Spectral Simulation Research Articles

Potential of Optical Spaceborne Sensors for the Differentiation of Plastics in the Environment

Plastics are part of our everyday life, as they are versatile materials and can be produced inexpensively. Approximately 10 Gt of plastics have been produced to date, of which the majority have been accumulated in landfills or have been spread into the terrestrial and aquatic environment in an uncontrolled way. Once in the environment, plastic litter—in its large form or degraded into microplastics—causes several harms to a variety of species. Thus, the detection of plastic waste is a pressing research question in remote sensing. The majority of studies have used Sentinel-2 or WorldView-3 data and empirically explore the usefulness of the given spectral channels for the detection of plastic litter in the environment. On the other hand, laboratory infrared spectroscopy is an established technique for the differentiation of plastic types based on their type-specific absorption bands; the potential of hyperspectral remote sensing for mapping plastics in the environment has not yet been fully explored. In this study, reflectance spectra of the five most commonly used plastic types were used for spectral sensor simulations of ten selected multispectral and hyperspectral sensors. Their signals were classified in order to differentiate between the plastic types as would be measured in nature and to investigate sensor-specific spectral configurations neglecting spatial resolution limitations. Here, we show that most multispectral sensors are not able to differentiate between plastic types, while hyperspectral sensors are. To resolve absorption bands of plastics with multispectral sensors, the number, position, and width of the SWIR channels are decisive for a good classification of plastics. As ASTER and WorldView-3 had/have narrow SWIR channels that match with diagnostic absorption bands of plastics, they yielded outstanding results. Central wavelengths at 1141, 1217, 1697, and 1716 nm, in combination with narrow bandwidths of 10–20 nm, have the highest capability for plastic differentiation.

Features of activation energy for a flow with microrotation near stagnation region and unbounded domain : a spectral simulation

This article is motivated to find the impact of various flow controlling parameters such as viscous dissipation, negative and positive values of activation energy on MHD stagnation point micropolar nanofluid flow over a surface. However, negative activation energy is scarce in practice, but the impact of negative values of activation energy could not be neglected as seen in chemical processes. The present mathematical model is solved with successive linearization method (a spectral technique). The velocity, angular velocity, temperature and concentration profiles are drawn by varying flow controlling parameters. The bar diagrams for skin friction, Nusselt number, Sherwood number and couple stress are also displayed. Results indicate that the activation energy boosts the concentration profile up. The negative values of activation energy have higher impact on concentration curves compared to positive values. Arrhenius function decays as activation energy enlarges. This eventually promotes the generative chemical reaction due to which concentration rises. By varying thermophoretic parameter from 0.1 to 0.3, 88.65% and 8.34% enhancement is captured in heat transfer and mass transfer respectively.

Spectral simulation and materials design for camouflage textiles coloration against materials of multidimensional combat backgrounds in visible and near infrared spectrums

Spectral simulation and materials design for camouflage textiles coloration against materials of multidimensional combat backgrounds in visible and near infrared spectrums

Dual plasmonic modes in the visible light region in rectangular wave-shaped surface relief plasmonic gratings

Rectangular wave-shaped surface-relief plasmonic gratings (RSR-PGs) have been fabricated from a hybrid polymer by employing a simple nanoimprint photocuring lithography technique using a silicon template, followed by gold nanolayer metallization on top of the formed replica structure. By forming a one-dimensional (1D) plasmonic grating with a periodicity of approximately 700 nm, a reflectance spectral dip was experimentally observed in the visible light region, from 600 to 700 nm, with increasing incident angle from 45° to 60°. This dip can be associated with surface plasmon resonance (SPR) wave excitation, which is coupled with the diffraction order m = − 2. The calculations of reflectance spectra simulation using the rigorous coupled wave analysis (RCWA) method have also been carried out, resulting in the appearance of an SPR dip in the range of 600–700 nm, for incident angles in the range of 45°–65°, which agrees with the experimental results. Interestingly, these RSR-PGs show richer plasmon characteristics than the sine-wave-shaped plasmonic gratings. The experimental and spectral simulation results revealed two different plasmonic excitation modes: long-range SPR and quasi-localized SPR (LSPR). While the long-range SPR was formed above the ridge sections along the grating structure surface, the quasi-localized SPR was locally formed inside the groove. In addition, for RSR-PGs with a narrow groove section, the long-range SPR seems to be coupled with the periodic structure of the grating, resulting in the appearance of plasmonic lattice surface resonance (LSR) that is indicated by a narrower plasmon resonance dip. These characteristics are quite different from those found in the sine wave-shaped plasmonic gratings. The present results may thus provide better insights for understanding the plasmon excitations in this type of rectangular plasmonic grating and might be useful for designing their structure for certain practical applications.

A semi-analytical radiative transfer model for explaining soil spectral features

Spectral techniques play a key role in the estimation of large-scale soil parameters, but most of the current estimation models are data-driven models lacking a physical basis. Therefore, in this study, we developed a novel radiative transfer model named the soil multifactor radiative transfer (SMRT) model that predicts the soil spectra as a function of the soil organic matter (SOM), particle size distribution (PSD), and iron oxide content. The SMRT model explains the soil spectral features commonly used in the data-driven estimation models and can be used to explore the mechanisms by which soil-related parameters affect soil spectra according to the model parameters. A total of 79 soil profile datasets were used in the experiments conducted in this study. The reflectance of the soil after air-drying can ignore the effect of moisture, thereby ensuring that the main influences on the soil spectra are the SOM, iron oxide content, and PSD. The SMRT model performed very well in the spectral simulation (R2 = 0.9681, RMSE = 0.0266, MAE = 0.0160). The absorption and scattering coefficients of the SMRT model explain the radiative transfer mechanism for the color representation of black soil and laterite soil. The spectral features around 1910 nm and 2210 nm are caused by not only the soil moisture (SM) and clay mineral content, but several other factors, including the SOM, iron oxide content, and PSD. Overall, these findings show that the SMRT model has a superior ability to describe the soil radiative transfer processes. However, as the coefficients in the SMRT model are dependent on the soil properties, the coefficients should be calibrated by an optimization algorithm and cannot be constants, which leads to the requirement for soil samples to calibrate the coefficients in practical applications.

Adapting FEFF to 5f angular momentum coupling

It is demonstrated here that the spectral simulation program FEFF can be adapted to include the effects of 5f total angular momentum coupling in the fluorite actinide dioxide systems ThO2, UO2, and PuO2. N4,5 x-ray absorption spectra produced with this modified FEFF approach will be compared to the previous experimental results, obtaining a strong agreement between the two.

Apex-shifted Radon transform for baseline-subtraction-free (BSF) damage scattered wave extraction

In ultrasonic structural health monitoring (SHM) and nondestructive evaluation (NDE), the scattered waves caused by damage sites and defects are the key to damage diagnosis. However, structural components and boundaries also interact with traveling waves, creating events that can bury damage scattered waves. The baseline subtraction method, which directly subtracts the waveform of a damage signal from that of a pristine baseline signal, is a common processing technique to separate these damage scattered waves. However, baseline subtraction is less effective when a component is measured in different environmental/loading conditions from when its baseline was recorded. For instance, baseline subtraction can be ineffective in aerospace structural parts because such parts expect significant and routine changes in ambient temperature, pressure, and humidity. To overcome the limitations of baseline subtraction, this paper proposes to develop an spex-shifted Radon transform (ASRT)-based damage scattered event extraction technique without baseline subtraction. Our proposed ASRT method converts the original time-space domain signals to a time delay–curvature–apex offset domain, which targets specific geometries of scattered/reflected waves in the domain and compresses them into a single point-like region in the new domain. In this domain, identifying and isolating targeted events becomes significantly easier. To benchmark the performance of this baseline-subtraction-free (BSF) method, ASRT is applied for signals acquired from (1) spectral finite element-based simulations to scan a water-immersed steel specimen (2) 3-D wave simulations in a bent aluminum plate, and (3) a full matrix capture for experimentally scanning a high-density polyethylene (HDPE) with multiple holes. The goal in each case is to target and separate events of interest from the original signals using the proposed algorithm. The results suggest the ASRT method is effective as a damage scattered wave extraction tool for ultrasonic SHM and NDE.

Spectral Simulation and Error Analysis of Dusty Leaves by Fusing the Hapke Two-Layer Medium Model and the Linear Spectral Mixing Model

The Hapke two-layer medium model is an efficient way of simulating the spectra of dusty leaves. However, the simulation accuracy is low when the amount of dustfall is small. To solve this problem, we introduced the dust coverage factor and the linear spectral mixing model, to improve the accuracy of the Hapke two-layer medium model. Firstly, based on the assumption of spherical dust particles, the arrangement and accumulation mode of the particles were set, and the coverage factor and accumulation thickness of particles in the leaf area were calculated. Then, the coverage factor was used as an abundance. Endmembers were the spectra of dust-free leaves (measured) and dust-covered leaves (simulated by model), and the final simulated spectra were calculated using linear spectral mixing theory. This study presents the following findings: (1) When the coverage factor was calculated using the exponential model, the maximum difference between the corrected simulated spectra and the measured spectra was 3.4%, and the maximum difference between the original simulated spectra and the measured spectra was 15.2%. The accuracy of the corrected spectra is much higher than that of the original simulated spectra. (2) In this study, the physical thickness and optical thickness calculated by the Hapke two-layer medium model are equivalent, which is quite different from the actual dust accumulation. When the linear spectral mixing model is introduced, to modify the simulation value when the number of dust particles accumulated is less than one layer, the spectral endmember value of the simulated dust leaf is replaced by the simulation spectrum when the number of dust particles accumulated is exactly one layer. The calculated cor-rection spectrum has high rationality and credibility. This finding may be beneficial for monitoring amounts of dustfall accurately using remote sensing in mining areas.

GSV-L: A general spectral vector model for hyperspectral leaf spectra simulation

Leaf optical spectra determine vegetation canopy optical spectra. Physically based leaf models are relatively complicated as they require many biophysical and biochemical parameters that are usually difficult to obtain. The aim of this study is to develop a new empirical model, the general spectral vector-leaf (GSV-L) model using globally collected leaf spectra data. A global field-measured leaf spectra database, including 66,478 leaf reflectance and 3575 transmittance spectra in the wavelength range of 400–2400 nm, was first constructed. The singular value decomposition (SVD) method was applied to the field data matrix to derive the spectral vectors for leaf spectral modeling. The SVD method was also compared with the successive approximation (SA) and principal component analysis (PCA) methods using the same training and validation datasets, and the GSV-L model was compared with two other physical models, PROSPECT and LEAF-SIP. The GSV-L model can be used to simulate full leaf reflectance and transmittance spectra using a few wavelengths in different bands with very high R2 (0.99, 0.99), small RMSE (0.014, 0.014) and bias (0, 0.002) values. The model also performs better than the PROSPECT and LEAF-SIP models for leaf spectral simulation. The coefficients of the reflectance spectral vectors can be used to estimate leaf structure parameters, equivalent water thickness, and leaf biochemical contents. As an efficient and accurate approach for leaf hyperspectral modeling, GSV-L can also be integrated with various canopy reflectance and land surface models.

Optical Characteristics Simulation of Wheat Stripe Rust Urediospores

Stripe rust is one of the most common diseases challenging the safe production of wheat. Rapid identification and analysis of urediospores, responsible for disease transmission, is the key to preventing and controlling stripe rust. In this study, combined with chemical analysis, spectral analysis method and finite element simulation of the intrinsic characteristics of urediospore were studied in details. Firstly, a comparative analysis of the urediospore components was carried out by HPLC-MS, and a total of 31 components were extracted. On this basis, a 3D urediospore model was established by using FEM software, the characteristic frequencies and modes were calculated. The results shown that and the resonance frequencies and modes of the elliptical structure were lower and more diverse. The method and conclusion can lay a theoretical foundation for the accurate monitoring and early control of wheat stripe rust urediospores.

Structural, Spectral, Molecular Docking, and Molecular Dynamics Simulations of Phenylthiophene-2-Carboxylate Compounds as Potential Anticancer Agents

Important biological compounds, namely, methyl 3-amino-4-(4-bromophenyl)thiophene-2-carboxylate (BPTC) and methyl 3-amino-4-(4-chlorophenyl)thiophene-2-carboxylate (CPTC), were characterized using complementary techniques of Fourier transform infrared (FT-IR), Raman spectroscopy. Nuclear magnetic resonance spectroscopy (NMR) confirmed the structural features, while Ultra Violet–Visible Spectroscopy was used to investigate the electronic properties of both compounds. The quantum chemical calculations for both compounds were performed using the DFT/B3LYP functional with the 6-311++G(d,p) basis set. This study computes electrostatic potential observation, electron localization function (ELF) assessment, and atoms-in-molecules (AIM) analysis. In the present investigation, the global hardness, chemical softness, electrophilicity, nucleophilicity indices, and dipole moment of both compounds were calculated. In addition, a molecular docking analysis was conducted to determine the binding potential of target molecules with protein tyrosine phosphatase. A 200-ns molecular dynamics (MDs) simulation had been performed to assess the compound’s binding stability.

Application of instantaneous spectral decomposition-based porosity simulations for imaging shallow-marine stratigraphic traps of Lower-Eocene carbonates sequences of Indus Basin, Onshore Pakistan

Application of instantaneous spectral decomposition-based porosity simulations for imaging shallow-marine stratigraphic traps of Lower-Eocene carbonates sequences of Indus Basin, Onshore Pakistan

Two-component three-dimensional atomic Bose-Einstein condensates supporting complex stable patterns

We report the computational discovery of complex, topologically charged, and spectrally stable states in three-dimensional multicomponent nonlinear wave systems of nonlinear Schr\"odinger type. While our computations relate to two-component atomic Bose-Einstein condensates in parabolic traps, our methods can be broadly applied to high-dimensional nonlinear systems of partial differential equations. The combination of the so-called deflation technique with a careful selection of initial guesses enables the computation of an breadth of patterns, including ones combining vortex lines, rings, stars, and vortex labyrinths. Despite their complexity, they may be dynamically robust and amenable to experimental observation, as confirmed by Bogoliubov--de Gennes spectral analysis and numerical evolution simulations.

Prototropically Controlled Dynamics of Cytosine Photodecay

The effect of the existence of several prototropic tautomers of cytosine on its UV/vis spectra and the excited state decay dynamics is studied by spectral and nonadiabatic molecular dynamics (NAMD) simulations in connection with the mixed-reference spin-flip time-dependent density functional theory (MRSF-TDDFT) method. Simulated UV/vis spectra provide a strong indication that the H3N keto-amino cytosine tautomer (the least anticipated species) may be present under experimental conditions. The NAMD simulations yield a wide range of excited state decay constants for various tautomers of cytosine, ranging from ∼1.3 ps for the biologically relevant H1N keto-amino tautomer to ∼0.1 ps for the keto-imino tautomer. The slowness of the H1N decay dynamics follows from the presence of a barrier on the excited state energy surface separating the Franck-Condon structure from the major decay funnel, the conical intersection seam. It is suggested that the experimentally observed photodecay dynamics may result from a combination of the decay processes of various tautomers (H3N in particular) present simultaneously under the experimental conditions.

Research on Stellar Spectrum Simulation Method Based on Genetic Algorithm and Fuzzy PID Composite Control

For the current spectral simulation based on Digital Micromirror, the spectral simulation unit has different bias properties and nonlinear modulation, which leads to the lack of a spectral simulation method for multiple color temperature modulation. In this paper, a stellar spectrum simulation method based on Genetic Algorithm and fuzzy PID compound control was proposed. It analyzed the composition and working principle of the stellar spectrum simulation system, designed the corresponding matrix algorithm, studied the compound control spectral simulation algorithm of Genetic Algorithm and fuzzy PID, constructed a dual-input, three-output fuzzy PID controller architecture, and designed the Genetic Algorithm dual-optimized fuzzy PID control algorithm. In this research, an experimental platform was built to verify the generalization and simulation accuracy of the Genetic Algorithm and fuzzy PID compound control stellar spectrum simulation method based on the 2500K-10000K color temperature spectral curve as the target. The results indicated that the error of 2500K-10000K spectral simulation was between -2.91% and 2.94%, and the error of spectral curve area simulation was between -0.18% and 0.22%.As the smoothing of the star spectrum curves fails to verify the simulation ability of detailed characteristics such as peaks and troughs, the AM1.5 solar spectrum is taken as the simulation object, which verifies the performance of the star spectrum simulation method based on a genetic algorithm and a fuzzy PID integration.On this basis, the AM1.5 solar spectrum was taken as the simulation target to verify the ability to simulate detailed features such as wave peaks and troughs based on Genetic Algorithm with fuzzy PID compound control stellar spectrum simulation method. The results revealed that the accuracy of the single-point spectral simulation of AM1.5 solar spectrum is -5.76%, and the spectral curve area simulation error is 0.07%. The proposed method has the ability to simulate a wide range of color temperature targets with high accuracy. It has the ability to simulate detailed features such as wave peaks and troughs. It can provide a theoretical and technical basis for the ground calibration of the high-precision star sensor development.

Synthesis, structure, and characterisation of a ferromagnetically coupled dinuclear complex containing Co(II) ions in a high spin configuration and thiodiacetate and phenanthroline as ligands and of a series of isomorphous heterodinuclear complexes containing different Co : Zn ratios.

We report the synthesis, crystal structure, and characterisation of a dinuclear Co(II) compound with thiodiacetate (tda) and phenanthroline (phen) as ligands (1), and of a series of metal complexes isomorphous to 1 with different Co : Zn ratios (2, 4 : 1; 3, 1 : 1; 4, 1 : 4; 5, 1 : 10). General characterisation methodologies and X-ray data showed that all the synthesised complexes are isomorphous to Zn(II) and Cu(II) analogues (CSD codes: DUHXEL and BEBQII). 1 consists of centrosymmetric Co(II) ion dimers in which the ions are 3.214 Å apart, linked by two μ-O bridges. Each cobalt atom is in a distorted octahedral environment of the N2O3S type. UV-vis spectra of 1 and 5 are in line with high spin (S = 3/2) Co(II) ions in octahedral coordination and indicate that the electronic structure of both Co(II) ions in the dinuclear unit does not significantly change relative to that of the magnetically isolated Co(II) ion. EPR spectra of powder samples of 5 (Co : Zn ratio of 1 : 10) together with spectral simulation indicated high spin Co(II) ions with high rhombic distortion of the zfs [E/D = 0.31(1), D > 0]. DC magnetic susceptibility experiments on 1 and analysis of the data constraining the E/D value obtained by EPR yielded g = 2.595(7), |D| = 61(1) cm-1, and an intradimer ferromagnetic exchange coupling of J = 1.39(4) cm-1. EPR spectra as a function of Co : Zn ratio for both powder and single crystal samples confirmed that they result from two effective S' = 1/2 spins that interact through dipolar and isotropic exchange interactions to yield magnetically isolated S' = 1 centres and that interdimeric exchange interactions, putatively mediated by hydrophobic interactions between phen moieties, are negligible. The latter observation contrasts with that observed in the Cu(II) analogue, where a transition from S = 1 to S' = 1/2 was observed. Computational calculations indicated that the absence of the interdimeric exchange interaction in 1 is due to a lower Co(II) ion spin density delocalisation towards the metal ligands.

Recent progress in solid-state NMR of spin-½ low-γ nuclei applied to inorganic materials.

Significant technological and methodological advances in solid-state NMR techniques in recent years have increased the accessibility of nuclei with small magnetic moments (hereafter termed low-γ) underpinning an increased range of applications of such nuclei. These methodological advances are briefly summarised, including improvements in hardware and pulse sequences, as well as important developments in associated computational methods (e.g. first principles calculations, spectral simulation). Here spin-½ nuclei are the focus, with this Perspective complementing a very recent review that looked at half-integer spin low-γ quadrupolar nuclei. Reference is made to some of the original reports of such spin-½ nuclei, but recent progress in the relevant methodology and applications to inorganic materials (most within the last 10 years) of these nuclei are the focus. An overview of the current state-of-the-art of studying these nuclei is thereby provided for both NMR spectroscopists and materials researchers.

Stochastic assembly of biomacromolecular complexes: impact and implications on charge interpretation in native mass spectrometry.

Native mass spectrometry is a potent method for characterizing biomacromolecular assemblies. A critical aspect to extracting accurate mass information is the correct inference of the ion ensemble charge states. While a variety of experimental strategies and algorithms have been developed to facilitate this, virtually all approaches rely on the implicit assumption that any peaks in a native mass spectrum can be directly attributed to an underlying charge state distribution. Here, we demonstrate that this paradigm breaks down for several types of macromolecular protein complexes due to the intrinsic heterogeneity induced by the stochastic nature of their assembly. Utilizing several protein assemblies of adeno-associated virus capsids and ferritin, we demonstrate that these particles can produce a variety of unexpected spectral appearances, some of which appear superficially similar to a resolved charge state distribution. When interpreted using conventional charge inference strategies, these distorted spectra can lead to substantial errors in the calculated mass (up to ∼5%). We provide a novel analytical framework to interpret and extract mass information from these spectra by combining high-resolution native mass spectrometry, single particle Orbitrap-based charge detection mass spectrometry, and sophisticated spectral simulations based on a stochastic assembly model. We uncover that these mass spectra are extremely sensitive to not only mass heterogeneity within the subunits, but also to the magnitude and width of their charge state distributions. As we postulate that many protein complexes assemble stochastically, this framework provides a generalizable solution, further extending the usability of native mass spectrometry in the characterization of biomacromolecular assemblies.

Layer-resolved characterization of subsurface of materials usmg ultrafast two-dimensional electronic spectroscopy

Surface of matter normally contains sublayers with molecular or electronic structure different from the outmost surface and the bulk, which may play a critical role in surface energy and/or charge transfer processes. Therefore, the development of layer-resolved characterization methods is of great importance for surface science and techniques. Although optical spectroscopy methods are very sensitive to structure, their spatial resolution is often much larger than the inter-layer distance of the sublayers, resulting in the inability to achieve laminar resolution. In this work, we discuss the possibilities of utilizing two-dimensional (2D) electronic spectroscopy to distinguish spectral information and energy transfer between different layers, which cannot otherwise be obtained from linear spectroscopy methods owing to lineshape broadening. By theoretical 2D spectral simulations, we investigated two layered systems by numerical simulations, material surface:subsurface:bulk and molecule:surface:subsurface:bulk. The directional energy transfer rates from the bulk to the surface layer owing to the surface-bulk coupling was preset. Due to the fact that the energy transfer between the subsurface and the outermost surface layer is faster than that between the bulk and the outermost surface layer, there will be special time periods during which only the former takes place and gives rise to the distinguishable dynamics of off-diagonal peaks. Our simulation results showed that by analyzing the difference between the projections of the off-diagonal peak, the excitation energy of the surface, subsurface and bulk layers can be determined. Furthermore, for the four-layer system, the off-diagonal peaks can be kept away from the interference of diagonal peaks, providing a better chance for realizing laminar resolution compared with the three-layer system.

One-color resonance enhanced two-photon ionization spectroscopy of phenylacetonitrile and its Franck-Condon simulation

Phenylacetonitrile (PAN) is widely used in the synthesis of medicines, pesticides, dyes, optoelectronic materials and quinoline derivatives, and has attracted much attention in related fields. In this paper, we report the one-color resonance enhanced two-photon ionization spectra of PAN obtained with ultrasonic molecular beam technique for the first time. The band origin of the S<sub>1</sub> ← S<sub>0</sub> electronic transition is determined to be (37646 ± 2) cm<sup>–1</sup>. Density functional theory B3LYP/6-311G++(d, p) and B3LYP/aug-cc-pvtz are used to calculate the structures, energy and vibrational frequencies of the molecule. Based on these calculations Franck-Condon spectral simulations are performed. The measured vibrational frequencies are analyzed in detail. Combined with theoretical calculation, the spectral assignments are given as accurately as possible. Theoretical and experimental results are in good agreement with each other, and show that the spectrum in the low frequency region has a great signal-noise ratio and resolution, while in the high frequency region the spectrum shows opposite characteristics, revealing that the high background in high frequency region originates from dense and weak overtone and combined vibrations. Many spectral bands are found, and most of them may be assigned to the in-plane ring deformation, and theoretical calculations suggest that this is related to the expansion of the aromatic ring during the transition.