Reflectance Curves Research Articles

Machine learning for neutron reflectometry data analysis of two-layer thin films * *Notice of Copyright: This manuscript has been authored by UT-Battelle, LLC under Contract DE-AC05-00OR22725 with the U.S. Department of Energy (DOE). The U.S. government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish

Neutron reflectometry (NR) is a powerful tool for probing thin films at length scales down to nanometers. We investigated the use of a neural network to predict a two-layer thin film structure to model a given measured reflectivity curve. Application of this neural network to predict a thin film structure revealed that it was accurate and could provide an excellent starting point for traditional fitting methods. Employing prediction-guided fitting has considerable potential for more rapidly producing a result compared to the labor-intensive but commonly-used approach of trial and error searches prior to refinement. A deeper look at the stability of the predictive power of the neural network against statistical fluctuations of measured reflectivity profiles showed that the predictions are stable. We conclude that the approach presented here can provide valuable assistance to users of NR and should be further extended for use in studies of more complex n-layer thin film systems. This result also opens up the possibility of developing adaptive measurement systems in the future.

Towards reflectivity profile inversion through artificial neural networks

The goal of specular neutron and x-ray reflectometry is to infer a material’s scattering length density (SLD) profile from its experimental reflectivity curves. This paper focuses on the investigation of an original approach to the ill-posed non-invertible problem which involves the use of artificial neural networks (ANNs). In particular, the numerical experiments described here deal with large data sets of simulated reflectivity curves and SLD profiles, and aim to assess the applicability of data science and machine learning technology to the analysis of data generated at large-scale neutron scattering facilities. It is demonstrated that, under certain circumstances, properly trained deep neural networks are capable of correctly recovering plausible SLD profiles when presented with previously unseen simulated reflectivity curves. When the necessary conditions are met, a proper implementation of the described approach would offer two main advantages over traditional fitting methods when dealing with real experiments, namely (1) sample physical models are described under a new paradigm: detailed layer-by-layer descriptions (SLDs, thicknesses, roughnesses) are replaced by parameter-free curves ρ(z), allowing a priori assumptions to be used in terms of the sample family to which a given sample belongs (e.g. ‘thin film,’ ‘lamellar structure’,etc.); (2) the time required to reach a solution is shrunk by orders of magnitude, enabling faster batch analysis for large datasets.

Insights into Particle-Bound Metal(loid)s in Winter Snow Cover: Geochemical Monitoring of the Korkinsky Coal Mine Area, South Ural Region, Russia

Snow plays an important role in air quality and winter geochemical monitoring in the South Ural region. This study deals with the air pollution monitoring of particle-bound metal(loid) concentrations using snow cover around the deepest coal mine in Eurasia, the Korkinsky coal mine. We studied the concentrations and ratios of suspended and dissolved forms of metal(loid)s (Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sb, Sr, and Zn) in snow samples. We examined 56 snow cover samples, collected at 12 sites located north, south, east and west of the Korkinsky coal mine. All snow samples were taken in January 2020. The spectral reflectance curves, cluster analysis, and spatial distribution maps were used to evaluate the potential sources of PM-bound metal(loid)s and the potential relationship among them. The highest concentrations (μg/L) were reported for Fe, Al, and Zn. In addition to the mine influence, burning coal for residential heating was identified as the major anthropogenic metal(loid) source. It was shown that elevated concentrations of some trace metals in snow samples were associated with southerly winds and the location of spoil heaps.

The oasis regional small and medium lake water transparency monitoring research and impact factor analysis based on field data combined with high resolution GF-1 satellite data

Water transparency is an important parameter to characterize water quality of rivers, lakes and wetlands. We measured the water quality data such as water transparency and the water spectral data of Shahu Lake. GF-1 image data were preprocessed to assure that the measured data were consistent with the reflectance curve of the remote sensing image data, and then selected an empirical method and semi-empirical/semi-analysis method of water transparency for remote sensing estimation of water transparency and constructed a remote sensing estimation model suitable for studying the water transparency of Shahu Lake. The new model was combined with GF-1 image data to analyze the total temporal and spatial variation characteristics of the water. The results showed that the empirical model based on the measured band 1/B4 of the spectral data was the best model for water transparency remote sensing estimation of Shahu Lake. The model was expression: SD = 0.3336 × (1/B1) + 27.94. The coefficient of determination of the verification model was 0.7454. The estimation of the water transparency model showed that the water in Shahu Lake has the transparency of the central lake and intake was higher and the transparency of the Third Drainage, Bird Island and Old Wharf were lower compared to each region. These findings were consistent with the measured numerical characteristics. The transparency of Shahu Lake is mainly affected by the water quality index, tourism activities, ecological hydration and distribution of reeds.

Visualization of the Orientation of Amphipathic Peptides at the Air-Water Interface by X-Ray Reflectometry.

X-ray reflectivity measurements were performed for the leucine and lysine-based LKα14 peptide designed to adopt an α-helical conformation at the air-water interface. The electron density profiles along the surface normal were calculated from the atomic coordinates predicted by an electronic structure program to fit the X-ray reflectivity curve. At the concentration of the monolayer formation, the long axis of the α-helix adsorbed parallel to the water surface, and the central part was revealed to be submerged in water. On the other hand, at 100 times higher than the surface area density of the monolayer formation, the double layer is formed in which the long axis of the α-helix is parallel to the water surface and only the peptide in the second layer is submerged in water.

Calibration of solids concentration optical fibre probes with solids‐polymer blocks

AbstractOwing to the determinant effects of the local distribution of solids concentration on transport phenomena, particularly in gas‐solids flows in such processing units as gas‐solid fluidized beds and pneumatic conveying lines, its accurate measurement has received considerable attention. Despite the widespread applications of optical fibre probes for the measurement of local solids concentration, these instruments may create measurement uncertainties due to their structural designs and challenges in their accurate calibrations. Several calibration methods have been proposed in the literature, while they need to be further improved. In the present study, we calibrated in‐house, fabricated, solids concentration mixed parallel optical fibre probes by two sets of solids‐polymer blocks covering solids volume fractions in the range of 0‐0.30. The uniform blocks were produced by a twin‐screw extruder and an injection moulding machine. FCC particles, 86 μm in diameter, formed the dispersed solids in the blocks, while poly styrene and poly methyl methacrylate were separately acting as the transparent medium. They helped us investigate the effects of the refractive index of the medium and the probe tip design on the calibration curve. The blind distance (zone) in front of the adopted probes was determined, at about 0.70 mm, upon measuring their reflective curves. Two glass windows with 1.00 and 1.60 mm thicknesses were separately installed at the tip of a probe to study their effects on the calibration curve. Experimental results indicated that in the absence of a glass window, the probes' voltage readings varied nonlinearly with solids concentration, the voltage readings were higher for blocks with a higher refractive index of the transparent medium, while the normalized calibration curves were similar for both sets of solids‐polymer blocks. In addition, the extent of the uniform distribution of illuminating and reflecting fibre strands at the tip of a mixed parallel optical fibre probe can change the degree of nonlinearity of its calibration curve. The application of glass windows thicker than the blind distance decreased the degree of nonlinearity of the calibration curve, yet did not completely eliminate it.

Inhibition of Primary Photosynthesis in Desiccating Antarctic Lichens Differing in Their Photobionts, Thallus Morphology, and Spectral Properties.

Five macrolichens of different thallus morphology from Antarctica (King George Island) were used for this ecophysiological study. The effect of thallus desiccation on primary photosynthetic processes was examined. We investigated the lichens’ responses to the relative water content (RWC) in their thalli during the transition from a wet (RWC of 100%) to a dry state (RWC of 0%). The slow Kautsky kinetics of chlorophyll fluorescence (ChlF) that was recorded during controlled dehydration (RWC decreased from 100 to 0%) and supplemented with a quenching analysis revealed a polyphasic species-specific response of variable fluorescence. The changes in ChlF at a steady state (Fs), potential and effective quantum yields of photosystem II (FV/FM, ΦPSII), and nonphotochemical quenching (NPQ) reflected a desiccation-induced inhibition of the photosynthetic processes. The dehydration-dependent fall in FV/FM and ΦPSII was species-specific, starting at an RWC range of 22–32%. The critical RWC for ΦPSII was below 5%. The changes indicated the involvement of protective mechanisms in the chloroplastic apparatus of lichen photobionts at RWCs of below 20%. In both the wet and dry states, the spectral reflectance curves (SRC) (wavelength 400–800 nm) and indices (NDVI, PRI) of the studied lichen species were measured. Black Himantormia lugubris showed no difference in the SRCs between wet and dry state. Other lichens showed a higher reflectance in the dry state compared to the wet state. The lichen morphology and anatomy data, together with the ChlF and spectral reflectance data, are discussed in relation to its potential for ecophysiological studies in Antarctic lichens.

Estimation model and its trade-off strategy of Mangifera persiciforma Colletotrichum gloeosporioides degree based on leaf reflection spectrum.

Colletotrichum gloeosporioides is one of the most common and serious fungal diseases of the tree Mangifera persiciforma. Yet we lack an effective method to evaluate this ecological interaction accurately. Here, we measured the functional traits and leaf reflectance spectrum of the host plants under different disease degrees. The findings provide a fast and efficient method for large-scale and high-precision monitoring of C. gloeosporioides in M. persiciforma stands. Using the collected leaf reflection data, we set up a prediction model of the optimal disease degree. Firstly, we found that leaf functional traits of M. persiciforma generally consisted of low leaf thickness, low relative chlorophyll content, small specific leaf area, high leaf tissue density, high dry matter content, low stomatal density, and large stomatal area. Secondly, leaf reflectivity increases with damage of C. gloeosporioides, which corresponds to five main reflection peaks and five absorption valleys in the spectral reflectance curve of leaves at the same positions (350-1800 nm). Thirdly, with the increase of infection degree, red edge slope and yellow edge slope decrease, while green peak reflectance, red valley reflectance, and blue edge slope all increase. Blue shift was detected in the red edge, green peak, and red valley, while red shift appeared at the blue edge and yellow edge. Finally, the best predictive model was that based on green peak reflectance (y=3.6396-0.0693x, R2=0.5149, RMSE [root-mean-square error] =0.2735), with an R2=0.92 and RMSE=0.0042 between its predicted vs. observed values. Because of its high inversion accuracy, the model can be used to predict the invasion conditions of M. persiciforma by C. gloeosporioides. Our study demonstrated that when plants are infected by C. gloeosporioides, there was a strong trade-off relationship between leaf functional traits. On the global leaf economics spectrum, the leaves tended toward the "slow investment-return" end when infected by C. gloeosporioides.

Spectral Pattern of Paddy as Response to Drought Condition: An Experimental Study

Every single physical object has a different response to the electromagnetic wave emitted to it. The response is in the form of how it absorbs and reflects the energy in every range of wavelength. The absorption and reflection curve is known as a spectral pattern. The spectral pattern of each object can be used to determine the object. In agriculture, the spectral pattern of plants can be used to determine the health condition of the plant. Drought is one factor that can affect the health of the plant. By identifying the spectral pattern of the plants, the effect of drought on paddy can be identified. This experimental study tried to identify the spectral pattern of some varieties of paddy and different growth stages. A spectrophotometer with a wavelength range of 350-1052 nm was used. Four varieties of paddy were planted in a greenhouse and being treated in drought conditions from the stage of vegetative, generative, and reproductive. Based on the result, the spectral response from the generative phase of all varieties gave the most different pattern compared to the control. This result compromising the rapid detection of paddy fields affected by drought using optical remote sensing data. Especially for plants in the stage of generative.

Dyeing Wool Knitted Fabric in Nano-scale Reverse Micelle with Reactive Dyes — A Computer Colour Matching Study

The colour quality assessment of reverse micelle-based (in octane or nonane medium) and conventional water-based dyed wool knitted fabric has been investigated using computer colour matching (CCM) approach. Both water-based and non-aqueous based dyeing methods exhibited no chromatic shift from the reflectance curves and established good linearity in the construction of calibration curves. The linearity of both calibration curves in terms of R2 value played a critical role in CCM. The colour yield obtained from reverse micellar dyed fabric samples was higher than the colour yield values from wool knitted fabrics dyed in water bath under different dye percentages. The CCM predicted concentrations were in good agreement to theoretical concentrations for both dyeing systems. To conclude, the results showed that reverse micellar dyeing in octane and nonane is capable of generating reliable colour recipes. The relative unlevelness indices (RUI) obtained from dyed wool knitted fabrics using reverse micellar approach reveal good to excellent levelness, which fulfills the requirements of the textile processing industry. TEM picture illustrated that reverse micelles are in nano-scale and this could enhance the dyeing effect of wool with reactive dyes.

Cellulose and Vanadium Plasmonic Sensor to Measure Ni2+ Ions

A novel vanadium–cellulose composite thin film-based on angular interrogation surface plasmon resonance (SPR) sensor for ppb-level detection of Ni(II) ion was developed. Experimental results show that the sensor has a linear response to the Ni(II) ion concentrations in the range of 2–50 ppb with a determination coefficient (R2) of 0.9910. This SPR sensor can attain a maximum sensitivity (0.068° ppb−1), binding affinity constant (1.819 × 106 M−1), detection accuracy (0.3034 degree−1), and signal-to-noise-ratio (0.0276) for Ni(II) ion detection. The optical properties of thin-film targeting Ni(II) ions in different concentrations were obtained by fitting the SPR reflectance curves using the WinSpall program. All in all, the proposed Au/MPA/V–CNCs–CTA thin-film-based surface plasmon resonance sensor exhibits better sensing performance than the previous film-based sensor and demonstrates a wide and promising technology candidate for environmental monitoring applications in the future.

Utilization of multispectral landsat-8 remote sensing data for lithological mapping of southwestern Saudi Arabia

The upper plutonic rocks in southwestern Saudi Arabia has been mapped through Landsat 8 Operational Land Imager (OLI) data. The gathered field rock samples were subjected to spectral measurements (in the range of 0.4–2.5 µm) in the laboratory using a GER 3700 spectroradiometer. Integrated remote sensing techniques, including the band ratio, principal component analysis (PCA), and Gram-Schmidt spectral sharpening have been applied through this study. The red–greenblue composites of the pan-sharpened original bands (3, 4, and 7), principal components (PC3, PC1, and PC2), and band ratios 5/6 and 5/7 were found to be the most useful to delineate the study area’s Upper Proterozoic plutonic rocks. The results of image processing methods, spectral reflectance analyses are in good agreement with the field data. The spectral reflectance curves of the collected samples and the corresponding Landsat 8 pixels match well. It is indicated that Landsat-8 image data has great capability to identify lithological units and could be applicable in several areas in arid and semiarid environments.

Evaluation of fullerenes C60/C70 layers in polystyrene thin films by neutron and X-ray reflectometry

Thin films of polystyrene-fullerene C60 and C70 nanocomposites are investigated by X-ray, neutron reflectometry and AFM. These films were prepared by spin coating from toluene solutions with fullerene content of 1, 3, and 5 wt % relative to polystyrene mass. The concomitant to spin-coating formation of aggregates, larger for C70, was observed. Still, a formation of an enriched layer of fullerenes with a thickness up to 5 nm was detected after model fitting of the reflectivity curves.

Comparative study of predicted MAX phase Hf2AlN with recently synthesized Hf2AlC: a first principle calculations

The physical properties including thermodynamic and optical properties, electronic charge density, Fermi surface, Mulliken bond overlap population and Vickers hardness of newly synthesized MAX phase Hf2AlC and predicted Hf2AlN phase have been explored using density functional theory for the first time. We revisit lattice and elastic constants, band structure and density of states to weigh the reliability of our calculations. The mechanical and dynamical stabilities of these compounds have been ensured. The brittle nature of Hf2AlX (X = C and N) compounds is also confirmed by the Pugh (G/B > 0.57) and Poisson ratio (< 0.26). The electronic band structure and density of states show the metallic conductivity with foremost contribution of Hf-5d states at the Fermi level. The mixture of covalent, metallic and ionic bonding is ensured by Mulliken population and charge density mapping. Low Vicker hardness value indicates soft material and easily mechinable nature of the phases. The reflectivity curves show the maximum values of 93% at 10.3 eV and 99% at 13.7 eV for the compounds Hf2AlC and Hf2AlN, respectively, that endorse the capability of reducing solar heating of these compounds. Excellent correlations are also found in all physical properties of these compounds.

Sensitivity enhancement of surface plasmon resonance sensor using Al–Au–BaTiO3–Graphene layers

The performance of prism-based surface plasmon resonance sensor utilizing new sensing configuration composed of thin metallic (Al–Au) film coated with a thin layer of BaTiO3is investigated theoretically based on angular interrogation method. It is observed that optimizing the thickness of bimetallic (Al–Au) and BaTiO3 layers, the sensitivity of the sensor improved greatly and still can maintain its minimum reflectivity and linewidth of the SPR reflectivity curve. We also observed addition of dual layer of graphene on BaTiO3 further enhanced the sensitivity. The sensitivity of the proposed sensor is found to be 227 deg/RIU, and the FWHM of resonance curve is observed to be 4.47 deg for the thickness of 28 nm of Al, 8 nm of Au and 10 nm of BaTiO3added with double layer of graphene.

An optimization-based design of a wideband, polarization-independent reflectarray antenna at terahertz frequencies

A broadband reflectarray antenna is proposed for operating at THz frequencies. An array of single-layer elements is composed of gold patches printed on a grounded cyclic olefin copolymer (COC) substrate. The elements are designed to have a smooth and linear phase reflection curve versus element positions. A random hill-climbing (RHC) optimization algorithm is applied to obtain the broadest bandwidth around the design frequency. The proposed antenna shows 3 dB relative bandwidth of 25% ranging from 0.9 to 1.15 THz, and it has a polarization-independent feature and low loss for better reflectarray performance.

FDTD modeling of sputtered Mo–Al2O3 nanocomposites

Ceramic-metal nanocomposites (NCs) are the one of the most promising materials for selective solar absorbers (SSAs) in renewable energy applications. Design of efficient SSAs demands precise modeling of light propagation in NCs. We report on the synthesis, detailed characterization, and analytical and numerical modeling of Molybdenum (Mo)-alumina (Al2O3) NCs. In this study, Mo–Al2O3 NC films with thicknesses of 45 nm and 60 nm and nominal metal volume fraction (f) of 30%, 40%, and 60% were grown on polished glass substrates, using sequential DC and RF sputtering. TEM analysis of the samples with f = 40% showed that most 2 nm-diameter Mo particles are spherical and isolated. The reflectance (R) and transmittance (T) curves of the NC were measured in the spectral range of 300 nm and 1700 nm. The measured R and T characteristics were compared with the calculated FDTD simulations to analyze the prediction accuracy of the approach.

The Formation and Structure of Thermomigration Silicon Channels Doped with Ga

Vertical through Si(Ga) p channels are created at 1450 K in c-Si(111) plates by thermomigration of local gallium zones. To this end, a technique is proposed and implemented for the formation of local zones consisting in the filling of linear grooves with a of width 60−100 μm and depth of 30−50 μm etched in the silicon plate with a fine-grained Ga powder. It is shown that a high yield of acceptable zones occurs with powder grains with a size of 5 μm and at ∼284 K. The obtained thermomigration Si(Ga) p channels are studied by the X-ray methods of double-crystal diffraction reflection curves and projection topography. The structural perfection of gallium p channels is characterized based on their comparison with features of the structure of thermomigration Si(Al) channels, obtained close to retrograde temperature 1380 K. It is shown that dislocation half-loops pinned at their ends at the boundaries of both thermomigration channels are a typical form of structural defects at their boundaries. The magnitudes of deformation of (2−5) × 10–5 and bending of 15″−30″ of the crystal planes close to the channel–matrix of the plate interface of the samples under study are determined. In the Vegard model, the concentration of aluminum and gallium atoms implanted into a crystal lattice of the silicon channels of the samples was CAl ∼ 1019 cm−3 and CGa ∼ 1.9 × 1019 cm−3, respectively.

Inhibition of photosynthesis in Melia azedarach and Ligustrum lucidum induced by manganese toxicity using OJIP chlorophyll a fluorescence transient

Manganese (Mn) excess is a major abiotic stress for plant growth. In the present study, we investigated the effects of Mn on photosynthesis in Ligustrum lucidum and Melia azedarach leaves using chlorophyll fluorescence transients. Both plant species were exposed to two Mn concentrations (0.5 and 1 mmol) for 10 and 30 d. Results showed that excess Mn significantly inhibited photosynthesis. With the increase of Mn concentration and stress time, the inhibition was more serious. Mn stress impaired PSII at the donor and the acceptor side by damaging the oxygen-evolving complex and limiting electron transport downstream of QA in both trees. A significant decline in 820 nm reflection curve absorption was observed in M. azedarach, suggesting that the oxidization-reduction reactions in PSI were inhibited but this phenomenon was not observed in L. lucidum. Therefore, excess Mn impaired the whole electron transport chain associated with inactive PSII reaction centers in Ligustrum lucidum and inhibited oxidization-reduction reactions in PSI in M. azedarach.

PARTICLES SIZE AND LATTICE STRAIN EFFECT ON THE OPTICAL CONSTANTS OF Fe3O4 NANOPARTICLES

In the case of optical sensors such as the Surface Plasmon Resonance (SPR) sensor, the Fe3O4 nanoparticles play a role to boost the signal however they can increase the detection sensitivity of the biosensor. For this application, the optical properties of Fe3O4 nanoparticles need to be studied. The optical properties are described in terms of their optical constants. Therefore, this work was purposed to study the effect of the particle size and lattice strain on the optical constants of Fe3O4 nanoparticles. Samples were synthesized by using the coprecipitation technique. Two calcination temperatures, i.e., 150oC and 250oC for 4 hours were applied to the samples. Samples were characterized for their diffraction pattern and optical properties by using XRD and Specular UV-Vis Spectroscopy technique, consecutively. The particle size and lattice strain were estimated by using the Williamson-Hall (W-H) method. The effect of the particle size and their optical constants on the reflectance curve in the SPR sensor application was also performed toward a simulation by using Winspall 3.02 software. The results show that calcination temperature causes an increase in particle size and a decrease in lattice strain. The optical constants, such as absorbance (A), absorption coefficient (α), extinction coefficient (k), refractive index (n), dielectric constants (ε), optical conductivity (σ), and the Urbach energy (Eu) significantly depended on particles size and lattice strain. However, the particle size and optical constant were significantly influent the SPR angle in the reflectance curve of Fe3O4