a tandem solar cell. In order to detect the instant of strain relaxation in the course of MOVPE, which deteriorates crystal quality significantly, we employed in situ optical surface reflectivity measurement. When strain balancing was incomplete, surface reflectivity dropped during the growth of MQWs, indicating lattice relaxation. Such drop in surface reflectivity occurred at a smaller number of stacked quantum wells when the absolute value of an average strain per well/barrier pair was larger. The accumulated strain, i.e., the product between the average strain and the total thickness at the moment of reflectivity dropped, was roughly constant for all the MQWs, indicating a possibility that we can use this value as the measure to predict the maximum number of MQWs for a given value of the average strain. The reflectance anisotropy (RA) was also monitored in the course of the growth. The value of RA showed linear periodic behavior before the lattice relaxation, corresponding to the well/barrier stacks, suggesting that anisotropy of surface atoms reflects accumulated strain of the growth surface.

Broadband Optical Antireflection of Plastic Optics by Molded Stochastic Sub-wavelength Structures

Stochastic sub-wavelength structures with lateral sizes of below 100 nm and heights of about 250 nm were produced on polymer surfaces by plasma treatment. From these master samples, an embossing nickel tool was manufactured, which, in turn, was used to replicate the master surface form by hot embossing in plastic materials. The geometry of the produced nanostructures was quantified by scanning electron microscopy. The optical surface reflectance of both the master and the replicated samples were measured in the visible wavelength range. A significant reduction of optical reflectance from the expected 4% of untreated surfaces, to less than 0.5% of the master samples, and to values between 1% and 2% of the replicated samples was achieved. The optical reflectance of the stochastic structures was calculated by a finite element-based rigorous solution of the Maxwell equations. The modeled results show a good agreement with experimental data.

Investigation on metallurgical properties and electromigration in AlCu metallizations for VLSI applications

The purpose of this study is to investigate the correlations between the deposition parameters, the resulting metallurgical properties, and finally the electromigration resistance of AlCu alloy films and line structures of different compositions and different multilayer sequences. The alloy films were either sputtered onto a physical vapour deposition Ti TiN diffusion barrier, or for selected samples, directly on the boron phosphorus silicon glass base layer. We investigated AlCu alloy films with 0.5, 1.0 and 2.0 at.% Cu content in comparison with the standard metallization AlSi 1.0Cu 0.5 used by Siemens, as a reference. For all alloy films investigated, the multilayer sequence is varied and the resulting properties are characterized afterwards. The results are compiled in a metallurgical data base with the following physical characterization properties: layer thickness, grain size, microhardness, wafer bow, optical surface reflectivity, and electrical resistivity. For selected samples electromigration tests, X-ray diffraction texture analysis, Auger electron spectroscopy, energy dispersive X-ray analysis, and scanning electron microscopy are applied. With the support of this data base we are able to obtain information about the correlation between microscopic and macroscopic properties of the investigated metallizations and multilayer structures, and especially about the specific influence on their electromigration resistance.