Reflectance Index Research Articles

From Molecules to Devices: Insights into Electronic and Optical Properties of Pyridine-Derived Compounds Using Density Functional Theory Calculations.

In this study, we delve into the electronic structure, spectroscopic, and optical properties of five benzo derivatives of pyridine, namely, 5-(4-chlorophenyl)-2-fluoropyridine (1), 2-fluoro-5-(4-fluorophenyl)pyridine (2), 4-(2-fluoropyridin-5-yl)phenol (3), 5-(2,3-dichlorophenyl)-2-fluoropyridine (4), and 5-(5-bromo-2-methoxyphenyl)-2-fluoropyridine (5). Utilizing quantum chemical density functional theory calculations at the B3LYP and Perdew-Burke-Ernzerhof levels of theory combined with the 6-311G(d,p) and 6-311++G(d,p) basis sets, we investigated the electronic and optical characteristics of these compounds. Band structure calculations were conducted for their crystalline structures, revealing a direct band gap varying from 3.018 to 3.558 eV, with the valence band maximum and conduction band minimum located at the G point in the Brillouin zone. The optical properties were analyzed, including the dielectric functions, reflectivity, and refractive index. Notably, reflectivity was found to be minimal in the photon energy range of 0.0-3.0 eV, and the static refractive index, n(0), ranged from 1.55 to 1.70. The research also involved assessing the reactivity of the compounds through calculation of the frontier orbital energy gaps (ΔE), indicating a significant charge transfer and high reactivity. Additionally, we performed frequency analysis to unveil the Fourier-transform infrared spectra of compounds 1-5 at room temperature. Molecular electrostatic potential surfaces of the optimized structures were employed to map the electrophilic and nucleophilic regions of the compounds. This investigation provides a comprehensive understanding of the electronic and optical properties of these pyridine derivatives, shedding light on their potential applications in optoelectronics.

Carotid wave analysis in young adults with a history of adolescent anorexia nervosa: a case control study

BackgroundAnorexia nervosa (AN) is associated with abnormalities that may increase the risk of future cardiovascular disease. This study assessed the cardiovascular health of individuals who recovered from AN during adolescence by conducting wave power analysis.MethodsFormer AN patients discharged from the Royal Children’s and Monash Children’s Hospitals (N = 17) in Melbourne, Australia underwent ultrasound imaging of the right carotid artery. Wave power analysis was conducted to assess biomechanical interactions of the cardiovascular system. Patient measures were compared to healthy controls (N = 51).ResultsEighty-eight percent of the former AN patients and controls were female, aged approximately 25 years, with a healthy body mass index. Mean carotid flow and pulsatility index were not different between groups. Carotid arterial strain and distensibility were lower, and the wave speed and beta stiffness index higher in the former AN patients. Characteristic impedance was not different nor were the forward and backward wave amplitudes. However, wave reflection indices (ratios of backward-to-forward compression wave area, and wave-related effect on pressure and hydraulic power) were 12–18% lower in the former AN patients (p < 0.05).ConclusionsIncreased carotid artery stiffness and reduced wave reflection are evident in young adults who recovered from adolescent AN. This may relate to an adaptive process that helps to maintain or restore flow and characteristic impedance despite increased vessel stiffness, with this warranting future investigation.

Predict Sarcopenia Risk in the Elderly by Cardiovascular Function and Heart Rate Variability

Objectives: Preventing and slowing sarcopenia in older people has become an important health issue. Heart rate variability reflects autonomic nervous system balance, and along with cardiovascular function, can indicate potential sarcopenia risk by signaling disruptions in muscle-supporting blood flow and autonomic control. Our objective was to collect simple and non-invasive cardiovascular function measurements and heart rate variability parameters to develop a model for predicting sarcopenia risk. Methods: We conducted a 3-minute cardiovascular function and heart rate variability test and sarcopenia screening (appendicular skeletal muscle index, grip strength, and walking speed) on 418 participants (105 males, 313 females, mean age 73.32±8.81 years) recruited from central Taiwan. Results: Appendicular skeletal muscle index, grip strength, walking speed, cardiovascular function, and heart rate variability had a significant correlation. The key features for predicting sarcopenia risk with logistic regression analysis were age, reflection index, dicrotic elasticity index, and high-frequency power (the overall accuracy was 70.10%; sensitivity was 81.30%; specificity was 54.07%). Conclusions: Simple and non-invasive 3-minute cardiovascular function and heart rate variability test parameters significantly predict sarcopenia risk in older people. This model can be applied to technology devices to detect sarcopenia risk and prevent sarcopenia in older people.

Using only the red-edge bands is sufficient to detect tree stress: A case study on the early detection of PWD using hyperspectral drone images

Pine wilt disease (PWD) is a destructive disease of pine trees caused by the pine wood nematode and early identification is crucial for disease control. Hyperspectral drone imagery has the potential to achieve early detection, although specific methods have not been sufficiently explored, including the spectral characteristics of early infections and the most efficient identification methods. This study aimed to examine the spectral responses to early infection, quantify the separability of healthy and early infections, and compare the accuracy and efficiency of different methods including single bands, vegetation indices (VIs) and 1st derivative reflectance and indices. We collected hyperspectral drone data in southeast China and used linear discriminant analysis (LDA) to determine the separability of healthy trees and trees at an early stage of infection. We also used bands with the same wavelengths as Sentienl-2 images (denoted S2 bands) to propose a standard for band selection.We found that it was possible to separate healthy trees and those at an early stage of infection around 0.71–0.78 using different methods. Among individual bands, the red-edge bands had the highest separability of 0.74. Using standard vegetation indices resulted in separability between 0.67 and 0.71; in addition, we proposed three new indices that achieved separability between 0.73 and 0.75. The 1st derivative reflectance at 714 nm had the highest separability of 0.78 in this study, while using the 1st derivative reflectance indices was slightly less accurate. The classification accuracy was also slightly lower when using Random Forest (RF) with all bands, sensitive bands, and S2 bands.We conclude that, of the methods tested, the red-edge bands are most sensitive to early infection, and using the 1st derivative reflectance at 714 nm or using the 1st derivative reflectance at the red-edge and blue-edge inflection point (REIP and BEIP) was sufficient for early identification. Acquiring and using additional wavelengths hardly improved the classification. Using wavelengths similar to those in the Sentienl-2 images achieved similar results, and thus can be used as a standard for dimensionality reduction of hyperspectral data pertaining to forest disease. The newly proposed VIs and 1st derivative reflectances at the yellow-edge inflection point (YEIP) and BEIP delivered better performance than the other tested indices, and could be alternatives for early identification. This study proposes simple and practical methods for early identification of wilt and provides insights for efficient data acquisition and data reduction.

Cu-based novel transition-metals chalcogenides for advanced optoelectronic and thermoelectric devices: first-principles study

Copper-containing ternary transition-metals chalcogenide semiconductors are remarkable due to their potential employment in optical and electronic devices. Here, density functional theory calculations are used to study the structural, optoelectronic, and thermoelectric properties of ternary Cu2WZ4 (Z = S, Se) materials. To accurately account for the strongly linked electronic combinations, advanced TB-mBJ approximations were used for these calculations. The formation energies are computed to predict their stability. The predicted band structure features well support the density of states calculations and verify semiconducting behavior in these studied materials. Moreover, for potential employment in optoelectronic devices, we calculated the optical parameters such as the dielectric function’s constituents, absorption coefficients, energy loss functions, reflectivity, and refractive index. The thermoelectric results revealed that the materials are suitable for thermoelectric applications. The development of remarkable and integrated semiconductor devices along with their applications would primarily benefit through these investigations.

Utilizing Density Functional Theory and SCAPS Simulations for Modeling High‐Performance MASnI3‐Based Perovskite Solar Cells

This study uses computational analysis to comprehensively investigate lead‐free organic–inorganic CH3NH3SnI3 (MASnI3)‐based perovskite solar cells (PSCs). The optoelectronic properties of MASnI3 are investigated using density functional theory with first‐principles calculations, highlighting its potential for photovoltaic applications. Key findings include the determination of a crucial bandgap (0.97 eV), identification of the onset of photon absorption at energies exceeding 2 eV, and characterization of material properties, such as the absorption and extinction coefficients, reflectivity, and refractive index. Device optimization through simulations explores parameters such as layer thickness, defect density, and different charge transport layers, resulting in a remarkable enhancement in the power conversion efficiency to 16.72%. Additionally, this study focuses on the influence of the working temperature, series resistance (R s), and shunt resistance (R sh) on the photovoltaic device performance. Hence, a high photovoltaic efficiency in MASnI3‐based PSCs can be achieved by carefully optimizing the device performance parameters and effectively managing the defect densities.

Exploring the Structural, Elastic, and Optoelectronic Properties of ScCuO3 via Density Functional Theory Approach

A thorough analysis of the structural, elastic, electronic, and optical properties of ScCuO3 perovskite is conducted using density functional theory. The compound's structural and mechanical stabilities are established under pressure. The values of Pugh's ratio (B/G) and the Zener anisotropy factor indicate that ScCuO3 displays ductile behavior and elastic anisotropy under varying pressures. The metallic behavior of ScCuO3 is confirmed by its electronic band structure, which shows that a few valence bands intersect the Fermi level. The Cu‐3d and O‐2p orbitals overlap near the Fermi level, which is found from the density of states diagram. It is also proclaimed that the Cu‐3d states strongly hybridized with O‐2p states are observed under applied pressure. Various optical properties (dielectric function, photoconductivity, absorption coefficient, loss function, reflectivity, and refractive index) are also analyzed. The compound has the highest reflectivity and is found in the low‐energy region, making it suitable as a coating material for reducing solar heating. The absorption spectra and optical conductivity indicate the metallic nature of ScCuO3, which is supported by the calculations of the electronic band structure. The current study explores the potential applications of ScCuO3 in various optoelectronic devices.

A comparative physiological study of three red varieties in the Demarcated Douro Region

In certain regions, especially those with a Mediterranean climate, that are highly susceptible to climate change, viticulture is expected to become less suitable for the production of high-quality wines. From an evolutionary perspective, grapevine varieties have evolved genetic adaptations in the form of protective mechanisms to withstand summer stress, reflecting the climatic conditions in which grapevines were initially domesticated. The in-depth knowledge of the structural and functional characteristics of grapevines can aid in the identification and selection of varieties that are better suited to adverse environmental conditions and to the increasingly challenging conditions imposed by climate change. Following, this study aims to evaluate the extent to which the water status adjustment and the leaf biophysical and biochemical processes influence the respective photosynthetic performance of a currently neglected grapevine variety, Tinto Cão (TC) and two commonly used varieties in the Douro region, Touriga-Nacional (TN) and Tinta-Roriz (TR). The experiment was undertaken in the Baixo-Corgo sub-region of the Demarcated Douro Region in the north of Portugal. Grapevine water status, chlorophyll contents, leaf reflectance indices, chlorophyll a fluorescence (modulated and transient) and leaf gas exchange (including A/PPFD and A/Ci curves) were evaluated in three different phenological stages. The results indicate that, compared to TN and TR varieties, the TC minimizes the light-harvesting system while promoting thermal energy dissipation, which can be interpreted as photoprotective mechanisms at the photosynthetic apparatus level. These mechanisms imply the downregulation of the photochemical reactions but without significant losses of net productivity compared to TN, while TR remained increased. Despite the minor expression of Tinto-Cão nowadays, this variety can also have great adaptability for very hot and sunny wine-growing regions.

Characterization of Microcrystalline Cellulose Isolated from Paper Sludge

The large amount of paper sludge generated from wastepaper industries emphasizes the importance of developing green waste management. The study aimed to characterize microcrystalline cellulose from paper sludge using different acid concentrations. The properties of chemical composition, morphological, thermal, reflectance, and crystallinity index were accessed. The disappearance of peaks in FTIR was related to the removal of amorphous structure. SEM confirmed the reduction in diameter with the decomposed temperature of 266°C. 3.0 M reflects the highest UVB at 28% and UVA at 39% due to the highest crystallinity index of 31%, which is possible for reinforcement application in film packaging.

Pressure Induced Structural, Electronic and Optical Properties of Sc2CBr2 MXene Monolayer: A Density Functional Approach

Current study theoretically examines the pressure induced structural stability, modulation in bandgap, optical properties and work function of Sc2CBr2 monolayer. The phonon dispersion relation confirms kinetic stability of monolayer. The cohesive energy and the AIMD simulation confirm the energetic and thermal stability of monolayer. The formation energy of Sc2CBr2 monolayer for all the applied pressure is computed. Bandgap of Sc2CBr2 monolayer is 1.57 eV, decreases with increasing pressure. The semiconductor to metal phase transition occurs at 16 GPa pressures. The Work function of Sc2CBr2 monolayer is increased by 12.68 % under pressure up to 16 GPa. Optical properties under the influence of pressure are studied. Absorption shows redshift and reflective index increases up to 3.7 and reflectivity increase up to 34 % with 16 GPa pressure. Hence, Sc2CBr2 monolayer has the ability to tune its physical properties under pressure. The enhanced optical properties suggest its applications in the low dimensional optoelectronic devises.

Modeling transpiration using solar-induced chlorophyll fluorescence and photochemical reflectance index synergistically in a closed-canopy winter wheat ecosystem

The joint use of solar-induced chlorophyll fluorescence (SIF) and the photochemical reflectance index (PRI) has been shown to improve gross primary productivity (GPP) estimation across various plant functional types. However, the utility of PRI in combination with SIF for transpiration (T) estimation has not yet been explored. Additionally, current SIF-driven transpiration models including linear models, semi-mechanical models (combination of canopy conductance, gC, derived from a SIF and vapor pressure deficit, VPD, driven linear model with the Penman-Monteith model), and hybrid models (combination of gC derived from a SIF and VPD driven machine learning model with the Penman-Monteith model) have rarely been mutually assessed. Based on concurrent remotely sensed SIF and PRI, and eddy covariance flux measurements during one growing season for a winter wheat ecosystem in northern China, we investigated the mediating effect of PRI on SIF-driven T estimation under different VPD conditions and compared the performance of linear, semi-mechanical, and hybrid models in estimating T. Our results showed that the mediating effect of PRI on T described in the SIF-driven linear, semi-mechanistic, and hybrid models was significant under high VPD conditions rather than under low VPD conditions. Specifically, based on T partitioned using an underlying water use efficiency method as a benchmark, the root mean square error (RMSE) value of the PRI-mediated linear, semi-mechanistic, and hybrid models was 28.01 W/m2, 22.25 W/m2, and 28.71 W/m2 lower, respectively, than those of the corresponding models without PRI when VPD was >1.5 kPa. Based on T partitioned using a transpiration estimation algorithm as a benchmark, these three models also exhibited a significant reduction in RMSE under high VPD conditions after considering PRI. The main rationale behind the PRI improvement is that PRI can track photosynthetic dynamics under high VPD conditions. Based on the simulation results of the Soil-Canopy-Observation of Photosynthesis and Energy fluxes (SCOPE) model, PRI can serve as an indicator for non-photochemical quenching (NPQ) within this ecosystem. Consequently, PRI can enhance the capability of SIF to characterize the energy dissipation of photosynthetically active radiation and help SIF to yield more accurate information on GPP and gc under high VPD conditions. Finally, the order of model performance in estimating T was generally hybrid model > semi-mechanistic model > linear model. Our findings show the effectiveness of PRI for improving SIF-driven transpiration estimation under high VPD conditions and provide a new hybrid model for estimating T from SIF.

Effect of duration of hypertension on arterial stiffness

Background: Hypertension is one of the common and prime causes contributing to 18% of deaths globally. Prevalence of essential hypertension increases with age, and individuals with relatively high blood pressure at younger ages are at increased risk for the subsequent complications of hypertension. The morphological and physiological changes in vasculature have been described in the evolution and maintenance of hypertension. Hypertension can increase the risk of cerebral, cardiac, and renal events. Aims and Objectives: (1) To record the arterial stiffness index (SI) and reflection index (RI) in subjects with hypertension and a control group of age-matched normotensives. (2) To compare the above vascular parameters between control and hypertensive subjects. (3) To classify the hypertensive subjects based on the duration of the disease and compare the vascular parameters among them. Materials and Methods: A cross-sectional study on 160 subjects aged between 30 and 60 years was conducted. Institutional ethical committee approval and informed written consent were obtained. They were divided into four groups. Group 1- control group (Healthy subjects), and study group of hypertensives are classified into three groups based on the duration of illness. Arterial stiffness was evaluated by SI and RI, calculated from recording digital volume pulse (DVP). DVP was measured by an instrument known as finger pulse photo plethysmography. Results: The results were analyzed using analysis of variance test and were considered statistically significant with P &lt; 0.05 with respect to arterial stiffness indices compared with the duration of hypertension. Conclusion: This study concludes a strong positive correlation between two indices of arterial stiffness that is the RI and SI values increases with the duration of hypertension.

Impact of samarium on magnetic and optoelectronic properties of magnesium-based MgSm2X4 (X = S and Se) spinels for spintronics.

Investigating novel compounds has become necessary due to the need for sophisticated materials in optoelectronic devices and spintronics. Because of their unique properties, magnesium-based spinels MgSm2X4 (X = S and Se) are very promising for these applications. We used the spin-polarized PBEsol for structural properties and the PBEsol functional for mechanical behavior, both using the WIEN2k code. Both compounds' stability in the magnetic and non-magnetic phases was validated by the Birch-Murnaghan equation of state, and their stability in the cubic phase was verified by the Born stability criterion. Their ductile character was shown by the computation of Pugh's ratio and Poisson ratio. Both MgSm2S4 and MgSm2Se4 display metallic behavior in the spin-up channel and semiconducting behavior in the spin-down channel, indicating a half-metallic nature, according to TB-mBJ potential calculations. With total magnetic moments of 20 μB, both materials showed ferromagnetic properties. Samarium ions contributed 5.27 μB for MgSm2S4 and 5.34 μB for MgSm2Se4. Furthermore, we computed optical parameters in the energy range of 0 to 15 eV, such as absorption, extinction coefficient, reflectivity, dielectric function, and refractive index. Our results demonstrate the potential of MgSm2X4 spinels for future technological developments by revealing their prospective optoelectronic and spintronic applications.

Pressure induced mechanical, elastic, and optoelectronic characteristics of Cd0.75Zn0.25Se alloy.

The change in composition and pressure, both of which lead to new desired properties by altering the structure, is particularly important for improving device performance. Given this, we focused here on the mechanical, elastic, and optoelectronic characteristics of the Cd0.75Zn0.25Se alloy using density functional theory at various pressures from 0GPa to 20GPa. It is found that the bulk modulus of the material rises with increasing pressure and exhibits mechanical stability as well as cubic symmetry. In addition, the increased pressure leads to a rise in the direct bandgap energy of the material from 2.03eV to 2.48eV. The absorption coefficient of the alloy also increases as the pressure increases, where the effective range of absorption covers the broad spectrum of light in the visible range from orange to cyan. This is due to the electronic transitions caused by the altered pressure. The optical parameters, including optical conductivity, extinction coefficient, reflection, and refractive index, are also analyzed under the influence of pressure. Based on this research, effective applications of the Cd substituted Zn-chalcogenides (CdZnSe) alloys in the fields of optoelectronics and photovoltaics are outlined, especially concerning fabricating solar cells, photonic devices, and pressure sensors for space technology.

A DFT investigation on structural, electronic, magnetic, optical, elastic and hydrogen storage properties of Ru-based hydride-perovskites XRuH3 (X = Cr, V, Ni).

The present investigation delves into various physical properties exhibited by CrRuH3, VRuH3 and NiRuH3. Notably adopting a stable cubic configuration, both compounds manifest a distinct metallic demeanor characterized by an absolute absence of band gap. In-depth analysis through Total Density of States (TDOS) and Partial Density of States (PDOS) justify this metallic conduct by distinctly showcasing peak conductivity at the Fermi level. The materials' magnetic behavior reveals an antiferromagnetic disposition for CrRuH3 and NiRuH3, while their intrinsic attributes emerge as anisotropic and rigid. Applying Poisson's ratio (ν) and the B/G ratio, all investigated compounds show ductility, but the CrRuH3 is superior among them. The heightened values of Young's modulus, Bulk modulus, and mean shear modulus observed in CrRuH3 underscore its enhanced rigidity as compared to VRuH3 and NiRuH3. Within the optical realm, CrRuH3 displays notable optical conductivity and absorption, particularly within the lower energy spectrum. Remarkably, at 0 eV, CrRuH3 showcases elevated reflectivity and refractive index as compared to the other investigated materials. On the hydrogen storage front, XRuH3 (X = Cr, V, Ni) exhibit promising potential, yet CrRuH3 emerges as the more favorable candidate for hydrogen storage applications.

Low reflective index, highly transparent, and ultra-low dielectric constant materials prepared via effective copolymerization of 4-methyl-1-pentene and a Si-containing α,ω-diolefin

A series of ultra-low dielectric constant materials containing C–Si-cyclic units were prepared. The new copolymers showed stable and ultra-low dielectric constants below 2.0, tunable glass transition temperature and mechanical performance.

Enhancing the potential of phenomic and genomic prediction in winter wheat breeding using high-throughput phenotyping and deep learning.

Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learning (DL) for the phenomic or multi-trait (MT) genomic prediction of grain yield (GY), test weight (TW), and grain protein content (GPC) in winter wheat. Significant correlations were observed between agronomic traits and HTP-based traits across different growth stages of winter wheat. Using a deep neural network (DNN) model, HTP-based phenomic predictions showed robust prediction accuracies for GY, TW, and GPC for a single location with R2 of 0.71, 0.62, and 0.49, respectively. Further prediction accuracies increased (R2 of 0.76, 0.64, and 0.75) for GY, TW, and GPC, respectively when advanced breeding lines from multi-locations were used in the DNN model. Prediction accuracies for GY varied across growth stages, with the highest accuracy at the Feekes 11 (Milky ripe) stage. Furthermore, forward prediction of GY in preliminary breeding lines using DNN trained on multi-location data from advanced breeding lines improved the prediction accuracy by 32% compared to single-location data. Next, we evaluated the potential of incorporating HTP-based traits in multi-trait genomic selection (MT-GS) models in the prediction of GY, TW, and GPC. MT-GS, models including UAV data-based anthocyanin reflectance index (ARI), green chlorophyll index (GCI), and ratio vegetation index 2 (RVI_2) as covariates demonstrated higher predictive ability (0.40, 0.40, and 0.37, respectively) as compared to single-trait model (0.23) for GY. Overall, this study demonstrates the potential of integrating HTP traits into DL-based phenomic or MT-GS models for enhancing breeding efficiency.

Functional-Input Gaussian Processes with Applications to Inverse Scattering Problems

Surrogate modeling based on Gaussian processes (GPs) has received increasing attention in the analysis of complex problems in science and engineering. Despite extensive studies on GP modeling, the developments for functional inputs are scarce. Motivated by an inverse scattering problem in which functional inputs representing the support and material properties of the scatterer are involved in the partial differential equations, a new class of kernel functions for functional inputs is introduced for GPs. Based on the proposed GP models, the asymptotic convergence properties of the resulting mean squared prediction errors are derived and the finite sample performance is demonstrated by numerical examples. In the application to inverse scattering, a surrogate model is constructed with functional inputs, which is crucial to recover the reflective index of an inhomogeneous isotropic scattering region of interest for a given far-field pattern.

Reflective Index Modulation for IRS Assisted Integrated Data and Energy Transfer

Reflective Index Modulation for IRS Assisted Integrated Data and Energy Transfer

Spectral phenology features of Platycladus orientalis (L.) Franco

Spectral plant phenology, based on time series of vegetation indices, is a useful tool for monitoring vegetation condition and climatic changes. The chlorophyll/carotenoid index (CCI) and photochemical reflectance index (PRI) show promise for spectral phenology of coniferous plants. This study evaluates the potential of using CCI, PRI, and the normalised difference vegetation index (NDVI) as phenological metrics for Platycladus orientalis. The study found a strong correlation between the annual dynamics of the chlorophyll/carotenoid ratio (Chl/Car) and the time series of CCI (R2 = 0.89, p &lt; 0.001) and PRI (R2 = 0.85, p &lt; 0.001). The CCI time series was used to determine the beginning and end of the phenological vegetation period (PVP) of P. orientalis through a double logistic regression model. The PRI model had an error of approximately two weeks in predicting the beginning and end of the PVP, with a tendency to overestimate the duration of the PVP. The use of NDVI as a model is unsuitable for describing the P. orientalis 2023 PVP.