Infrared Reflectance Spectroscopy Research Articles

Metal-insulator transition in (Pr,Y)0.7Ca0.3CoO3 in the far-infrared spectral region

Bulk ceramics and thick nanogranular films of mixed-valence cobaltite ${({\mathrm{Pr}}_{1\ensuremath{-}y}{\mathrm{Y}}_{y})}_{0.7}{\mathrm{Ca}}_{0.3}\mathrm{Co}{\mathrm{O}}_{3}$ were studied using time-domain terahertz transmission spectroscopy and infrared reflection spectroscopy. Thanks to the high probing frequency, the overall increase in the conductivity during the insulator to metal transition was observed both in the ceramics and in the nanogranular films. The terahertz conductivity spectrum shows that the transition is not a simple cross-over between two states. As the charges become delocalized during the insulator to metal transition, a broad resonant mode corresponding to the eigenfrequency of the binding potential appears in the terahertz conductivity spectra in the ceramics, and it further softens as the metallic state prevails. This is interpreted as a consequence of the complexity of charge motion in a temperature-dependent energy landscape, changing dramatically from the tightly bound charges on atomic distance in the insulating phase to almost free charges in the metallic phase. This behavior is not directly observed in the nanogranular films as their nature introduces spectral signatures of an additional localization due to grain boundaries which obscure the pronounced effects observed in the bulk. Nevertheless fine spectral signatures accompanying the phase transition are still resolved. The insulator to metal transition is also accompanied by a weak softening of infrared-active phonon modes, which is related to the expansion of lattice parameters upon phase transition.

Field characterisation of rock art paintings using non-invasive reflectance spectroscopy in the search for organic paint binders at Genealogy and Stickman Rockshelters in the Weld Range (Western Australia)

This paper reports on the search for organic binder materials in rock art paintings at Genealogy and Stickman Rockshelters in Wajarri Yamaji country, Weld Range (Western Australia). Portable visible, near infrared and shortwave infrared (VNIR-SWIR) reflectance spectroscopy requires no physical sampling or surface preparation. Eleven motifs were analysed in-situ. Only one of the motifs had absorption features characteristic of organic molecular bonds and resembled hematite and blood experimental paint reference materials. Constituent hematite and clay pigment minerals defined the spectra of the remaining ten motifs. This pilot study demonstrates that non-invasive VNIR-SWIR spectroscopy is an effective field characterisation tool for assessing painted rock art motifs for constituent organic materials and mineralogy including clay minerals and iron oxides. Without the need to take samples, the technique will be invaluable for rock art conservation, and as a screening tool in the search for organic materials suited for C14 direct dating in mineral pigmented rock art paint.

Conversion of dimethyl ether to liquid hydrocarbons on zeolite catalysts: Influence of a base admixture in the zeolite

This paper presents comparative data on the selectivity and gasoline fraction composition for commercial catalysts based on Zn- and Pd-modified zeolites with the same MFI structural type, but produced by different manufacturers. The data are obtained in the operation of a two-reactor micropilot unit in a flow circulation mode. The relationship and differences between the character and type of Brønsted acid site were investigated using in situ high-temperature diffuse reflectance IR spectroscopy during annealing of the catalysts in dry argon, hydrogen, and dimethyl ether flows. It was found that catalysts contain organic ammonium cations with different structures of organic substituents, which decompose to give a very strong nitrogen-containing acid site. This site can promote the formation of branched paraffins and light aromatics from dimethyl ether. Under the action of these sites, methanol can be rapidly converted to DME, which is more reactive towards the production of gasoline fraction.

Hydrothermal alteration characteristics of the Chating Cu-Au deposit in Xuancheng City, Anhui Province, China: Significance of sericite alteration for Cu-Au exploration

The Chating Cu-Au deposit in Xuancheng City, Anhui Province, is characterized by porphyry-style mineralization with intensive hydrothermal alteration. Short-wave infrared reflectance spectroscopy was used to systematically analyze the alteration of drill cores from two cross sections. Eleven alteration minerals—sericite, smectite, kaolinite, dickite, chlorite, epidote, gypsum, carbonate, iron oxide, saponite, and prehnite—were identified, and the relative abundances of individual minerals at various depths were calculated by depth of absorption peak. In these minerals, iron oxides and gypsum are probably related to supergene process and other alteration minerals are hydrothermal alteration minerals. The mineral assemblages and their spatial distributions indicate that the alteration patterns in this Cu-Au deposit were controlled mainly by water–rock interaction of the magmatic–hydrothermal process, resulting in a typical porphyry-style hydrothermal mineralization system. A saponite–smectite–K-feldspar–anhydrite (gypsum) alteration assemblage is located mainly in the host quartz diorite porphyry, and is minor in the wall rocks of limestone and a post-mineralization diorite porphyry. A sericite–chlorite alteration assemblage was widely developed in the quartz diorite porphyry, and the intensity of alteration decreases gradually outward from the center to the margins of the deposit. A kaolinite–calcite alteration assemblage is mainly located on the top of the quartz diorite porphyry and in the surrounding limestone. The physiochemical conditions of the hydrothermal fluid, such as temperature and pH, control the compositional variations of specific alteration minerals. The most remarkable feature is a subtle change in octahedral Al cation content of sericite, as identified by the change in wavelength of sericite Al-OH absorption peak position. Muscovite is the main component of sericite, with a trace amount of phengite. The Cu-Au grades are negatively correlated with the wavelength of sericite Al-OH absorption peak position, because high ore grades are associated with relatively shorter Al-OH wavelengths, corresponding to a high Al/Si ratio in sericite (i.e. towards muscovite). This correlation suggests that the ore metal tends to be enriched and precipitated in an acidic environment of the alteration system. In addition, a lateral variation across the deposit in Al-OH wavelength indicates that the acidity of the hydrothermal fluids decreases gradually from the center of the deposit outward to the wall rocks, whereas the variation of sericite Al-OH wavelength with depth suggests an increase in fluid pH with decreasing depth. The alteration patterns imply that during mineralization the ore-forming fluids probably migrated from the southwest in the deep part of the porphyry system towards the northeast near the surface. Based on the spectral alteration mapping, it is concluded that there were at least three stages of hydrothermal activity in the Chating mining district: an early potassic–skarn hydrothermal alteration stage, an intermediate propylitic–sericite medium-low temperature alteration stage, and a late kaolinite–dickite epithermal stage. The sericite alteration stage is temporally related to Cu-Au mineralization, leading to the formation of the main orebody at Chating. As the current exploration is still focused in the sericite alteration zone, it is inferred that deep exploration has great potential in the Chating district.

Making EuO multiferroic by epitaxial strain engineering

Multiferroics are materials exhibiting the coexistence of ferroelectricity and ideally ferromagnetism. Unfortunately, most known magnetoelectric multiferroics combine ferroelectricity with antiferromagnetism or with weak ferromagnetism. Here, following previous theoretical predictions, we provide clear experimental indications that ferroelectricity can be induced by epitaxial tensile strain in the ferromagnetic simple binary oxide EuO. We investigate the ferroelectric phase transition using infrared reflectance spectroscopy, finding that the frequency of the soft optical phonon reduces with increasing tensile strain and decreasing temperature. We observe such a soft mode anomaly at 100 K in (EuO)2/(BaO)2 superlattices grown epitaxially on (LaAlO3)0.29-(SrAl1/2Ta1/2O3)0.71 substrates, which is a typical signature for a displacive ferroelectric phase transition. The EuO in this superlattice is nominally subjected to 6.4% biaxial tensile strain, i.e., 50% more than believed needed from previously published calculations. We interpret our results with new first-principles density functional calculations using a hybrid functional, which provides a better quantitative agreement with experiment than the previously used local-density approximation and generalized gradient approximation functionals.

VIRS based detection in combination with machine learning for mapping soil pollution.

Widespread soil contamination threatens living standards and weakens global efforts towards the Sustainable Development Goals (SDGs). Detailed soil mapping is needed to guide effective countermeasures and sustainable remediation operations. Here, we review visible and infrared reflectance spectroscopy (VIRS) based detection methods in combination with machine learning. To date, proximal, airborne and spaceborne carrier devices have been employed for soil contamination detection, allowing large areas to be covered at low cost and with minimal secondary environmental impact. In this way, soil contaminants can be monitored remotely, either directly or through correlation with soil components (e.g. Fe-oxides, soil organic matter, clay minerals). Observed vegetation reflectance spectra has also been proven an effective indicator for mapping soil pollution. Calibration models based on machine learning are used to interpret spectral data and predict soil contamination levels. The algorithms used for this include partial least squares regression, neural networks, and random forest. The processes underlying each of these approaches are outlined in this review. Finally, current challenges and future research directions are explored and discussed.

Desarrollo y evaluación de modelos de predicción de Finura en vellones de vicuña, mediante espectroscopía de reflectancia en el infrarrojo cercano.

El sistema productivo de fibra de vicuña (Vicugna vicugna) requiere de tecnologías que permitan determinar objetivamente la calidad de aquéllas. En este trabajo se desarrollaron y evaluaron modelos de predicción de la Finura Media en vellones de vicuña, mediante espectroscopía de reflectancia en el infrarrojo cercano. El modelo con mayor capacidad predictiva evidenció un coeficiente de determinación R2= 0,72 y Valor Predictivo Residual= 2,10. Esto da la pauta del potencial de la espectroscopía para utilizarse en determinaciones generales del parámetro evaluado.

Chemical pressure induced near-complete suppression of spin-wave excitations in Bi0.9A0.1FeO2.95 (A = Ba, Ca)

We have probed the changes in the phonon and magnon modes of BiFeO3 on substitution of Ba and Ca at the A-site using infrared reflectance spectroscopy. The systematic hardening of the phonon modes in the doped samples is seen to correlate well with the volume reduction of the unit cell observed from the Rietveld measurements. This is attributed to the generation of chemical pressure in these samples on account of substitution of the dopants. In addition, a near-complete suppression accompanied by a complete lifting of the degeneracy of the magnon modes as compared to the pristine BiFeO3 is detected for the Ca-doped samples. These results suggest that aliovalent doping at A-site affects the crystal field of FeO6 octahedra of BiFeO3, which eventually modifies its magnetic nature. These doping-induced modifications are mainly responsible for the improved magnetic and magnetoelectric properties of the Ca-doped BiFeO3 samples.

Reactivity of Platinum Hydrides in the Selective Hydrogenation of Acetic Acid on Pt–ReOx/TiO2 Catalysts

The interaction between hydrogen and subnanometer deposited Pt–ReOx particles active in dehydrogenation of carboxylic acids is investigated via in situ diffuse reflectance IR spectroscopy. Absorption bands of platinum hydrides are detected in the range of 2025–2043 cm−1, and their high reactivity with respect to adsorbed acetic acid is revealed. The absorption band of platinum hydride shifts toward higher frequencies and becomes more intense, due to the effect of adjacent acetates on the electron state of platinum. It is established that in a hydrogen medium the intensity of platinum hydride bands sharply increases after the adsorption of acetic acid and then gradually decreases owing to the reaction of the hydrides with surface acetates.

Features of the Mechanism of the Dimethyl Ether to Light Olefins Conversion over MgZSM-5/Al2O3: Study by Vibrational Spectroscopy Experimental and Theoretical Methods

Features of the mechanism of dimethyl ether (DME) conversion to olefins over ZSM-5 zeolite catalysts were studied using experimental and theoretical methods of vibrational spectroscopy. A catalytic activity comparison of the catalysts Mg-HZSM-5 without a binder and Mg-HZSM-5/Al2O3 containing 1% Mg (by weight) and 33% Al2O3 (by weight) as a binder in the DME conversion was carried out. Using high-temperature diffuse reflectance IR (DRIR) spectroscopy in situ combined with quantum-chemical simulations in the temperature range of 25–450 °C in a stream of dry Ar and DME, the bands corresponding to OH bonds, including BAS and H3O+, were interpreted. Depending on the temperature and the presence of magnesium and a binder in the catalyst composition, the intensity and position of these bands maxima vary greatly. The intermediates of the catalytic DME conversion were discovered and identified. At low temperatures (below 200 °C), in a DME stream, methoxy groups (CH3O-Al-), ketene (CH2 =C=O), and a carbocation (CH3 +) were formed on the surface of the catalysts. As the temperature rises (above 300° C), the bands from ketene completely disappear in the spectra of catalysts, and bands from oxonium cations or ylide particles appear, leading the process of DME conversion by the oxonium-ylide mechanism. In the presence of H3O+, the conversion of DME on the zeolite catalyst surface was more effective; however, selectivity for olefins was lower.

Wood and Pulping Properties Variation of Acacia crassicarpa A.Cunn. ex Benth. and Sampling Strategies for Accurate Phenotyping

Research Highlights: This study provides a comprehensive set of wood and pulping properties of Acacia crassicarpa A.Cunn. ex Benth. to assess variation and efficient sampling strategies for whole-tree level phenotyping. Background and Objectives: A. crassicarpa is an important tree species in Southeast Asia, with limited knowledge about its wood properties. The objective of this study was to characterize important wood properties and pulping performance of improved germplasm of the species. Furthermore, we investigated within-tree patterns of variation and evaluated the efficiency of phenotyping strategies. Materials and Methods: Second-generation progeny trials were studied, where forty 50-month-old trees were selected for destructive sampling and assessed for wood density, kraft pulp yield, α-cellulose, carbohydrate composition, and lignin content and composition (S/G ratio). We estimated the phenotypic correlations among traits determined within-tree longitudinal variation and its importance for whole-tree level phenotyping. Results: The mean whole-tree disc basic density was 481 kg/m3, and the screened kraft pulp yield was 53.8%. The reliabilities of each sampling position to predict whole-tree properties varied with different traits. For basic density, pulp yield, and glucose content, the ground-level sampling could reliably predict the whole-tree property. With near infrared reflectance spectroscopy predictions as an indirect measurement method for disc basic density, we verified reduced reliability values for breast height sampling but sufficiently correlated to allow accurate ranking and efficient selection of genotypes in a breeding program context. Conclusions: We demonstrated the quality of A. crassicarpa as a wood source for the pulping industry. The wood and pulping traits have high levels of phenotypic variation, and standing tree sampling strategies can be performed for both ranking and high-accuracy phenotyping purposes.

Influence of forage particle size and residual moisture on near infrared reflectance spectroscopy (NIRS) calibration accuracy for macro-mineral determination

Near infrared reflectance spectroscopy (NIRS) is routinely used for the determination of nutrient components of forages. However, little is known about the impact of sample preparation on the accuracy of the calibration to predict minerals. Three types of forages, hay (n = 117), grass (n = 109) and haylage (n = 119) were used to determine the impact of different sample preparation procedures: particle size (1.0 mm and 0.5 mm) and presence or absence of residual moisture (dried and re-dried) on resultant NIRS prediction statistics. All forages were scanned using a total of four combinations of sample pre-treatments (1 mm dried, 1 mm re-dried, 0.5 mm dried and 0.5 mm re-dried). Each sample preparation combination was subjected to spectra pre-processing methods such as standard normal variate (SNV), detrending (DT), combination of SNV and DT (SNV&DT) and None (log1/R) together with mathematical treatments (1,4,4,1; 2,4,4,1; 2,6,4,1; 3,5,5,1 and 2,4,4,2). Reduction of particle size from 1 mm to 0.5 mm slightly improved calibration statistics for the prediction of macro-minerals in hay and haylage samples. However, for the grass samples, improved calibration statistics was observed at a particle size of 1 mm for most of the minerals studied. Furthermore, the removal of residual moisture through additional oven drying improved calibration statistics for all minerals examined in the hay, haylage and grass samples. These results highlight the importance of the reduction in particle sizes for the improvement of calibration statistics for the determination of macro-minerals. In addition, re-drying of samples will improve calibration statistics for macro-minerals at particle sizes of 1 mm and/or 0.5 mm.

Evolution of novel rGO/ZrHCF composite and utility in electrocatalysis towards nanomolar detection of sodium nitrite and ferulic acid

Novel composite of reduced graphene oxide/zirconium hexacyanoferrate (rGO/ZrHCF) was fabricated via electrochemical deposition and used as a sensor for detecting sodium nitrite and ferulic acid. The sensor was thoroughly characterized using scanning electron microscope, DRS-UV, attenuated total reflection IR spectroscopy as well as atomic force microscopy. The rGO/ZrHCF exhibited cube-like morphology of ZrHCF on multilayered rGO sheets. Electrochemical characterization was carried out using cyclic voltammetry and square wave voltammetry for the detection of ferulic acid and sodium nitrite. Ferulic acid and sodium nitrite are used as food additives and the overdose of either of them can result in various physiological ailments and necessitates their detection. The proposed sensor could detect both sodium nitrite and ferulic acid at nanomolar levels exhibiting linearity in the range of 1.14 to 13.77 nM and 3.23 to 41.98 nM, respectively. The corresponding limit of detection was 0.38 nM and 1.39 nM. The rGO/ZrHCF-modified electrode was checked for real sample analysis by carrying out determination of sodium nitrite and ferulic acid in water and milk samples and the recovery percentages were found to be in between 96.15 and 99.80. The sensor exhibited long-term stability and reproducibility.

Assessing the nitrogen status of almond trees by visible-to-shortwave infrared reflectance spectroscopy of carbohydrates

Precise nitrogen (N) fertilization requires new indices of plants’ nutritional status. Non-structural carbohydrates (NSC) are the energetic currency of plants and can, thus, serve as a physiological indicator for their condition. Nevertheless, only a few records exist about NSC composition and allocation in crops, and their relationship with N uptake and the current methods to detect NSC compositions in plants are cumbersome and expensive, which limits their use. The current work aimed to associate the nutritional status of almond trees with the carbohydrate compositions in their roots, branches, and leaves by a high-throughput technique. We found that low N availability forces trees to allocate carbohydrates to their roots. High N availability, on the other hand, promoted above-ground vegetative growth, and minimized carbohydrate storage in the leaves. These observations implied that carbohydrate distribution could, indeed, serve as an indication of the nutritional status of the trees. To measure NSC content efficiently, we attempted to quantify soluble carbohydrates and starch in dried and powdered tissues by visible-to-shortwave infrared (VIS-NIR-SWIR; 350–2500 nm) reflectance spectroscopy, which is an inexpensive, safe, and non-destructive technique. We applied several multivariate statistical models based on the spectral datasets, including partial least squares-regression (PLS-R) and discriminant analysis (PLS-DA) as supervised registration and classification models. PLS-DA results of the N gradient in the roots and leaves showed an overall accuracy of 94% and 98%, respectively. PLS-R model performances of soluble carbohydrates and starch improved, in terms of the coefficient of determination (R2), if the leaf and root samples were integrated. Moreover, we found that the SWIR spectral region (1100–2500 nm) had unique reflectance features that revealed the carbohydrate composition and starch concentrations in the different plant tissues. The analyses also clustered the reflectance by tree part (root, branch, or leaf tissues) and N availability, forming a holistic model that can identify the nutritional status of trees. Conclusively, it is suggested that reflectance spectroscopy at the SWIR spectral region could guide precise fertilization by high-throughput identification of plants’ seasonal metabolism.

Pressure-induced structural transition and metallization in MnSe2

The high-pressure behavior of manganese diselenide MnSe2 was investigated by synchrotron angle-dispersive X-ray diffraction (ADXRD) and infrared reflection spectroscopy equipped with a diamond-anvil cell. It was found that MnSe2 with a pyrite-type structure undergoes a transformation into a disordered intermediate phase at ~ 12.5 GPa, with a ground state composed of an arsenopyrite-type structure, as confirmed by laser-heating treatment. The pyrite to arsenopyrite phase transition was found to be coupled to a large collapse in the unit-cell volume (∆V ~ 19%) and an electronic transition from a high-spin to low-spin state for manganese cations (Mn2+). With a fixed value for the pressure derivation of the bulk modulus K' = 4, fitting of the pressure–volume data to a second-order Birch–Murnaghan equation of state yielded isothermal bulk modulus values of K0 = 56.1(9) GPa and K0 = 93.1(4) GPa for the pyrite-type and arsenopyrite-type phases, respectively. The measured infrared reflectivity (Rsd) for MnSe2 showed a drastic increase at pressures between 13 and 20 GPa, but became insensitive to pressure under further compression, implying a pressure-induced transition from an insulator to metallic state.

Effect of Sample Preparation Methods on the Prediction Performances of Near Infrared Reflectance Spectroscopy for Quality Traits of Fresh Yam (Dioscorea spp.)

High throughput techniques for phenotyping quality traits in root and tuber crops are useful in breeding programs where thousands of genotypes are screened at the early stages. This study assessed the effects of sample preparation on the prediction accuracies of dry matter, protein, and starch content in fresh yam using Near-Infrared Reflectance Spectroscopy (NIRS). Fresh tubers of Dioscorearotundata (D. rotundata) and Dioscoreaalata (D. alata) were prepared using different sampling techniques—blending, chopping, and grating. Spectra of each sample and reference data were used to develop calibration models using Modified Partial Least Square (MPLS). The performance of the model developed from the blended yam samples was tested using a new set of yam samples (N = 50) by comparing their wet laboratory results with the predicted values from NIRS. Blended samples had the highest coefficient of prediction (R2pre) for dry matter (0.95) and starch (0.83), though very low for protein (0.26), while grated samples had the lowest R2pre of 0.87 for dry matter and 0.50 for starch. Results showed that blended samples gave a better prediction compared with other methods. The feasibility of NIRS for the prediction of dry matter and starch content in fresh yam was highlighted.

Determination of crude protein and metabolized energy with near infrared reflectance spectroscopy (NIRS) in ruminant mixed feeds

This study aims to determine the crude protein and metabolizable energy values in ruminant mixed feeds based on the measurements obtained from Near Infrared Reflectance Spectroscopy (NIRS) device. The mixed feeds used in the study were produced in Balıkesir. Reference analyses were determined by making chemical analyses of mixed feed samples used in the study. Metabolic energy value of mixed feed samples was calculated by using the determined nutrient values in equations. Portable NIRS device was used in the study. The relationship between estimates obtained from NIRS device and reference values was statistically evaluated. In regression analysis, R2 value was found as 0.0064 for crude protein while it was 0.9397 for metabolizable energy. It has been demonstrated that the NIRS method is a fast, reliable and good estimation method for quantitatively determining the metabolic energy value in ruminant mixed feeds.

Near Infrared Reflectance Spectroscopy and Multivariate Analyses for Fast and Non-Destructive Prediction of Corn Seed Germination

The application of near-infrared reflectance spectroscopy (NIRS) and multivariate analysis for determining the seed germination rate of corn genotypes was assessed. Seed samples about 90 gr belong to commercial and local corn varieties at various ages were scanned with FT-NIRS on the reflectance mode from 1000 to 2500 nm wavelength. Filter paper technique showed the seed germination rates varied between 18-100% depending on the genotypes after 7 days at ±25°C. Partial least squares regression (PLSR) was applied to the reference values corresponding to the spectra. The best statistical results obtained from the pre-treatment combinations of Smooth Savitzky-Golay 9 Points (sg9), MSC full and normalization to unit length (nle). The regression coefficient of calibration (R2C) and prediction (R2P) of the created NIRS calibration via chemometric software NIRCal are realized 0.97 and 0.98 respectively for the property of corn germination rate. The standard error of both calibration (SEC) and prediction (SEP) were almost overlapping (4.17%, 4.61% respectively). The prediction accuracy of the final NIRS model was quite reasonable with the acceptable root mean standard error of prediction (RMSEP) as 8.88%. According to the residual predictive deviation (RPD) index (4.18), the accuracy of the NIRS model regarded as in the best category. Therefore, the NIRS model developed here is sufficient to predict the corn seed germination rate very fast and non-destructively without using any regents.

Near Infrared Reflectance Spectroscopy Coupled to Chemometrics as a Cost-Effective, Rapid, and Non-Destructive Tool for Fish Fraud Control: Monitoring Source, Condition, and Nutritional Value of Five Common Whitefish Species.

Fish fraud is a problematic issue for the industry. For it to be properly addressed will require the use of accurate, rapid, and cost-effective tools. In this work, near infrared reflectance spectroscopy (NIRS) was used to predict nutritional values (protein, lipids, and moisture) as well as to discriminate between sources (farmed vs. wild fish) and conditions (fresh or defrosted fish). Samples of five whitefish species-Alaskan pollock (Gadus chalcogrammu), Atlantic cod (G. morhua), European plaice (Pleuronectes platessa), common sole (Solea solea), and turbot (Psetta maxima)-including farmed, wild, fresh, and frozen ones, were scanned by a low-cost handheld near infrared reflectance spectrometer with a spectral range between 900 and 1700 nm. Several machine learning algorithms were explored for both regression and classification tasks, achieving precisions and coefficients of determination higher than 88% and 0.78, respectively. Principal component analysis (PCA) was used to cluster samples according to classes where good linear discriminations were denoted. Loadings from PCA revealed bands at 1150, 1200, and 1400 nm as the most discriminative spectral regions regarding classification of both source and condition, suggesting the absorbance of OH, CH, CH2, and CH3 groups as the most important ones. This study shows the use of NIRS and both linear and non-linear learners as a suitable strategy to address fish fraud and fish QC.

Optical, structural and electrical characterization of pure ZnO films grown on p-type Si substrates by radiofrequency magnetron sputtering in different atmospheres

ZnO films were grown on p-type Si substrates by radio-frequency magnetron sputtering of ZnO target in pure argon or mixed argon-oxygen plasma and were investigated using atomic force microscopy, spectroscopic ellipsometry, Fourier-transformed infrared spectroscopy and electrical methods. It was observed that the films grown in argon plasma had large surface roughness which increases with the rise of deposition time. The lateral size of ZnO columns showed similar dependence on deposition parameters as the roughness. Contrary to this, the films produced in argon-oxygen plasma were found to be smoother and denser having thinner ZnO columns. These films also demonstrated an abrupt absorption band-gap edge that is the evidence of better crystalline quality of these films (the lower number of native point and elongated defects). Plasmon-phonon interaction in ZnO films as well as the effect of the plasmon system of Si substrate on this interaction was considered. The theoretical approach used for the fitting of specular infrared reflection spectra allowed determining concentration and mobility of free carriers as well as conductivity of ZnO films. It was found that the films grown in pure argon plasma demonstrated a higher concentration and a smaller mobility of free carriers in the comparison with the corresponding parameters of the films grown in argon-oxygen mixed plasma. The direct resistivity measurements show the essentially higher values compared with the values estimated from IR reflection spectra. The possible reasons of this difference are discussed. The utility of infrared reflection spectroscopy for the non-destructive analysis of electro-physical properties of polycrystalline films was shown.