Average Reflectance Values Research Articles

Formation and radiolytic alteration of uraniferous solid bitumen related to hydrothermal base-metal mineralization in the Bytíz deposit, Příbram district, Czech Republic

The Bytíz deposit is a part of the Příbram uranium and base-metal ore district. It is an example of a vein-type deposit with polyphase hydrothermal mineralization. Samples of uraniferous solid bitumen from Bytíz with U content up to 38 wt% are characterized petrologically, geochemically, and mineralogically using EPMA, Raman and infrared microspectroscopy. The bitumen-bearing samples consist of base-metal sulfides: galena, sphalerite, pyrite, chalcopyrite, and also minor amounts of tetrahedrite, stibnite, and acanthite, associated with Mn-bearing calcite, quartz and silicates (chlorite, muscovite). Solid bitumens were found in the form of small veins and droplets, and roundish to irregular accumulations, in association with uraninite and carbonate veins.U-bearing minerals in the studied samples are represented by uraninite and more rarely by coffinite. Three generations of uraninite in association with solid bitumen were distinguished: 1. spherulites and large grains, filled with organic phase in the cracks; 2. as a part of complex textures inside areas with organic matter; in this case, the uraninite was assumed to have been remobilized; and 3. small inclusions in the latest calcite veins.More than 80 vol% of the solid bitumen from the vein fillings appeared to be radiolytically altered. Radiolytic alteration results in changes in optical properties and in composition, and in the formation of various textures around uraninite grains: halos, and irregular textures from simple massive to flow, dendritic, and fractured to a very complex morphology. The random reflectance values of unaltered mineral-free bitumen range from 0.45% to 0.99%, while in the radiolytically altered bitumen the average reflectance values are higher, from approximately 1.72% to 3.44%.The degree of graphitization of the organic matter was assessed by infrared micro-spectroscopy. Spectral maps show significant destruction changes of the aliphatic CH bonds and an increase in the content of oxygen functional groups in the vicinity of U minerals.On the element distribution maps, obtained by EPMA, the distribution of S, U, Pb and other elements across solid bitumen in the vicinity of uraninite and coffinite has a very heterogeneous character. An elevated content of sulfur in bitumen was also found, as well as a clear interdependence between S and C. It is suggested that the presence of sulfur in solid bitumen may result in ‘clouding’ of the solid bitumen with tiny stibnite grains. The dark rims of the halos observed under the optical microscope may be due to an elevated U content at the rims around the uraninite.Based on analysis of complex textural relationships of the solid bitumens with coexisting minerals, the formation of solid bitumen in association with uraninite is therefore assumed to relate to several stages of the influx of hydrothermal fluid. The temperature of the fluid, associated with bitumen formation was estimated to be up to 270 °C, according to chlorite thermometry.

Conformal Antireflective Multilayers for High‐Numerical‐Aperture Deep‐Ultraviolet Lenses

AbstractPrecise surface reflectance control at specific deep‐ultraviolet (DUV) wavelengths across wide angles is crucial for semiconductor inspection and lithography tools. The inherent challenges in designing DUV antireflective multilayers stem from limited transparent materials and the resultant fabrication complexity owing to numerous interfaces. Here, wide‐angle antireflective multilayers finely tuned to 248 nm designed using an active learning scheme is presented. The active learning scheme employing factorization machines (FM) identifies the optimal configurations for binary‐material‐based multilayers (AlF3/LaF3, AlF3/MgF2, and AlF3/Al2O3) with varying index contrasts, achieving minimal figure‐of‐merit (i.e., average angular reflectance) values at predetermined total thicknesses. High‐index‐contrast AlF3/Al2O3 multilayers are fabricated via atomic layer deposition, thus enabling the conformal coating of high‐numerical‐aperture (NA) lenses with atomic precision. An optimized AlF3/Al2O3 tri‐layer with a total thickness of 180 nm results in an average (0°–45°) reflectance of 0.4% on a CaF2 planar substrate and 0.6% on a CaF2 convex lens (NA = 0.47), similar to the performance of an ideal single‐layer coating requiring a practically unavailable refractive index. Phasor analysis, which considers only first‐order reflections between adjacent layers, supports the benefits of high‐index‐contrast binary materials and the use of the FM‐based active learning scheme in antireflective multilayer design.

Combining Feature Selection Techniques and Neurofuzzy Systems for the Prediction of Total Viable Counts in Beef Fillets Using Multispectral Imaging

In the food industry, quality and safety issues are associated with consumers’ health condition. There is a growing interest in applying various noninvasive sensorial techniques to obtain quickly quality attributes. One of them, hyperspectral/multispectral imaging technique has been extensively used for inspection of various food products. In this paper, a stacking-based ensemble prediction system has been developed for the prediction of total viable counts of microorganisms in beef fillet samples, an essential cause to meat spoilage, utilizing multispectral imaging information. As the selection of important wavelengths from the multispectral imaging system is considered as an essential stage to the prediction scheme, a features fusion approach has been also explored, by combining wavelengths extracted from various feature selection techniques. Ensemble sub-components include two advanced clustering-based neuro-fuzzy network prediction models, one utilizing information from average reflectance values, while the other one from the standard deviation of the pixels’ intensity per wavelength. The performances of neurofuzzy models were compared against established regression algorithms such as multilayer perceptron, support vector machines and partial least squares. Obtained results confirmed the validity of the proposed hypothesis to utilize a combination of feature selection methods with neurofuzzy models in order to assess the microbiological quality of meat products.

Assessment of thermal maturity in Lower Cambrian organic-rich shale in south China using integrated optical reflectance and Raman spectroscopy of pyrobitumen

It is challenging to accurately determine the thermal maturity of Lower Cambrian overmature shale, which is widely distributed in South China. In this study, we report an integrated method of measuring optical reflectance and Raman spectroscopy of pyrobitumen to determine the thermal maturity of Lower Cambrian organic-rich shales that contained a highly aromatized organic matter chemical structure. The optical reflectance measurement was conducted on large-particle-size angular pyrobitumen to eliminate the interference of clay mineral matrix, and the Raman spectrum analysis is a statistical response of a highly thermally evolved pyrobitumen chemical structure. Raman analysis compensates for the limitation of optical anisotropy interference in optical reflectance measurements. There is a good agreement between optically measured pyrobitumen reflectance (PBRo) and pyrobitumen reflectance calculated by Raman parameters (RmcPBRo), reflecting only minimal effects of optical anisotropy on the average optical reflectance (PBRo) values of pyrobitumen with fine or irregular mosaic texture, further indicating reliability of this integrated method for analyzing overmature shale. Thermal maturity varies significantly in the Lower Cambrian organic-rich shales, ranging from 2.60 to 2.92% EqVRo in the western Hubei province (WHBP), 2.98–3.49% EqVRo in the southern Shaanxi province (SSXP), 3.20–3.38% EqVRo in the southern Sichuan province (SSCP) and 4.06–4.31% EqVRo in the southeastern Chongqing (SECQ). The degree of aromatization and the structural order of organic matter (OM) are abruptly intensified when thermal maturity reaches about 3.5–3.7% EqVRo, as indicated by the deconvolution of the D and G bands in the Raman spectrum of pyrobitumen. The abrupt change in chemical structure of OM provides evidence for further dividing the early and late stages of overmaturation at a boundary of 3.5–3.7% EqVRo. The Lower Cambrian organic-rich shales distributed in the Cambrian shale gas breakthrough areas are normally at the early stage of overmaturation (2.0% < EqVRo < 3.5–3.7%). Development of paleo-uplifts in the Cambrian shale gas breakthrough areas led to relatively shallow burial depth of Lower Cambrian shale distributed on the peripheral areas of paleo-uplifts and created favorable shale gas preservation condition with only rare and small-scale faults.

Paleo-Wildfires and Their Paleoclimatic Effects in Early Permian Coal in the Southern North China Basin.

Paleo-wildfires can help elucidate the transition trends of Earth from "icehouse" to "greenhouse," thereby allowing us to forecast the current changes associated with wildfires of this era. In this study, the early Permian Shanxi Formation in the Pingdingshan coalfield, located south of the North China Basin, was selected as a study site. Based on data on inertinite content, inertinite reflectance, nine polycyclic aromatic hydrocarbons (PAHs), paleo-wildfires, and their paleoclimate effect during the early Permian coal formation were systematically analyzed. The inertinite content in coal in the study area ranged from 9.76 to 29.65%, with an average of 19.32%. Meanwhile, the average inertinite reflectance values ranged from 2.41-4.74%, with an average of 2.75%. PAHs in the study area were mainly tricyclic and tetracyclic; the contents of fluorene, phenanthrene, pyrene, bypyrene, benzo[b]fluoranthene, and benzo[e]pyrene were higher than those of other PAHs in the same stratum. The total concentration of PAHs varied widely between layers (3601-21,894 ng/g). The presence of paleo-wildfires was confirmed by the contents of inertinite and PAHs. It can be concluded that paleo-wildfires in the study area were dominated by surface fires at low and medium temperatures based on the combustion equation. The oxygen content in the paleo-atmosphere of the Early Permian Shanxi Formation in the study area was 24.29%, which provided the necessary conditions for the occurrence of wildfires.

All‐Glass Metasurfaces for Ultra‐Broadband and Large Acceptance Angle Antireflectivity: from Ultraviolet to Mid‐Infrared

AbstractFor many optics technologies, such as display screens, solar cells, laser systems, and eyeglasses, antireflective (AR) coatings are well integrated; these applications frequently benefit from the ability to function as broadband AR. Here, all‐glass metasurfaces are reported on, exhibiting a measured reflectance of 0.18% ± 0.23% per interface, averaged across wavelengths spanning from 350 nm (ultraviolet) to 2350 nm (mid‐infrared); to the best of knowledge, this is the first‐ever demonstration of an AR layer capable of this. Furthermore, acceptance angles up to 100° (angle of incidence = ±50°) results in %R &lt; 0.6% per interface over the band 350–1300 nm for P‐polarization and S‐polarization, with wavelength averaged reflectance values 0.04% ± 0.05% and 0.11% ± 0.15%, respectively – another technological first. The process advancements presented here allow for reflectance suppression over a broad range of wavelengths, angles, and polarizations.

Spectroscopic Characterization of Impactites and a Machine Learning Approach to Determine the Oxidation State of Iron in Glass‐Bearing Materials

AbstractWe investigated a suite of impact glass‐bearing rocks using a multi‐analytical approach including visible‐near‐infrared diffuse reflectance spectroscopy, Mössbauer spectroscopy, and powder X‐ray diffraction. In order to better understand and interpret the obtained results, we built a database containing physical, chemical, and spectroscopic information on glasses and glass‐bearing materials using new results from this study and published works. We used the database to explore systematic relationships between parameters of interest and finally we applied several machine learning algorithms (support vector machine, random forests, and gradient boosting) to test the possibility to regress the oxidation state of iron from chemical and spectroscopic information. Our results show that even small amounts of mafic crystalline phases have a big influence on the spectral features of glass‐bearing rocks. Samples without mafic crystalline inclusions show the typical spectrum of glasses (two broad and shallow bands roughly centered around 1,100 and 1,900 nm) with minor variations due to bulk chemistry. We described a non‐linear relationship between average reflectance (average reflectance value between 500 and 1,000 nm), FeO + TiO2 content, grain size, and Fe3+/FeTOT. We tested the relation for the finer grain size (0–25 μm), and we qualitatively assessed how it is affected by grain size, Fe3+/FeTOT, and crystal content. Finally, we developed a machine learning pipeline to regress the Fe3+/FeTOT of glass‐bearing materials using the proposed database. Our machine learning calculations give satisfactory results (MAE: 0.0321) and additional data will enable the application of our computational strategy to remotely acquired data to extract chemical and mineralogical information of planetary surfaces.

Simulation of CdS/p-Si/p+-Si and ZnO/CdS/p-Si/p+-Si heterojunction solar cells

In this study, the antireflection effect of CdS and ZnO/CdS layers was investigated via computing and solar cell I-V graphs and efficiency of the solar cell is simulated using the SCAPS. The lowest average reflectance value for single layer CdS was calculated as 13.43 %, for ZnO/CdS double layer 9.46 %. The efficiency values of CdS/p-Si/p+-Si and ZnO/CdS/p-Si/p+-Si heterojunction solar cells were calculated by changing the CdS and ZnO thicknesses from 40 nm to 80 nm. The highest efficiency value for the CdS/p-Si/p+-Si structure was calculated as 20.30 %. The efficiency value for the ZnO/CdS/p-Si/p+-Si heterojunction solar cell was increased to 21.82 % with the effect of the ZnO layer.

Petroleum source rock evaluation of organic black shales in the Paleogene N'kapa Formation, Douala Basin, Cameroon

Black shales outcropping in the Douala Basin were studied using organic petrography and Rock-Eval pyrolysis. The goal of this study was to use organic petrography and bulk geochemical analysis to evaluate N'kapa Formation shales in terms of organic matter (macerals) composition and its relationship to oil and gas productivity potentials. The quantity of organic matter, kerogen type and thermal maturity were determined, and their relationship to oil and gas generation was evaluated. The results of this investigation indicate that the nine samples analyzed had average random vitrinite reflectance values (VRo random) between 0.48 and 0.57% and are indicative of immature source rocks. Calculated maximum reflectance values (VRo maximum) ranged from 0.50 to 0.59%, showing a maximum volatile C bituminous rank and Liptinite macerals were found to fluoresce in the yellow-green to the yellow range, which is consistent with the indicated rank. The total organic carbon (TOC) of the samples ranges from 0.55 to 2.23 wt% (average of 1.18 wt%), implying fair to good concentration of organic matter, while the S1 values range from 0.04 to 0.10 mg HC/g rock (average of 0.07 mg HC/g rock) and S2 values range from 0.10 to 0.91 mg HC/g rock (average of 0.38 mg HC/g rock) and are described as showing poor source potential. Based on Genetic Potential (GP = S1+S2) values (0.18-1.01 mg HC/g rock), the studied N'kapa Formation shales are dominated by type III gas-prone kerogen with a minor association of type IV kerogen. The hydrogen index (HI<50mg HC/g TOC) and oxygen index (OI<75mg CO2/g TOC) values are too low for the shales to have generated hydrocarbons. The low values HI and OI and the absence of type II and mixed type II/III may be due to some degree of weathering of the samples.

Taguchi method and Box-Behnken design approach for process parameter optimization of magnetite (Fe3O4) coating developed on stainless steel 410 grade by hot alkaline treatment

The blackening of materials is widely used in the automobile industry, defense applications, aerospace applications, and solar applications. Methods such as electroless chemical process, conversion coating, physical vapor deposition, chemical vapor deposition, and diamond-like carbon are some of the commonly employed techniques to produce black coatings on various metals. Hot aqueous alkaline treatment is a chemical conversion coating process. In this study, hot alkaline treatment is used to blacken surgical equipment made of stainless steel 410, which is a novel approach. The effect of process variables such as immersion time, salt solution temperature, and wt% of sodium dichromate on the anti-reflective property of ferrous ferric oxide (magnetite, Fe3O4) coating has been optimized using the Taguchi method and response surface methodology. The experiments were designed using a Taguchi orthogonal array and a Box-Behnken design. The influences of coating parameters on average percentage reflectance were quantified by the signal-to-noise ratio, main effect plot, analysis of variance, and two-dimensional and three-dimensional plots. The comparison of experimental and confirmatory tests shows that both procedures optimized the parameters successfully. The lowest average percentage reflectance value of 8.013% was obtained at 56.976 min immersion time, 124.998°C salt solution temperature, and 348.689 g/l wt% of sodium dichromate in the composition by Box-Behnken design methodology.

Wide-angle broadband antireflection coatings with nano-taper hydrated alumina film.

Wide-angle and broadband antireflection (AR) coating is of the essence in modern optical systems in many fields, which has a great influence on the stray light and imaging quality. A simple and convenient manufacturing method is proposed to address this issue based on a composite coating combining the nano-tapered Al2O3•xH2O (AH) structure and high-low index thin film stack. The optical properties of nano-tapered AH structure at various thickness are first studied and modeled in optics by several homogeneous sub-layers with the graded equivalent index. The designed composite AR coatings are manufactured by vacuum deposition and wet etching subsequently in the hot deionized water. Compared to the common dielectric multilayer antireflection stack, the composite coating presents excellent AR performance. The measured average reflectance values of the double-side coated BK7 glass are as low as 0.40%, 0.41%, 0.56% and 3.13% in 400-1100nm band at angles of incidence (AOI) of 6°, 20°, 40°, and 60°, respectively, while the measured average transmittance at normal incidence increases up to 99.3%. Finally, the process reproductivity, environmental reliability test including long term storage, high temperature annealing and 85°C-85% relative humidity storage of the composite coatings are evaluated. The proposed AR scheme provides a low-cost, efficient, wide-angle and broadband AR coating for kinds of large-curvature components and complex surfaces in fields of consumer electronics, automotive, security, etc.

Fabrication of high-transmittance and low-reflectance meter-scale moth-eye film via roll-to-roll printing

Anti-reflection technology is a core technology in the field of optoelectronic devices that is used to increase efficiency by reducing reflectance. In particular, the bio-mimetic moth-eye pattern has the advantage of being independent of wavelength, polarization, and angle of incidence. In this study, we fabricated a 1.1 m wide meter-scale moth-eye film using roll-to-roll printing. A uniform moth-eye pattern with a height of 170 nm was formed, which reduced the average reflectance value by 3.2% and increased the average transmittance value by 3.1%, in a wide wavelength range of 400–700 nm. Additionally, the moth-eye film coated with a self-assembled monolayer (SAM) exhibited a contact angle of 140.3°, almost equal to the superhydrophobic angle of 150°. Furthermore, the contact angle, transmittance, and reflectance of the SAM-coated moth-eye film were maintained after an environmental test, which was conducted for 168 h at 60 °C and 80% humidity.

Identification of Cold Spots Using Non-Destructive Hyperspectral Imaging Technology in Model Food Processed by Coaxially Induced Microwave Pasteurization and Sterilization.

The model food in this study known as mashed potato consisted of ribose (1.0%) and lysine (0.5%) to induce browning via Maillard reaction products. Mashed potato was processed by Coaxially Induced Microwave Pasteurization and Sterilization (CiMPAS) regime to generate an F0 of 6–8 min and analysis of the post-processed food was done in two ways, which included by measuring the color changes and using hyperspectral data acquisition. For visualizing the spectra of each tray in comparison with the control sample (raw mashed-potato), the mean spectrum (i.e., mean of region of interest) of each tray, as well as the control sample, was extracted and then fed to the fitted principal component analysis model and the results coincided with those post hoc analysis of the average reflectance values. Despite the presence of a visual difference in browning, the Lightness (L) values were not significantly (p < 0.05) different to detect a cold spot among a range of 12 processed samples. At the same time, hyperspectral imaging could identify the colder trays among the 12 samples from one batch of microwave sterilization.

A low cost additive-free acid texturing process for large area commercial diamond-wire-sawn multicrystalline silicon solar cells

Diamond-wire-sawing (DWS) technique allows slicing of silicon ingots to produce wafers at cheaper price due to its reduced kerf-loss and increased cutting rate. However, there is no cost-effective and industrially viable method available for texturing DWS wafers, especially for multicrystalline silicon (mc-Si) wafers. Currently additive-based acid texturing process is availed by PV manufacturing units for texturing DWS mc-Si wafers. An additive-free, low cost and energy-efficient acid texturing process is demonstrated for DWS mc-Si wafers in industrial production line. Nearly 10% absolute reduction in weighted average reflectance values (WAR) are noticed for the newly textured wafers from that of as-cut DWS mc-Si wafers and the WAR values are comparable to that of existing additive-based acid textured mc-Si wafers. An absolute reduction in emitter saturation current density by ~17 fA-cm-2 and improved implied open circuit voltage of ~5 mV (absolute) are reported for lifetime sample fabricated using newly textured wafers when compared to the additive-based acid textured lifetime samples. An impressive batch average efficiencies of 18.20% and 18.24% are achieved for the additive-free and existing additive-based acid textured mc-Si cells, respectively. Detailed analysis conclude that ~1.5% (relative) enhancement in short circuit current density can be achieved by further process optimization. Cost analysis indicates that 60% of the chemical cost involved the texturing process can be cut down by replacing the existing additive-based acid process with the new method using the same process equipment. Hence, the texturing process presented has great potential for producing large area high efficiency mc-Si cells favoring cost considerations without compromising performance.

Night-based hyperspectral imaging to study association of horticultural crop leaf reflectance and nutrient status

In the literature of hyperspectral remote sensing to assess nutrient status in crops, there is a general lack of studies conducted under greenhouse conditions. This may be attributed to technical issues associated with inconsistent lighting conditions during daytime data acquisitions due to shadows and spectral scattering inside greenhouse structures. In this proof-of-concept study, we developed a novel night-based hyperspectral remote sensing system with attached halogen lighting to study leaf reflectance of bok choy [Brassica rapa L. var Chinensis] and spinach [Spinacia oleracea L. ‘Correnta”] grown under high, medium and low fertilization regimes. The study objectives were to: 1) identify spectral regions in which average leaf reflectance values could be used accurately to characterize crop responses to overall fertilizer regimes, and 2) characterize consistency across crops of associations between crop leaf reflectance and levels of individual macronutrient elements. Our findings were: 1) leaf reflectance could be used to differentiate low versus medium/high fertilization regimes with 75% (bok choy) and 80% (spinach) accuracy, and 2) the following spectral regions: 700–709 nm, 780–787 nm and 817–821 nm were associated with N, K, Mg and Ca levels in bok choy and spinach. Based on comprehensive sensitivity analysis, we demonstrated that classification accuracy was highly similar when 50–80% of the crop reflectance data were used as training data, indicating robustness of the proposed linear discriminant classification models. We believe the proposed sensitivity analysis has broad relevance as a method to thoroughly examine the robustness of reflectance-based algorithms that are used to classify agricultural products.

Dust Deposited on Snow Cover in the San Juan Mountains, Colorado, 2011–2016: Compositional Variability Bearing on Snow‐Melt Effects

AbstractLight‐absorbing particles in atmospheric dust deposited on snow cover (dust‐on‐snow, DOS) diminish albedo and accelerate the timing and rate of snow melt. Identification of these particles and their effects is relevant to snow‐radiation modeling and water‐resource management. Laboratory‐measured reflectance of DOS samples from the San Juan Mountains (USA) were compared with DOS mass loading, particle sizes, iron mineralogy, carbonaceous matter type and content, and chemical compositions. Samples were collected each spring for water years 2011–2016, when individual dust layers had merged into one (all layers merged) at the snow surface. Average reflectance values of the six samples were 0.2153 (sd, 0.0331) across the visible wavelength region (0.4–0.7 μm) and 0.3570 (sd, 0.0498) over the full‐measurement range (0.4–2.50 μm). Reflectance values correlated inversely to concentrations of ferric oxide, organic carbon (1.4–10 wt.%), magnetite (0.05–0.13 wt.%), and silt (PM63‐3.9; median grain sizes averaged 21.4 μm) but lacked correspondence to total iron and PM10 contents. Measurements of reflectance and Mössbauer spectra and magnetic properties indicated that microcrystalline hematite and nano‐size goethite were primarily responsible for diminished visible reflectance. Positive correlations between organic carbon and metals attributed to fossil‐fuel combustion, with observations from electron microscopy, indicated that some carbonaceous matter occurred as black carbon. Magnetite was a surrogate for related light‐absorbing minerals, dark rock particles, and contaminants. Similar analyses of DOS from other areas would help evaluate the influences of varied dust sources, wind‐storm patterns, and anthropogenic inputs on snow melt and water resources in and beyond the Colorado River Basin.

Remote Sensing Monitoring of Vegetation Dynamic Changes after Fire in the Greater Hinggan Mountain Area: The Algorithm and Application for Eliminating Phenological Impacts

Fires are frequent in boreal forests affecting forest areas. The detection of forest disturbances and the monitoring of forest restoration are critical for forest management. Vegetation phenology information in remote sensing images may interfere with the monitoring of vegetation restoration, but little research has been done on this issue. Remote sensing and the geographic information system (GIS) have emerged as important tools in providing valuable information about vegetation phenology. Based on the MODIS and Landsat time-series images acquired from 2000 to 2018, this study uses the spatio-temporal data fusion method to construct reflectance images of vegetation with a relatively consistent growth period to study the vegetation restoration after the Greater Hinggan Mountain forest fire in the year 1987. The influence of phenology on vegetation monitoring was analyzed through three aspects: band characteristics, normalized difference vegetation index (NDVI) and disturbance index (DI) values. The comparison of the band characteristics shows that in the blue band and the red band, the average reflectance values of the study area after eliminating phenological influence is lower than that without eliminating the phenological influence in each year. In the infrared band, the average reflectance value after eliminating the influence of phenology is greater than the value with phenological influence in almost every year. In the second shortwave infrared band, the average reflectance value without phenological influence is lower than that with phenological influence in almost every year. The analysis results of NDVI and DI values in the study area of each year show that the NDVI and DI curves vary considerably without eliminating the phenological influence, and there is no obvious trend. After eliminating the phenological influence, the changing trend of the NDVI and DI values in each year is more stable and shows that the forest in the region was impacted by other factors in some years and also the recovery trend. The results show that the spatio-temporal data fusion approach used in this study can eliminate vegetation phenology effectively and the elimination of the phenology impact provides more reliable information about changes in vegetation regions affected by the forest fires. The results will be useful as a reference for future monitoring and management of forest resources.

A New Vegetation Index to Detect Periodically Submerged Mangrove Forest Using Single-Tide Sentinel-2 Imagery

Mangrove forests are tropical trees and shrubs that grow in sheltered intertidal zones. Accurate mapping of mangrove forests is a great challenge for remote sensing because mangroves are periodically submerged by tidal floods. Traditionally, multi-tides images were needed to remove the influence of water; however, such images are often unavailable due to rainy climates and uncertain local tidal conditions. Therefore, extracting mangrove forests from a single-tide imagery is of great importance. In this study, reflectance of red-edge bands in Sentinel-2 imagery were utilized to establish a new vegetation index that is sensitive to submerged mangrove forests. Specifically, red and short-wave near infrared bands were used to build a linear baseline; the average reflectance value of four red-edge bands above the baseline is defined as the Mangrove Forest Index (MFI). To evaluate MFI, capabilities of detecting mangrove forests were quantitatively assessed between MFI and four widely used vegetation indices (VIs). Additionally, the practical roles of MFI were validated by applying it to three mangrove forest sites globally. Results showed that: (1) theoretically, Jensen–Shannon divergence demonstrated that a submerged mangrove forest and water pixels have the largest distance in MFI compared to other VIs. In addition, the boxplot showed that all submerged mangrove forests could be separated from the water background in the MFI image. Furthermore, in the MFI image, to separate mangrove forests and water, the threshold is a constant that is equal to zero. (2) Practically, after applying the MFI to three global sites, 99–102% of submerged mangrove forests were successfully extracted by MFI. Although there are still some uncertainties and limitations, the MFI offers great benefits in accurately mapping mangrove forests as well as other coastal and aquatic vegetation worldwide.

Metal-Based Graphical SiO₂/Ag/ZnS/Ag Hetero-Structure for Visible-Infrared Compatible Camouflage.

A brand-new approach to realizing visible-infrared compatible camouflage is proposed based on a metal-based graphical hetero-structure (MGHS) SiO2/Ag/ZnS/Ag. For different thicknesses (20, 40, and 60 nm) of color-controlling sub-layer, high-contract and large-span structure colors (yellow, navy, and cyan) were observed due to reintroducing constructive interference with a matching intensity of reflected waves. Ultra-low infrared emissivity values of 0.04, 0.05, and 0.04 (with high average reflectance values of 95.46%, 95.31%, and 95.09%) were obtained at 3–14 μm. In addition, the well-performing trisecting-circle structure further indicates that it is feasible to design on-demand compatible camouflage patterns using the easily-prepared MGHS.

A Front Surface Optimization Study for Photovoltaic Application

In this paper, we presented a possible front surface optical enhancement of Si solar cell by optimizing the Antireflection (AR) and light trapping (LT) schemes. Conventional plasma enhanced chemical vapor deposition (PECVD) and in house hot wire chemical vapor deposition (HWCVD) tool was used to deposit Silicon Nitride (SiNX) layer and optimized at 668nm wavelength. This was followed by surface texturing of random pyramids to further enhance the broadband reflectance of the front surface. Broadband reflectance measurement using integrating sphere method showed achieved weighted average reflectance (WAR) value of as low as 1.8% and 1.5%, when 85nm SiNX was deposited on top of random pyramids structure using HWCVD and PECVD methods, respectively.