Reflectance Spectra Research Articles

New three red-edge vegetation index (VI3RE) for crop seasonal LAI prediction using Sentinel-2 data

Leaf area index (LAI) serves as a pivotal parameter in crop monitoring, significantly impacting agricultural applications. Empirical models are one of the commonly used methods for estimating LAI, they are often dependent on vegetation indices (VIs), predominantly derived from low-to-moderate spatial resolution satellite sensors. A critical limitation of these VIs is their tendency to saturate at elevated LAI values. Additionally, the interplay between chlorophyll content (Cab), LAI, as well as average leaf inclination angle (ALA), particularly in reflectance spectra from red to red-edge regions, has been underexplored in past research. Based on Sentinel-2 satellite, with three red-edge bands and enhanced spatio-temporal resolution, this study introduced a new three red-edge vegetation index (VI3RE), comprising NDVI3RE and CI3RE, which leverages the unique spectral characteristics of these bands and related differential response to LAI and Cab variations. We investigated VI3RE’s efficacy through a threefold approach: firstly, by conducting sensitivity analyses using noise equivalent (NE)ΔLAI ((NE) ΔLAI=1.37 and 1.59 for NDVI3RE and CI3RE; (NE)ΔLAI = 1.75 – 3.25 for other VIs) and extended Fourier amplitude sensitivity test (EFAST) (the contribution of LAI: FOI > 30 % and TOI > 40 % for VI3RE; FOI ∼ 17 % − 28 % and TOI ∼ 25 % − 34 % for other VIs, except for NDVI with TOI ∼ 50 %), we demonstrated VI3RE’s heightened sensitivity to LAI and its improved capability for seasonal LAI estimation compared to other VIs. Secondly, by comprehensively considering the simplicity, interpretability, AIC and R2 values of various models, the linear regression model was selected for analyzing the relationships between LAI and various VIs. We established that VI3RE, particularly NDVI3RE, exhibits a robust correlation with LAI, thereby enhancing LAI estimation accuracy (R2 = 0.72, RMSE = 1.39). Lastly, we applied the LAI-VI regression models to generate crop LAI imageries throughout the growing season, subsequently validating by field measured LAI data. The results affirmed VI3RE’s superior performance in seasonal LAI estimation of crops, notably during peak growth and sowing phases. We conclude that the newly formulated VI3RE offers a universal, highly precise, and reliable model for LAI prediction across various crop types and phenological stages. However, the broader application of VI3RE may be limited, due to the three red-edge bands are not commonly found in most satellite platforms. In addition, some other aspects are not considered in this study, such as phenological information, meteorological factors, sampling strategies, etc., which should be meticulously considered in the future studies.

The Antimicrobial Activity of Cu/CuxO Composites Synthesized by Thermal Oxidation of Copper Tablets

Introduction: One of common bacteria is Staphylococcus aureus, which is a gram- positive, coagulasepositive, golden color in culture. That causes a wide range of clinical infections, resistance to β-lactam antibiotics. Objectives: In this paper, we investigate the ability of copper nanoparticles in Cu/CuxO composites to inhibit Staphylococcus aureus bacteria and the effect of oxidation temperature on the inhibition efficacy. Methods: Cu/CuxO composites were synthesized on the surfaces of copper samples by thermal oxidation of copper pressed tablets at various temperatures. The optical reflectivity spectra of the Cu/CuxO composites were measured. The edges of the plasma in these spectra were observed in the range 526-600 nm. In order to verify the antibacterial behavior of these composites, inhibition zone tests were realized for Staphylococcus aureus. Results: The results showed that, the widest zone of inhibition was for the treated sample at temperature 100°C. In addition, we found that the thermal oxidation reduces the ability of copper nanoparticles to inhibit bacteria. Conclusions: The results we obtained are summarized in the following points: 1) Thermal oxidation reduces the reflectivity of copper samples. 2) The plasma edge increases with the increase in the oxidation temperature. 3) Increasing the oxidation temperature leads to a decrease in bacterial inhibition rates

Photocatalytic Performance of the BaSn-based Nanoscale Materials for the Organic Pollutants Enhanced by Sm (Er) Doping

Background: Sm (Er) doping is an effective strategy for enhancing the photocatalytic activity of the semiconductor photocatalysts for the degradation of organic pollutants. BaSnbased nanorods possess wide band gap energy, which limits the photocatalytic application. It is important to research the feasibility of the improved photocatalytic performance of the BaSnbased nanorods by doping with Sm (Er). Objective: The aim is to synthesize Sm (Er)-doped BaSn-based nanoscale materials through a simple hydrothermal process and research the photocatalytic performance of the Sm (Er)-doped BaSn-based nanoscale materials for the gentian violet degradation. Methods: Sm (Er)-doped BaSn-based nanoscale materials with a polycrystalline structure were synthesized through a simple hydrothermal process. The Sm (Er)-doped composites were analyzed by X-ray diffraction, electron microscopy, solid diffuse reflectance spectrum, X-ray photoelectron spectroscopy, photoluminescence, and electrochemical impedance spectroscopy. Results: Sm (Er) doping induces the morphological evolution of the BaSn-based nanoscale materials from the nanorods to irregular nanoscale particles. Sm (Er) in the doped BaSn-based nanoscale materials exists in the form of the cubic Sm2Sn2O7 and orthorhombic ErF3 phases. The band gap value is decreased with increasing the Sm (Er) dopant contents. Sm (Er)-doped BnSnbased nanoscale materials with the Sm (Er) content of 8wt.% have the lowest band gap and show the strongest light absorption ability. Compared with the un-doped BaSn-based nanoscale materials, the Sm (Er)-doped BnSn-based nanoscale materials exhibit higher photocatalytic activity for the gentian violet degradation. 8wt.% Sm-doped BnSn-based nanoscale materials show the highest photocatalytic activity for the degradation of the gentian violet. 20 mL gentian violet solution (concentration of 10 mg·L-1) can be totally degraded using 20 mg 8wt.% Sm-doped BnSnbased nanoscale materials under UV light illumination for 150 min. Conclusion: The enhanced photocatalytic activity of the Sm (Er)-doped BnSn-based nanoscale materials can be attributed to the decreased band gap, enhanced light absorption ability, and decreased recombination of the photo-generated electron-hole pairs.

Enhancing color saturation in photonic glasses through optimized absorption

Photonic glasses, isotropically assembled nanoparticles with short-range correlation, can produce angle independent structural colors. They show broader reflectance spectra and lower saturated colors, compared to photonic crystals. Low color saturation creates barriers for photonic glasses to be used for coatings, cosmetics, and colors. Broadband absorbing materials are commonly used to absorb incoherently scattered light to enhance the saturation. However, there is limited understanding on how the absorption quantitatively affects the colors of photonic glasses. To this end, we here use a validated Monte Carlo-based multiple scattering model to investigate how absorption impacts the reflectance spectra in photonic glasses. We show that the color saturation can be maximized with an optimal level of absorption regardless of sample thickness or refractive index contrast between particles and matrix. We quantitatively demonstrate that the multiple scattering is largely reduced with the optimal absorption level and the reflectance is dominantly contributed by the single scattering. The optimal absorption occurs when the sample absorption mean free path is comparable to the transport mean free path, which offers a guidance on how much absorbing material is needed for creating highly saturated photonic glasses. This work will not only pave ways for pushing applications of angle-independent structural colors, but also improve our understanding of light scattering and absorption in short-range correlated disordered systems.

Dy3+ doped KCa(PO3)3 phosphor for white light generation: structural and luminescent studies

Abstract Using the traditional solid-state reaction approach, Dy3+ ions doped KCa(PO3)3 phosphors have been synthesized to investigate their luminescent properties to produce high-quality white light for solid-state lighting applications, particularly in white LEDs. X-ray diffraction (XRD) patterns were used to examine the structure and phase of the phosphors. Using scanning electron microscopy (SEM), the morphology of the as-synthesized phosphor has been investigated. Fourier transform infrared spectroscopy (FT-IR) has been used to investigate several vibrational bands seen in the phosphor. Using diffuse reflectance spectra (DRS), the as-synthesized phosphors' optical band gap values have been estimated. When Dy3+ ions are excited at 350 nm, the photoluminescence (PL) spectra characteristics observed for the activated KCa(PO3)3 phosphor show strong white area emission at 575 nm, which is related to the 4F99/2 → 6H13/2 transition of Dy3+ ions. Additionally, the concentration quenching of Dy3+ ions doped at 4 mol% is seen in the PL spectra. Based on the observed PL spectra, the computed CIE chromaticity coordinates for the doped KCa(PO3)3 phosphors show that the optimised 4.0mol% Dy3+ doped phosphor is located in the deep white area. The lifespan of the as-titled phosphors decreases as the amount of Dy3+ ions increases in the host lattice. Additionally, the PL decay profiles shows a dual exponential behaviour when excited at 350 nm, with an emission wavelength at 575 nm. On the basis of the results of the aforementioned studies, we wish to project Dy3+ ion doped KCa(PO3)3 phosphors as white light generating materials in w-LEDs and for other photonic applications.

Time division multiplexing based multi-spectral semantic camera for LiDAR applications

The recent progress in the development of measurement systems for autonomous recognition had a substantial impact on emerging technology in numerous fields, especially robotics and automotive applications. In particular, time-of-flight (TOF) based light detection and ranging (LiDAR) systems enable to map the surrounding environmental information over long distances and with high accuracy. The combination of advanced LiDAR with an artificial intelligence platform allows enhanced object recognition and classification, which however still suffers from limitations of inaccuracy and misidentification. Recently, multi-spectral LiDAR systems have been employed to increase the object recognition performance by additionally providing material information in the short-wave infrared (SWIR) range where the reflection spectrum characteristics are typically very sensitive to material properties. However, previous multi-spectral LiDAR systems utilized band-pass filters or complex dispersive optical systems and even required multiple photodetectors, adding complexity and cost. In this work, we propose a time-division-multiplexing (TDM) based multi-spectral LiDAR system for semantic object inference by the simultaneous acquisition of spatial and spectral information. By utilizing the TDM method, we enable the simultaneous acquisition of spatial and spectral information as well as a TOF based distance map with minimized optical loss using only a single photodetector. Our LiDAR system utilizes nanosecond pulses of five different wavelengths in the SWIR range to acquire sufficient material information in addition to 3D spatial information. To demonstrate the recognition performance, we map the multi-spectral image from a human hand, a mannequin hand, a fabric gloved hand, a nitrile gloved hand, and a printed human hand onto an RGB-color encoded image, which clearly visualizes spectral differences as RGB color depending on the material while having a similar shape. Additionally, the classification performance of the multi-spectral image is demonstrated with a convolution neural network (CNN) model using the full multi-spectral data set. Our work presents a compact novel spectroscopic LiDAR system, which provides increased recognition performance and thus a great potential to improve safety and reliability in autonomous driving.

Microsphere-assisted multispectral microscopy

Studies of novel nanostructures have highlighted the need for characterization methods at the nanometric level. To address this challenge, an innovative label-free microsphere-assisted multispectral microscope is presented in this paper. This spectral technique is the first, to our knowledge, to take advantage of the imaging properties of the microsphere. The multispectral acquisition is performed through a 145 µm diameter soda-lime glass microsphere to map the reflectance spectra over a surface covered by an 8 µm diameter disk and with an improved lateral resolution of a factor of 1.8. Relevant reflectance characterizations of materials and sub-diffracted features demonstrate the technique. The proposed setup can be implemented and adapted to any optical microscope.

Towards FAIR Data Management in Heritage Science Research: Updates and Progress on the INFRA-ART Spectral Library

The heritage science sector is facing a critical need for accessible and comprehensive data resources to facilitate research, preservation efforts, and interdisciplinary collaboration. The concept of FAIR data management involves embracing principles and practices that ensure that data are Findable, Accessible, Interoperable, and Reusable. This work presents an overview of the latest updates on the INFRA-ART Spectral Library, an open access spectral database of cultural-heritage-related materials that was designed as a digital support tool for heritage research specialists that work with (portable) non- or minimally invasive spectroscopic techniques such as X-ray fluorescence (XRF), attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy, or Raman spectroscopy, among others. The database is an ongoing compilation of high-quality curated data that currently incorporates primary ATR-FTIR and XRF spectra and a preliminary dataset of Raman and short-wave infrared (SWIR) reflectance spectra on over 900 different materials typically found in painted works of art. For increased and sustainable accessibility, the database follows the European Commission’s recommendations on access to scientific information, as well as the FAIR guiding principles on research data that result from publicly funded research. The INFRA-ART Spectral Library is registered as a resource within the Open Science Cloud (EOSC) Portal and is among the services offered by the Romanian hub within E-RIHS (European Research Infrastructure for Heritage Science) DIGILAB.

A new spectrally-invariant approach to the remote sensing of inhomogeneous clouds

Current operational satellite retrievals of cloud optical and microphysical properties go back to the Nakajima-King technique developed at the end of the 1980 s. This technique is based on library calculations for plane-parallel homogeneous clouds. It often works well for overcast skies but leads to substantial errors for inhomogeneous and broken cloud fields where the plane-parallel-geometry assumption is no longer valid. The basic concept of a new technique was first introduced in nuclear physics to quantify the critical conditions of reactors. Based on the eigenvalues of the radiative transfer equation, their approach provides a powerful means to parameterize the structure of 3D media. This parameterization was later successfully applied to relate surface reflectance spectra to 3D canopy structure and is known as the spectrally-invariant approximation. The proposed approach adapts this technique to the remote sensing of cloud properties such as droplet single scattering albedo and the average number of scatterings (which are the fundamental parameters in radiative transfer theory), with an emphasis on quantifying the associated errors and uncertainties. This retrieval is free from the plane-parallel homogeneous cloud assumption.

Kinetic study of adsorption and photocatalytic degradation of methylene blue dye using TiO2 nanoparticles with activated carbon

Abstract Activated carbon (AC) exhibits limited adsorption capacity for pollutants. Conversely, titanium dioxide (TiO2) demonstrates excellent photocatalytic performance, making it a popular choice for pollutant removal. This study investigates the removal of methylene blue (MB) dye from wastewater using AC, TiO2@AC-2, and TiO2@AC-10 samples via adsorption and photocatalysis. The Energy Dispersive analysis of X-rays (EDAX) has confirmed the presence of Ti, C and O in the prepared samples without any impurities. All the diffraction peaks in X-ray diffractograms indicated the presence of pure anatase TiO2 (tetragonal phase) with no evidence of any other phase. Fourier transform infrared spectroscopy (FTIR) analysis identified a peak around 545 cm⁻¹ in the TiO2@AC-2 sample, indicative of O-Ti-O stretching vibrations. This peak shifted to 602 cm⁻¹ in the TiO2@AC-10 sample. Raman spectroscopy confirmed the presence of carbon (D and G bands) at 1310-1347 cm⁻¹ and 1582-1597 cm⁻¹. Additionally, characteristic Raman active bands for anatase TiO2 were observed at 154 cm⁻¹ (Eg), 204 cm⁻¹ (Eg), 398 cm⁻¹ (B1g), 508 cm⁻¹ (A1g), and 628 cm⁻¹ (Eg). N2 adsorption-desorption isotherms revealed a mesoporous structure for all samples (AC, TiO2@AC-2, and TiO2@AC-10) with hysteresis loops, indicating pores ranging from 2 nm to 50 nm in diameter. Reflectance spectra of TiO2@AC-2 and TiO2@AC-10 displayed absorption edges at 368 nm and 385 nm, respectively, corresponding to a direct band gap of approximately 3.22 eV. Subsequently, these prepared samples were effectively employed for the removal of methylene blue (MB) dye from wastewater utilizing both adsorption and photocatalysis method. Under dark conditions, 20 mg/L doses of TiO2@AC-2 and TiO2@AC-10 resulted in 60% and 36% dye adsorption within 60 minutes respectively. In the presence of UV radiation, the degradation of dye was observed to be 74% and 95% by TiO2@AC-2 and TiO2@AC-10 respectively. This observation indicates that TiO2 nanoparticles along with AC leads to enhanced photocatalytic activity. The Langmuir-Hinshelwood model reveals lower rate constants for AC compared to the composite samples. This is likely because AC lacks inherent catalytic activity, requiring UV light to trigger adsorption. Conversely, TiO2@AC-10 exhibits the highest rate constants (K1 = 24.25 × 10-3 min⁻¹ and K2 = 82.71 × 10-3 min⁻¹), aligning with its higher TiO2 content confirmed by EDAX analysis. This suggests a significantly faster photocatalytic rate and superior degradation efficiency, even at a low sample concentration (20 mg/L).

Directly modulated deformed-square-FP coupled-cavity laser with intracavity-mode photon-photon resonance

We propose and demonstrate a high-speed directly modulated laser based on a hybrid deformed-square-FP coupled cavity (DFC), aiming for a compact-size low-cost light source in next-generation optical communication systems. The deformed square microcavity is directly connected to the FP cavity and utilized as a wavelength-sensitive reflector with a comb-like and narrow-peak reflection spectrum for selecting the lasing mode, which can greatly improve the single-mode yield of the laser and the quality (Q) factor of the coupled mode. By optimizing the device design and operating condition, the modulation bandwidth of the DFC laser can be enhanced due to the intracavity-mode photon-photon resonance effect. Our experimental results show an enhancement of 3-dB modulation bandwidth from 19.3 GHz to 30 GHz and a clear eye diagram at a modulation rate of 25 Gbps.

Non-destructive prediction of anthocyanin concentration in whole eggplant peel using hyperspectral imaging

Accurately detecting the anthocyanin content in eggplant peel is essential for effective eggplant breeding. The present study aims to present a method that combines hyperspectral imaging with advanced computational analysis to rapidly, non-destructively, and precisely measure anthocyanin content in eggplant fruit. For this purpose, hyperspectral images of the fruits of 20 varieties with diverse colors were collected, and the content of the anthocyanin were detected using high performance liquid chromatography (HPLC) methods. In order to minimize background noise in the hyperspectral images, five preprocessing algorithms were utilized on average reflectance spectra: standard normalized variate (SNV), autoscales (AUT), normalization (NOR), Savitzky–Golay convolutional smoothing (SG), and mean centering (MC). Additionally, the competitive adaptive reweighted sampling (CARS) method was employed to reduce the dimensionality of the high-dimensional hyperspectral data. In order to predict the cyanidin, petunidin, delphinidin, and total anthocyanin content of eggplant fruit, two models were constructed: partial least squares regression (PLSR) and least squares support vector machine (LS-SVM). The HPLC results showed that eggplant peel primarily contains three types of anthocyanins. Furthermore, there were significant differences in the average reflectance rates between 400–750 nm wavelength ranges for different colors of eggplant peel. The prediction model results indicated that the model based on NOR CARS LS-SVM achieved the best performance, with a squared coefficient of determination (R2) greater than 0.98, RMSEP and RMSEC less than 0.03 for cyanidin, petunidin, delphinidin, and total anthocyanin predication. These results suggest that hyperspectral imaging is a rapid and non-destructive technique for assessing the anthocyanin content of eggplant peel. This approach holds promise for facilitating the more effective eggplant breeding.

Multi-parameter terahertz metamaterial sensors based on single-layer quarter ring patterns

A terahertz metamaterial sensor based on a single-layer quarter ring pattern is proposed to realize the simultaneous measurement of temperature, refractive index, and other parameters through a metasurface consisting of a patterned quarter ring gold layer and a silicon substrate. Field finite element numerical simulations were performed to analyse the transmission and reflection spectra. A two-parameter sensor combined with electric field distribution was realized using multiple peaks, thus revealing the physical mechanisms of the interaction in metamaterial structures. In addition, the effect of each geometrical parameter on the sensor performance is also simultaneously analysed to verify the optimal selection of structural parameters. On this basis, the sensors are theoretically analysed at different incidence and polarization angles, and the results show that the transmittance is not sensitive to the polarization angle. The simulation results show that the transmittance at the resonant frequencies of 0.48 THz, 0.64 THz, 0.79 THz and 1.04 THz are 93.7 %, 79.1 %, 38.4 % and 50.8 %, respectively, and the refractive index sensitivities at the resonant frequencies are 6.84 GHz/RIU, 7.42 GHz/RIU, 8.22 GHz/RIU and 32.11 GHz/RIU, and quality factor Q of 6.76, 9.63, 15.51 and 26.28, respectively. The devices proposed in this study are simple in structure, easy to fabricate, easy to miniaturize and can be integrated for sensitivity, multi-parameter sensors. They can be functionally designed for chemical and biological sensing and other important applications.

Ultra-broadband absorbance of nanometer-thin pyrolyzed-carbon film on silicon nitride membrane

Fifty percents absorption by thin film, with thickness is much smaller than the skin depth and optical thickness much smaller than the wavelength, is a well-known concept of classical electrodynamics. This is a valuable feature that has been numerously widely explored for metal films, while chemically inert nanomembranes are a real fabrication challenge. Here we report the 20 nm thin pyrolyzed carbon film (PyC) placed on 300 nm thick silicon nitride (Si3N4) membrane demonstrating an efficient broadband absorption in the terahertz and near infrared ranges. While the bare Si3N4 membrane is completely transparent in the THz range, the 20 nm thick PyC layer increases the absorption of the PyC coated Si3N4 membrane to 40%. The reflection and transmission spectra in the near infrared region reveal that the PyC film absorption persists to a level of at least 10% of the incident power. Such a broadband absorption of the PyC film opens new pathways toward broadband bolometric radiation detectors.

AgriTera: Accurate Non-Invasive Fruit Ripeness Sensing via Sub-Terahertz Wireless Signals

The potential to transform the agriculture sector and reduce food waste significantly lies in the ability to assess the quality of fruits and vegetables on a large scale. This article introduces AgriTera, an innovative solution that utilizes sub-terahertz wireless signals for accurate and non-invasive fruit ripeness sensing, without the need for physical contact. The underlying idea is that sugar and water concentrations in fruits, linked to ripening, create distinctive patterns in the wideband spectrum of reflected signals from the fruit body. AgriTera leverages the sub-THz bands due to their wide bandwidth, sensitivity to water, millimeter-scale penetration depth, and non-ionizing features. This enables high-resolution inferences from both the peel and pulp underneath. A chemometric model is developed to translate reflection spectra into well-known ripeness metrics like Dry Matter and Brix. Extensive over-the-air experiments using commercial sub-THz transceivers are conducted and compared with ground truth values from specialized sensors and a vision-based scheme.

Investigation of Physical Properties of Nanostructured Selenium-Based Compound Semiconductors

The study of physical properties of compound semiconductors plays a vital role in the device fabrication point of view. Different investigations suggest that one can tune these properties by impurity dopants, irradiation techniques, adopting different synthesis techniques, etc. In this study, the physical properties of nanostructured thin films of Se–S compound were tuned by different Hg dopant concentrations. X-ray diffraction spectra clarify the preferred crystallite growth occurs in the cubic phase of the corresponding Bravi’s crystal system. The particle size calculated from Bragg’s reflection spectra by using Scherrer’s analytical formula illustrates an enhancement of crystallite size in highly concentrated Hg-doped sample. Similar consequences are found in surface morphological micrographs. The optical band gap reduced from 1.65[Formula: see text]eV to 1.54[Formula: see text]eV on increasing the doping concentration of Hg, according to the computed optical parameters using optical transmission spectra in the wavelength range 200–1100[Formula: see text]nm. The thin-film refractive index dispersion data fits well in accordance with the single oscillator model. Investigation of electrical properties tells that there is significant improvement in electrical conductivity in highly concentrated Hg-doped samples. Therefore, the apparent tuning as observed in the physical properties of the investigated material may have practical uses in industry for a variety of optoelectronic devices.

Identification of rare earth elements in synthetic and natural monazite and xenotime by visible-to-shortwave infrared reflectance spectroscopy

To support the role of proximal and remote sensing in geological rare earth element (REE) resource exploration, we studied the reflectance spectroscopy of synthetic single- and mixed-REE phosphate phases. Synthesis yielded monazite for the elements La to Gd, and xenotime for Dy to Lu and Y. Visible-to-shortwave infrared (350–2500 nm) reflectance spectra of synthetic single-REE monazites and xenotimes can be used to identify the ions responsible for the absorption features in natural monazites and xenotimes. Nd3+, Pr3+ and Sm3+ produce the main absorption features in monazites. In natural xenotime, Dy3+, Er3+, Ho3+ and Tb3+ ions cause the prevalent absorptions. The majority of the REE-related absorption features are due to photons exciting electrons within the 4f subshell of the trivalent lanthanide ions to elevated energy levels resulting from spin-orbit coupling. There are small (< 20 nm) shifts in the wavelengths of these absorptions depending on the nature of the ligands. The energy levels are further split by crystal field effects, manifested in the reflectance spectra as closely spaced (∼ 5–20 nm) multiplets within the larger absorption features. Superimposed on the electronic absorptions are vibrational absorptions in the H2O molecule or within [OH]−, [CO3]2− and [PO4]3− functional groups, but so far only the carbonate-related spectral features seem usable as a diagnostic tool in REE-bearing minerals. Altogether, our study creates a strengthened knowledge base for detection of REE using reflectance spectroscopy and provides a starting point for the identification of REE and their host minerals in mineral resources by means of hyperspectral methods.

2D/1D nested hollow porous ZnIn2S4/g-C3N4 heterojunction based on morphology modulation for photocatalytic CO2 reduction

The two-dimensional (2D) composite one-dimensional (1D) heterojunction structure is one of the main strategies for constructing composite photocatalysts for photocatalytic reduction of carbon dioxide (CO2). However, morphology modulation for 2D/1D heterojunction is an important way to enhance performance. In this study, a unique 2D/1D ZnIn2S4/g-C3N4 nested hollow porous heterojunction structure was constructed by an in-situ growth method with spatial confinement effect. The synergy between 1D g-C3N4 and 2D ZnIn2S4, achieved through advanced morphology modulation at an optimal ratio of 3:1, results in the formation of the CZ-3 photocatalyst. This unique configuration enables a simultaneous high yield of carbon monoxide (CO) and methane (CH4), achieving 79.96 μmol/g and 17.33 μmol/g respectively, under visible light irradiation without the need for sacrificial agents. The core of this enhanced photocatalytic performance is attributed to the employment of a type-II heterojunction mechanism, which optimizes the transfer of photogenerated carriers. Ultraviolet-visible diffuse reflection spectrum, photoluminescence spectrum and photoelectrochemical analysis reveal the effect of morphology on photocatalytic performance in terms of visible light absorption, photogenerated carrier pairs separation and electronic band structure of heterojunction. By combining the advantages of 2D/1D structural benefits with the efficient charge dynamics of a type-II heterojunction, this work provides new ideas for improving the morphology of composite heterojunction photocatalysts with 2D/1D structure to enhance the photocatalytic CO2 reduction performance.

Mud Spectral Characteristics from the Lusi Eruption, East Java, Indonesia Using Satellite Hyperspectral Data

Imaging spectroscopy allows us to identify surface materials by analyzing the spectra resulting from the light–material interaction. In this preliminary study, we analyze a pair of hyperspectral cubes acquired by PRISMA (on 20 April 2021) and EO1- Hyperion (on 4 July 2015) over the Indonesian Lusi mud eruption. We show the potential suitability of using the two sensors for characterizing the mineralogical features in demanding “wet and muddy” environments such as Lusi. We use spectral library reflectance spectra like Illite Chlorite from the USGS spectral library, which are known to be associated with Lusi volcanic products, to identify minerals. In addition, we have measured the reflectance spectra and composition of Lusi sampled mud collected in November 2014. Finally, we compare them with reflectance spectra from EO1-Hyperion and PRISMA. The use of hyperspectral sensors at improved SNR, such as PRISMA, has shown the potential to determine the mineral composition of Lusi PRISMA data, which allowed the distinction of areas with different turbidities as well. Artifacts in the VNIR spectral region of the L2 PRISMA reflectance product were found, suggesting that future work needs to take into account an independent atmospheric correction rather than using the L2D PRISMA product.

Internal quality evaluation of ‘Fuji’ apples during storage based on bulk optical properties or diffuse reflection and transmission spectra

The purpose of this study is to compare the performance of prediction models based either on the bulk optical properties (BOP) or with models based on the diffuse reflection and transmission spectra to assess the soluble solids content (SSC) or fruit firmness (FF) of ‘Fuji’ apples. Diffuse reflection and transmission spectra of 240 apples in 500-1000 nm were acquired using a self-constructed single integrating sphere system, from which the absorption coefficient (μa) and reduced scattering coefficient (μ's) were determined. The relationships of μa, μ's, and the reflection and transmission spectra with the SSC and FF were analyzed, and detection models were established using partial least squares regression coupled with characteristic wavelength selection. Results showed that neither the SSC nor the FF changed obviously during 80-days storage, and the μa and μ's showed no monotonic increase or decrease pattern. The SSC prediction model based on μa spectra combined with the baseline correction method performed the best (R2p=0.79, RMSEP=0.62), while the model based on μ's spectra was the best for FF (R2p=0.67, RMSEP=0.35 N). Overall, the accuracy of the model based on BOP in predicting internal quality was better than that based on reflection and transmission spectra from the same measurement.