Waveband Region Research Articles

Y2O3:Eu3+@SiO2 nanocomposites as a convertor for a broadband solar‐blind UV photodetector

AbstractCore–shell nanocomposites have attracted extensive attention in the photoelectric field because of their improved material properties and the combination of multiple functions. Particularly, these nanocomposites exhibit tunable structure and excellent optical properties. Inspired by these unique features, a novel optically active nanocomposites, Y2O3:Eu3+@SiO2 with a core–shell structure, is designed and fabricated by a hydrothermal method and electrophoretic deposition. In addition, the Y2O3:Eu3+@SiO2 composite film is also successfully developed and applied as a spectral down‐converter in the solar‐blind ultraviolet (UV) waveband region of 200–280 nm. Moreover, a broadband solar‐blind UV photodetector device is elaborated and a notable enhancement in the UV sensitivity is achieved. The findings not only provide a new idea for the development of broadband solar‐blind UV photodetector but also extended the application range of core–shell nanocomposites in photonics.

Determination of starch and amylose contents in various cereals using common model of near-infrared reflectance spectroscopy

Near-infrared reflectance spectroscopy (NIRS) was used to determine the total starch and amylose contents in various kinds of cereals namely wheat, waxy rice, non-waxy rice, millet, sorghum, waxy maize, buckwheat, barley, and hulless oat. The partial least-squares (PLS) analysis and principal component regression (PCR) were used to establish the calibration models. PLS model achieved a better effect than PCR at 1100 - 2500 nm, and the coefficient of determination (R2) of the calibration and prediction sets were both higher than 0.9 after the best pre-treatment method, first derivative plus Savitzky-Golay. Additionally, the root mean square error (RMSE) was lower than 2.50, and the root mean square error of cross-validation (RMSECV) was less than 3.50 for starch. By comparing PLS models at different waveband regions, the optimal determination results for starch and amylose were obtained at 1923 - 1961 and 1724 - 1818 nm, respectively. NIRS was found to be a successful method to determine of the starch and amylose contents in various cereals.

Manipulating Nonlinear Optical Response via Domain Control in Nanocrystal-in-Glass Composites.

Nanocrystal-in-glass (NIG) is an exciting class of composites, because it can not only combine the advantages of crystal and glass materials but also potentially generate new physical phenomenon in a cooperative manner. Herein, the nonlinear light-matter interaction processes in a broad range of NIG composites homogeneously embedded with LiNbO3 are investigated. It is shown that, by rational control of the organization manner of crystal and glass phases, second-harmonic generation (SHG) can be precisely tuned. Importantly, an unusual SHG phenomenon, transverse SHG (TSHG), can be realized in the special region of the microstructure map combined with the features of high loading, nanoscale size, and homogenous distribution of nanocrystals. Furthermore, NIG composites exhibit broadband optical response, allowing TSHG in a wide waveband region to be achieved. Based on the above effects, the applications of the constructed NIG composite for precise measurement of the group velocity and duration of ultrashort optical pulses with femtosecond time scales are demonstrated. Indeed, the findings outline a fundamental principle to design NIG configurations for creating new properties, providing new directions for expanding the scope of NIG functional materials.

Hyperspectral response and quantitative estimation on soil aggregate characters

Soil aggregate stability can be used to describe soil structure quality. In contrast, the conventional determination for soil aggregate stability, relying on dry-sieving and wet-sieving methods, is too resource consuming, especially for mass soil samples covering a large-scale field. Exploring the application of hyperspectral technology will provide a rapid, efficient and alternative method for the estimation of soil aggregate characteristics. In this study, we collected 199 soil samples (0–15 cm soil depth) from the Loess Plateau regions in the south areas of Shanxi province in China. Afterwards, we analyzed the relationship between spectra in region of 350–2500 nm and seven soil aggregate characters. The quantitative models for each soil aggregate character were built and the sensitive wavebands were determined by using the method of partial least squares. The results showed there was a negative relationship between soil spectra and soil aggregate stability, and the extreme correlation coefficient could reach −0.60 and 0.62, respectively, indicating that soil spectra could produce a significant response on soil aggregate characteristic. The significant waveband regions for soil aggregate characters were 350–870, 1250–1360, 1885–2020, and 2215–2450 nm. The important wavelengths were around 427, 599, 1326, 1890, 1926, 2208, 2311, and 2336 nm, which were also confirmed by the consistent correlation between soil spectra and each aggregate character. In addition, the reliable models (R2 = 0.612–0.714; RPD = 1.584–1.796) were produced for most of the soil aggregate indicators, while percentage of aggregate destruction (PAD) led to the worst predictive model (R2 = 0.599; RPD = 1.261). Aggregate fractal dimension (D) character was proved as the perfect indicator for spectral monitoring of soil aggregate stability, mainly due to the two-fold interpretation functions to soil structure distribution and soil adhesion with organic matter and soil moisture. It indicated that hyperspectral technology provides an alternate method for soil aggregate characters, especially for a large area.

In situ and tunable structuring of semiconductor-in-glass transparent composite.

SummarySemiconductor-in-glass composites are an exciting class of photonic materials for various fundamental applications. The significant challenge is the scalable elaboration of composite with the desirable combination of tunable structure, high semiconductor loading ratio, and excellent transparency. Here we report that the topological engineering strategy via hybridization of the glass network former enables to surmount the aforementioned challenge. It not only facilitates the in situ precipitation of (Ga2-xAlx)O3 domains with continuously tunable composition but also allows to simultaneously refine the grain size and enhance the crystallinity. In addition, the composites exhibit excellent transparency and can host various active dopants. We demonstrate the attractive broadband optical response of the composite and achieve the pulse laser operation in mid-infrared waveband. The findings are expected to provide a fundamental principle of in situ modification in hybrid system for generation of high-performance semiconductor-in-glass composites.

Hyperspectral monitor on chlorophyll density in winter wheat under water stress

AbstractLack of water can lead lower chlorophyll concentrations and yields. Based on the hyperspectral reflectance of winter wheat (Triticum aestivum L.), we analyzed the relationship between the canopy hyperspectral reflectance and the water‐stressed winter wheat. The correlation analysis (CA), partial least squares regression (PLSR), and successive progressions algorithm (SPA) were used to extract the important bands. Then the hyperspectral estimation models for chlorophyll density (ChD) by characteristic variables were established. The results showed that the reflectance in the visible regions increased gradually with an increasing water stress. In the near‐infrared (NIR) region, reflectance decreased with stress intensity. We extracted five and seven important waveband regions by CA and PLSR. Then we extracted right and nine important bands through SMLR, and 11 important bands were extracted by the method of SPA. We found that 427, 434, 749, and 814 nm contained important information about ChD of winter wheat after water stress. The model established by CA+SMLR was generally realized, whereas the ChD estimation models established by PLSR+SMLR and SPA with multiple linear regression had better performance, and the performance of the validation model was accurate and robust. The results of this study could provide theoretical basis and practical reference for accurate estimation of ChD in winter wheat after water stress.

Multiphase Transition toward Colorless Bismuth-Germanate Scintillating Glass and Fiber for Radiation Detection.

The applications of scintillating fiber in high-resolution medical imaging, remote radiation monitoring, and microbeam radiation therapy have raised a growing demand of bismuth-germanate (BGO) glass fiber. However, the task of construction of colorless BGO glass fiber has been met with limited success. Here, we present a renewable process that can help to achieve BGO scintillating fiber, based on glass relaxation and crystallization mediated dissolution of unexpected Bi center. The experimental results indicate that the strategy can improve the optical transmittance up to more than 73.17% at 483 nm, which is ∼6.28 times higher than that of the conventional material. Importantly, the obtained nanostructured BGO exhibits bright visible luminescence under excitation with X-ray. Furthermore, it can host various types of rare-earth dopants, and the radiation-induced luminescence can be tuned in a wide waveband region from visible to infrared waveband. In addition, colorless BGO fiber with bright emission is also successfully constructed, and the radiation probing test demonstrates the achievement of ∼19.48 times improvement in the detection sensitivity. Our results highlight the approach based on the dynamic glass relaxation may provide new opportunities for construction of scintillating glass fiber and compact radiation fiber detector.

Double-layer broadband perfect metamaterial absorber and its potential for refractive index sensing

A simple structured broadband perfect metamaterial absorber (PMA) for visible-infrared spectrum is proposed. The PMA composed of a two-dimensional vanadium (V) cylinder array coated with a film of TiO2 and a V substrate is designed using finite-difference time-domain method. Theoretical simulation results show that the PMA exhibits nearly perfect absorption in a wide waveband region from 400 to 1600 nm. The PMA has another potential for refractive indices sensing when it is immersed in different surrounding dielectrics such as liquid and solution. Furthermore, a PMA sample is fabricated and the spectral responses of the PMA sample are measured. Owing to the good consistence of theoretical simulation results and experimental ones, the novel characteristics of the proposed PMA are experimentally demonstrated.

Estimating growth and photosynthetic properties of wheat grown in simulated saline field conditions using hyperspectral reflectance sensing and multivariate analysis

The timely estimation of growth and photosynthetic-related traits in an easy and nondestructive manner using hyperspectral data will become imperative for addressing the challenges of environmental stresses inherent to the agricultural sector in arid conditions. However, the handling and analysis of these data by exploiting the full spectrum remains the determining factor for refining the estimation of crop variables. The main objective of this study was to estimate growth and traits underpinning photosynthetic efficiency of two wheat cultivars grown under simulated saline field conditions and exposed to three salinity levels using hyperspectral reflectance information from 350–2500 nm obtained at two years. Partial least squares regression (PLSR) based on the full spectrum was applied to develop predictive models for estimating the measured parameters in different conditions (salinity levels, cultivars, and years). Variable importance in projection (VIP) of PLSR in combination with multiple linear regression (MLR) was implemented to identify important waveband regions and influential wavelengths related to the measured parameters. The results showed that the PLSR models exhibited moderate to high coefficients of determination (R2) in both the calibration and validation datasets (0.30–0.95), but that this range of R2 values depended on parameters and conditions. The PLSR models based on the full spectrum accurately and robustly predicted three of four parameters across all conditions. Based on the combination of PLSR-VIP and MLR analysis, the wavelengths selected within the visible (VIS), red-edge, and middle near-infrared (NIR) wavebands were the most sensitive to all parameters in all conditions, whereas those selected within the shortwave infrared (SWIR) waveband were effective for some parameters in particular conditions. Overall, these results indicated that the PLSR analysis and band selection techniques can offer a rapid and nondestructive alternative approach to accurately estimate growth- and photosynthetic-related trait responses to salinity stress.

Mid‐infrared luminesce of ZnS:Cr2+‐glass composite and fiber

AbstractCr2+‐doped materials with mid‐infrared (Mid‐IR) broadband luminescence are of fundamental importance for various applications, such as solid‐state lasers technology, biolabeling, optical telecommunication, and solar energy management. Especially, Cr2+‐doped glass has been considered as one of important material candidates. The major challenge is the precipitation of crystals doped with Cr2+ ions in glass. So, “crystals in glass composite” is an effective method to solve this issue. Here, we describe a ZnS:Cr2+ in borophosphate glass composite (CZPB) which exhibits Mid‐IR luminescence in the region from 1700 to 2900 nm with the full width at half maximum (FWHM) of about 690 nm. In addition, the materials can also be fabricated into fiber without obvious change in the characteristic luminescence band. The results provide new opportunities for the construction of the broadband fiber light source operating at Mid‐IR waveband region.

Multi-sensor mapping of honey bee habitats and fragmentation in agro-ecological landscapes in Eastern Kenya

Extensive land transformation leads to habitat loss, which directly affects and fragments species habitats. Such land transformations can adversely affect fodder availability for bees and thus colony strength with consequences for rural communities that use bee keeping as a livelihood option. Quantification of the landscape structure is thus critical if the linkages between the landscape and honey bee colony health are to be well understood. In this study, a random forest algorithm was used on dual-polarized multi-season Sentinel-1A (S1) synthetic aperture radar (SAR) and single season Sentinel-2A (S2) optical imagery to map honey bee habitats and their degree of fragmentation in a heterogeneous agro-ecological landscape in eastern Kenya. The dry season S2 optical imagery was fused with the S1 data and class-wise mapping accuracies (with and without radar) were compared. Relevant fragmentation indices representing patch sizes, isolation and configuration were thereafter generated using the fused imagery. The fused imagery recorded an overall accuracy of 86% with a kappa of 0.83 versus the SAR imagery only, which had an overall accuracy of 76% with a kappa of 0.68. However, the S1 imagery had slightly higher user’s and producer’s accuracies for under-represented but important honey bee habitat classes, that is, natural grasslands and hedges. The variable importance analysis using the fused imagery showed that the short-wave infrared and the red-edge waveband regions were highly relevant for the classification model. Our mapping approach showed that fusing data generated from S1 and S2 with improved spectral resolution, could be effectively used for the spatially explicit mapping of honey bee habitats and their degree of fragmentation in semi-arid African agro-ecological landscapes.

Tunable excitation in nitrided amorphous TiO2:Eu

Developing luminescent materials with broadband optical response is of fundamental importance for various applications, including photovoltaics, biological imaging and photonics. However, the task of engineering the optical excitation with tunable feature in doped luminescent materials has been met with limited success, owing to the limited space for modifying dopant-host interactions. Here, we present an effective strategy for control of the light-harvesting process, based on the collaborative nitriding and annealing in amorphous TiO2:Eu. The structural characterizations, including X-ray Diffraction (XRD) and transmission electron microscopy (TEM), indicate that the phase of nitrided TiO2:Eu can be well kept in amorphous form below 500 °C. X-ray photoelectron spectroscopy (XPS) confirms that the N content can be well controlled by changing the annealing temperature. The samples present notable absorption in the broad waveband region from 400 to 1000 nm, which is associated with the band tail states induced by nitriding. The doping engineering allows us to achieve broadband and tunable excitation covering the whole ultraviolet waveband from 250 to 400 nm. We also demonstrate the construction of composite layer which exhibits intense visible luminescence under ultraviolet and X-ray irradiation. Our results outline a fundamental principle to design light-harvesting materials with extended optical response, providing a major step toward in expanding the scope of lanthanide-doped phosphor.

Determination of Soil Salt Content Using a Probability Neural Network Model Based on Particle Swarm Optimization in Areas Affected and Non-Affected by Human Activities

Traditional partial least squares regression (PLSR) and artificial neural networks (ANN) have been widely applied to estimate salt content from spectral reflectance in many different saline environments around the world. However, these methods entail a great amount of calculation, and their accuracy is low. To overcome these problems, a probability neural network (PNN) model based on particle swarm optimization was used in this study to build soil salt content models. Furthermore, there is a clear correlation between the level of human activities and the degree of salinization of an environment. This paper is the first to discuss this matter. Here, the performance of the PNN model to estimate soil salt content from reflectance data was investigated in areas non-affected (Area A) and affected (Area B) by human activities. The study area is located in Xingjinag, China. Different mathematical procedures, five wave band intervals, and two types of signal input sources were used for cross analysis. The coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to deviation (RPD) index values were compared to verify the reliability of the model. Particle swarm optimization was used to adjust the optimal smoothing parameters of the PNN model and to avoid the long training processes required by the traditional ANN. The results show that the optimal wave band interval of the PNN is between 1000 nm and 1350 nm in Area A and between 400 nm and 700 nm in Area B. The reciprocal (1/R) transformation after Savitzky-Golay (SG) smoothing of the signal source is optimal for both areas. The RPD for both is greater than 30, which shows that the PNN model is applicable to areas with and without human activities and the prediction results are very good. The results indicated that the optimal wave band intervals for PNN modeling differed in areas affected and non-affected by human activities. The optimal interval of the artificial activities region falls in the visible light portion of the spectrum, and the optimized wave band region without human activities falls in the near-infrared short-wave portion of the spectrum.

Polymer-Based MEMS Photodetector With Spectral Response in UV-Vis-NIR and Mid-IR Region

Integrating various components on the same chip is highly sought after for various optoelectronic applications. In an attempt to provide an on-chip photodetection, a MEMS-based photodetector device with a wide spectral response is presented. The design merges the photoconductive and pyroelectric properties of nanomorphology-controlled polyvinyl alcohol as a photoactive layer. The fabrication technology is low cost with a single-layer deposition of photoactive polymer on a MEMS low thermal mass platform designed to improve the heat loss to the substrate. This fabricated device with a metal-semiconductor-metal structure shows Schottky diode behavior. The photoresponse of this device was observed from UV to mid-IR region with minimum light detection capability of 30 nW in UV, 120 nW for visible light, and 100 μW for IR light. The effect of nanomorphology and the thickness of the photoactive layer were studied to optimize the responsivity in the different waveband regions. Typically, at zero bias, under 405-nm illumination with light intensity of 170 μW/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the photodetector exhibited responsivity of 0.53 A/W. The wavelength response of this detector was found to be similar with standard detectors of the UV visible as well as mid-IR region (6.3-10.6 μm). The proposed on-chip MEMS-based photodetection module with the broad-spectrum detection capability and lower power consumption is useful for lab-on-chip-based technologies for a wide range of optical/spectroscopic applications.

The High Quantum Efficiency of Exponential-Doping AlGaAs/GaAs Photocathodes Grown by Metalorganic Chemical Vapor Deposition

An exponential-doping structure is successfully applied to the preparation of AlGaAs/GaAs photocathodes through the metalorganic chemical vapor deposition (MOCVD) technique. The experimental results show that the quantum efficiency in the entire waveband region for the exponential-doping photocathodes grown by MOCVD is remarkably enhanced as compared to those grown by molecular beam epitaxy. As a result of the improved built-in electric fields and cathode performance parameters, the photoemission characteristics for the MOCVD-grown transmission-mode and reflection-mode AlGaAs/GaAs photocathodes are different over the wavelength region of interest.

A review on hyperspectral remote sensing for homogeneous and heterogeneous forest biodiversity assessment

This review paper evaluates the potential of hyperspectral remote sensing for assessing species diversity in homogeneous (non-tropical) and heterogeneous (tropical) forest, an increasingly urgent task. Existing studies of species distribution patterns using hyperspectral remote sensing have used different techniques to discriminate different species, in which the wavelet transforms, derivative analysis and red edge positions are the most important of them. The wavelet transform is used based on its effectiveness and determined as the most powerful technique to identify species. Furthermore, estimations of relationships between spectral values and species distributions using chemical composition of foliage, tree phenology, selection of signature training sites based on field measured canopy composition, selection of the best wavelet coefficient and waveband regions may be useful to identify different plant species. This paper presents a summary on the feasibility, operational applications and possible strategies of hyperspectral remote sensing in forestry, especially in assessing its biodiversity. The paper also reviews the processing and analysis of techniques for hyperspectral data in discriminating different forest tree species.

Comparison of macroscopic cloud data from ground-based measurements using VIS/NIR and IR instruments at Lindenberg, Germany

A comparison between different types of ground-based sensors has been carried out to derive macroscopic cloud data such as cloud cover and cloud-base heights. The instruments compared in the campaign at the Meteorological Observatory Lindenberg in the period May to September 2006 include an infrared (IR) sky scanner called Nubiscope, a Daylight VIS/NIR Whole Sky Imager (WSI), a ceilometer LD-40 measuring in the near infrared region (NIR) and a Ka band cloud radar measuring in the micro wave band (extremely high frequency or EHF) region. In addition, our data analysis included regular hourly cloud observations by weather observers, and vertical profiles of temperature, humidity and winds taken from six-hourly radio soundings at the site. The comparison has been focused on performance and features of the Nubiscope as a prototype instrument for automatic cloud observations. Cloud cover (CC) derived from the Nubiscope cloud algorithm compares quite well with CC derived from both WSI and from observations. CC differences are within ± 2 Okta in 67% of cases between Nubiscope and observations, and in 90% of cases between Nubiscope and WSI. The cloud detection capability as derived from the zenith signals of Nubiscope and WSI shows coincidence in about 90% of cases. For cloud-base heights (CBHs) from Nubiscope data and ceilometer as well as from radar reflectivity, the comparison showed a general good correspondence in the lower and middle troposphere up to heights of about 6 km with some systematic difference due to the different detection methods. For the upper troposphere above 6 km the differences become widespread and more random. Cloud detection capabilities of the instruments are also illustrated by a case study of moving clouds with patterns similar to contrails that were erroneously classified as such by the weather observer mainly due to lack of height information that the ceilometer did not provide. By combined information from WSI, radio sonde humidity and radar, they were shown not to be contrails, but most likely low-level water clouds either of natural origin or built from aircraft at their ascent or descent flight close to the airport.

In situ measurement of the infrared absorption and extinction of chemical and biologically derived aerosols using flow-through photoacoustics

In an effort to establish a more reliable set of optical cross sections for a variety of chemical and biological aerosol simulants, we have developed a flow-through photoacoustic system that is capable of measuring absolute, mass-normalized extinction and absorption cross sections. By employing a flow-through design we avoid issues associated with closed aerosol photoacoustic systems and improve sensitivity. Although the results shown here were obtained for the tunable CO2 laser waveband region, i.e., 9.20-10.80 microm, application to other wavelengths is easily achievable. The aerosols considered are categorized as biological, chemical, and inorganic in origin, i.e., Bacillus atrophaeus endospores, dimethicone silicone oil (SF-96 grade 50), and kaolin clay powder (alumina and silicate), respectively. Results compare well with spectral extinction measured previously by Fourier-transform infrared spectroscopy. Comparisons with Mie theory calculations based on previously published complex indices of refraction and measured size distributions are also presented.

Reduced polarized thermal emission due to surface contamination by dew and atmospheric aerosols

We report on a series of polarimetric measurements designed to quantify the degree by which polarized thermal emittance is attenuated by either dew formation or contamination by atmospheric aerosols. In particular, we measure changes in the linear degree of polarization from smooth borosilicate glass (pyrex) substrates that are subject to either dew formation or contamination by three aerosol particulates, i.e., carbon black, KBr particles, and Dactylis glomerata (orchard grass) pollen. Calibrated polarimetric images of the contaminated substrates are recorded in the 8.5–10.5μm waveband region using a specially modified thermal camera. Video microscopy is used to characterize the degree in which the surface is covered by the contaminate in question. Results are compared with a geometric based model that effectively modifies the Fresnel relation to account for masking of the surface by the contaminate and/or particle shadowing.

Analysis of thermal infrared data from the Digital Airborne Imaging Spectrometer

Thermal infrared data of the Digital Airborne Imaging Spectrometer (DAIS), whose channels 74-79 are in the 8-13 w m waveband region, were analysed with the aim of recovering land surface temperature (LST). DAIS images were acquired over an experimental site where field and laboratory emissivity measurements were performed, and these were used to recover the LST from the six DAIS thermal channels. Atmospheric correction of DAIS data was calculated by means of a nearby radiosounding and a radiative transfer model. DAIS derived LSTs were compared with ground measurements of LST made coincidentally for a few test fields, the central DAIS channels yielding temperatures up to 10°C higher than ground measurements. A linear calibration was performed using in situ measurements of temperature and emissivity for two reference fields, and the large differences in temperature were then considerably reduced. Temperatures obtained from DAIS channel 79 agreed with the in situ measurements within - 2°C. This channel seemed the most reliable for deriving accurate LSTs in the dataset analysed here.