Mid-infrared Reflectance Research Articles

Mid-infrared reflectance spectroscopy of carbonaceous chondrites and Calcium–Aluminum-rich inclusions

We obtained mid-infrared reflectance spectra of powdered size fractions (0–25 ​μm, 25–63 ​μm, 63–125 ​μm and 125–250 ​μm) of 5 carbonaceous chondrites HaH 280 (CK4), Allende (CV3), NWA 10574 (CM2) and Murchison (CM2), and C2 (ungrouped) Tagish Lake. In addition, in-situ micro-FTIR reflectance spectra of CAIs in Allende, Ornans and Vigarano have been made.These spectra are part of a database for the comparison with remote sensing data of asteroids and planetary bodies, but also for laboratory studies of meteorites.Carbonaceous chondrites HaH 280 (CK4), Allende (CV3) and NWA 10574 (CM2) show mid-IR spectra with Reststrahlen bands (RB) dominated by forsterite and pyroxene features. The transparency features (TF) are at 12.1 ​μm–12.9 ​μm and the Christiansen features (CF) at 8.5 ​μm–9.3 ​μm.Murchison (CM2) and ungrouped Tagish Lake (C2) show mainly phyllosilicate features in their spectra. The CF is between 8.6 ​μm and 9.0 ​μm.Micro-FTIR spectra of CAIs from Allende, Vigarano, and Ornans have spinel features between 14.1 ​μm and 14.3 ​μm. In addition, melilite was identified in the Vigarano and Ornans samples with characteristic features at 11.7 ​μm and 12.4 ​μm.Nepheline and sodalite features have been identified around 14 ​μm in the Allende CAI as alteration phases resulting from thermal metamorphism.A band shift in spinel with increasing Fe content from thermal metamorphism could be spectral indicator for parent body metamorphism.A comparison with other bulk samples from the same meteorites/type shows high similarity.Comparison of the finest size fractions modelled in emissivity with remote sensing data of asteroids shows some similarity between a linear mixture of Allende and Murchison and the spectra of asteroid 253 Mathilde. However, the main 10 ​μm plateau is clearly shifted by 0.5 ​μm between asteroid and meteorite spectra. Also, the general band shapes are different. Differences between asteroidal environment (e.g. fairy castle structure) and laboratory make direct comparisons difficult.

Temperature dependent mid-infrared (5–25 μm) reflectance spectroscopy of carbonaceous meteorites and minerals: Implication for remote sensing in Solar System exploration

Interpretation of spectroscopic data from remote sensing strongly depends on the spectroscopic properties, particle size and temperature of materials present on the observed surface. Spectral indices of silicates, carbonates, sulfates, oxides and chemicals available on public database are commonly obtained at room temperature and pressure. Hitherto, few studies were performed by analyzing the effects of space environment such as low pressure and temperature on spectroscopic features of minerals, mostly focused on near infrared spectral region. In particular, whether temperature can affect spectral properties of minerals such as the peak emissivity position, band area and shape, was advanced decades ago, but a systematic laboratory study on such effects is still missing. This is especially lacking in the mid-infrared region, where laboratory data are almost completely absent. Thus, it is pivotal to acquire spectra in vacuum both at various temperatures and with variable particle sizes, for better simulating space environmental conditions.Our experimental apparatus at INAF-Astrophysical Observatory of Arcetri allows reflectance measurements in an extended spectral range from VIS to far IR and at temperatures ranging from 64 K to 500 K. We present here a detailed analysis on temperature-dependent variation on mineral and carbonaceous chondrite samples in the spectral range 1500–400 cm−1 (6.6–25 μm in wavelength). Mineral phases and meteorites analyzed are: pyroxene, olivine, serpentine, Tagish Lake (CI2-ungruped), Aguas Zarcas (CM2) and Orgueil (CI1). Samples are prepared with particle sizes <20 μm, <200 μm, and 200–500 μm. Our results show that temperature induces spectral features modifications such as peak position shifts, band area and peak intensity changes. Such modifications are reversible with temperature and the trend of variation is related to the sample composition and hydration level. Moreover, magnitude of temperature-dependent spectroscopic changes is strongly linked with grain size and composition, hence making this type of analysis pivotal for a correct interpretation of data collected by space telescopes and orbital spacecrafts.

Factors affecting in situ analysis of total petroleum hydrocarbons in contaminated soils by using a mid-infrared diffuse reflectance spectroscopy

The hand-held mid-infrared diffuse reflectance infrared Fourier transform (MIR-DRIFT) spectrometer was used to assess the applicability of on-site and real time monitoring of total petroleum hydrocarbons (TPH) in contaminated soils during site characterization and remediation. Field measurement devices (MIR-DRIFT and turbidimetric screening test kits) were used to analyze reference soils with concentration ranging from 713 to 54790 mg/kg and compared with the results by a gas chromatography/mass spectrometry method (GC/MS). In situ field measurement of 147 petroleum-contaminated soil samples from 11 contaminated sites was correlated with laboratory-determined soil TPH levels by GC/MS. The concentrations of TPH by MIR-DRIFT were significantly correlated to the concentrations of TPH by GC/MS. Detection of TPH by the MIR spectrometer was not affected by the weathering effects of diesel-contaminated soils. Soils contaminated by mixed fuels with high content of gasoline constituents may cause the potential interference in MIR measurement. In field practice, interference may be attributed to soil moisture, soil organic matter, and soil texture. Soil moisture below 5% is required to reduce variation of infrared beam reflected from high level of surface liquid. When measuring the contaminated soil with a high organic matter content, the results may be overestimated due to the possible effects of surface reflection and interference. Clay and partial silty clay soils were not suitable for MIR spectrometer detection due to a potential shielding effect to reduce the infrared radiation absorbed by TPH. Future research is warranted to reduce the variation caused by soil texture and heterogeneity in TPH prediction.

Prediction of soil organic and inorganic carbon concentrations in Tunisian samples by mid-infrared reflectance spectroscopy using a French national library

Mid-infrared reflectance spectroscopy (MIRS, 4000–400 cm−1) is being considered to provide accurate estimations of soil properties, including soil organic carbon (SOC) and soil inorganic carbon (SIC) contents. This approach has mainly been demonstrated by using datasets originating from the same area A, with similar geopedological conditions, to build, validate and test prediction models. The objective of this study was to analyse how MIRS performs when applied to predict SOC and SIC contents, from a calibration database collected over a region A, to predict over a region B, where A and B have no common area and different soil and climate conditions. This study used a French MIRS soil dataset including 2178 topsoil samples to calibrate SIC and SOC prediction models with partial least squares regression (PLSR), and a Tunisian MIRS topsoil dataset including 96 soil samples to test them. Our results showed that when using the French MIRS soil database, i) the SOC and SIC of French validation samples were successfully predicted using global models (R2val = 0.88 and 0.98, respectively), ii) the SIC of Tunisian samples was also predicted successfully both using a global model and using a selection of spectral neighbours from the French calibration database (R2test of 0.96 for both), iii) the SOC of Tunisian samples was predicted moderately well by global model (R2test of 0.64) and a transformation by natural logarithm of the calibration SOC values significantly improved the SOC prediction of Tunisian samples (R2test of 0.97), and iv) a transformation by natural logarithm of SOC values provided more benefit than a selection of spectral neighbours from the French calibration database for predicting Tunisian SOC values. Therefore, in the future, MIRS might replace conventional physico-chemical analysis techniques, or at least be considered as an alternative technique, especially when optimally exhaustive calibration databases will become available.

Explaining Soil Fertility Heterogeneity in Smallholder Farms of Southern Ethiopia

Soil is spatially heterogeneous and needs site-specific management. However, soil nutrient information at larger scale in most cases is lacking. Consequently, fertilizer advisory services become dependent upon blanket recommendation approach. Subsequently, it affects yield and profitability. This study is aimed at explaining soil fertility heterogeneity in Wolaita zone, Southern Ethiopia. About 789 soil samples were collected to evaluate soil physical (color, particle size, and bulk density) and chemical properties (pH, OC, N, P, K, Ca, Mg, B, Cu, Fe, Mn, Zn, PBS, and CEC). The laser diffraction method for soil particles and mid-infrared diffused reflectance (MIR) spectral analysis for OC, TN, and CEC determination were employed. Mehlich-III extraction and inductively coupled plasma (ICP) spectrometer measurement were used for the remaining elements. The result based on principal component analysis showed that 52% of the total variations were explained by exchangeable bases, CEC, pH, available P, Cu, B, and particle sizes. Clay texture and acidic soil reaction are dominant. Soil parameters with the following ranges were found at low status: soil OC (0.2–6.9%), total N (0.01–0.7%), available P (0.1–238 mg/kg), S (4–30 mg/kg), B (0.01–6.9 mg/kg), and Cu (0.01–5.0 mg/kg). Besides, low levels of exchangeable Ca, Mg, and K (Mg-induced K deficiency) on 22, 34, and 54% soil samples, respectively, were recorded. The soil contained sufficient Fe, Zn, and Mn. In conclusion, the study aids in developing practical decision for optimum soil management interventions and overcomes lower productivity occurring due to fertilizer use that is not tailored to the local conditions. Overall, continuous cropping, low return of crop residues, and low and/or no fertilizer application might have caused the low status of N, P, K, S, B, and Cu. Therefore, application of inorganic fertilizers specific to the site, lime in acidic soils, and organic fertilizers are recommended to restore the soil fertility and improve crop productivity.

Mid-Infrared Reflectance Spectroscopy of Oil Sands Minerals Based on Tunable Quantum Cascade Lasers.

Minerals play an important role in the oil sands extraction efficiency. It is thus important to assess the major mineral abundance in oil sands ores. This paper presents the application of tunable quantum cascade lasers for mid-infrared reflectance spectroscopy on oil sands minerals. The investigations and results show a new tool to determine oil sands mineral type and to determine potentially quartz and clay contents.

Hyperspectral Estimation of Soil Organic Matter Content using Different Spectral Preprocessing Techniques and PLSR Method

Soil organic matter (SOM) is the main source of soil nutrients, which are essential for the growth and development of agricultural crops. Hyperspectral remote sensing is one of the most efficient ways of estimating the SOM content. Visible, near infrared, and mid-infrared reflectance spectroscopy, combined with the partial least squares regression (PLSR) method is considered to be an effective way of determining soil properties. In this study, we used 54 different spectral pretreatments to preprocess soil spectral data. These spectral pretreatments were composed of three denoising methods, six data transformations, and three dimensionality reduction methods. The three denoising methods included no denoising (ND), Savitzky–Golay denoising (SGD), and wavelet packet denoising (WPD). The six data transformations included original spectral data, R; reciprocal, 1/R; logarithmic, log(R); reciprocal logarithmic, log(1/R); first derivative, R’; and first derivative of reciprocal, (1/R)’. The three dimensionality reduction methods included no dimensionality reduction (NDR), sensitive waveband dimensionality reduction (SWDR), and principal component analysis (PCA) dimensionality reduction (PCADR). The processed spectra were then employed to construct PLSR models for predicting the SOM content. The main results were as follows—(1) the wavelet packet denoising (WPD)-R’ and WPD-(1/R)’ data showed stronger correlations with the SOM content. Furthermore, these methods could effectively limit the correlation between the adjacent bands and, thus, prevent “overfitting”. (2) Of the 54 pretreatments investigated, WPD-(1/R)’-PCADR yielded the model with the highest accuracy and stability. (3) For the same denoising method and spectral transformation data, the accuracy of the SOM content estimation model based on SWDR was higher than that of the model based on NDR. Furthermore, the accuracy in the case of PCADR was higher than that for SWDR. (4) Dimensionality reduction was effective in preventing data overfitting. (5) The quality of the spectral data could be improved and the accuracy of the SOM content estimation model could be enhanced effectively, by using some appropriate preprocessing methods (one combining WPD and PCADR in this study).

Improvement in spectral library-based quantification of soil properties using representative spiking and local calibration – The case of soil inorganic carbon prediction by mid-infrared spectroscopy

Mid-infrared reflectance spectroscopy (MIRS) is time- and cost-effective. It was used for quantifying soil inorganic carbon (SIC) concentration in France based on a national library, and performances were evaluated on an independent regional set. Our objective was to improve the accuracy of MIRS predictions based on common multivariate regression, through spiking (enrichment of the national library with some representative target samples) with possible extra-weighting (replication of spiking samples) and local calibration (only using calibration samples that are spectral neighbours of each target samples), which have not been fully explored yet, in combination especially.Global (i.e. common) calibration yielded accurate prediction (standard error of prediction, SEP, was ≈5 g kg−1), which could be improved when the library was completed with spiking samples (optimally 10samples extra-weighted 40times; SEP = 3.3 g kg−1). Using spiking samples only (without the library) yielded slightly less accurate results (SEP = 3.6 g kg−1). Prediction was more accurate using local calibration without spiking, but on a validation set that was reduced because some validation samples lacked calibration neighbours (SEP = 2.5–2.7 g kg−1). Local calibration with spiking (optimally 10samples without extra-weight) yielded somewhat less accurate prediction but for the full validation set when few calibration neighbours were required (SEP = 2.7 g kg−1), or higher accuracy on the reduced validation set when many neighbours were required (SEP = 2.3 g kg−1).These accurate predictions demonstrated the usefulness of representative spiking and local calibration for rendering large soil spectral libraries fully operational, while extra-weighting had no additional benefit. Along with more exhaustive spectral libraries, this paves the way for extensive use of MIRS for SIC determination.

Comparison of structure and composition of a fossil Champsosaurus vertebra with modern Crocodylidae vertebrae: A multi-instrumental approach

Information on the adaptation of bone structures during evolution is rare since histological data are limited. Micro- and nano-computed tomography of a fossilized vertebra from Champsosaurus sp., which has an estimated age of 70–73 million years, revealed lower porosity and higher bone density compared to modern Crocodylidae vertebrae. Mid-infrared reflectance and energy dispersive X-ray mapping excluded a petrification process, and demonstrated a typical carbonate apatite distribution, confirming histology in light- and electron microscopy of the preserved vertebra. As a consequence of this evolutionary process, the two vertebrae of modern Crocodylidae show reduced overall stiffness in the finite element analysis simulation compared to the fossilized Champsosaurus sp. vertebra, with predominant stiffness along the longitudinal z-axes.

Low-Resolution Mid-Infrared Reflection Analysis for Discernment of Contaminants in Seed Cotton

Contaminants mixed with cotton during harvesting and processing dramatically decreases its quality and economic value. A low resolution mid-infrared reflection instrument using four wavelengths (3100, 2900, 2300, and 1500 cm^-1) was designed and constructed to distinguish cotton samples from 16 common contaminants (e.g. plastic and grease). These wavelengths were identified from associated high-resolution FT-IR spectra using multivariable analysis (i.e. Principal Component Analysis, Cluster Analysis, and Multiple Curve Regression).

Low-Resolution Mid-Infrared Reflection Analysis for Discernment of Contaminants in Seed Cotton

Contaminants mixed with cotton during harvesting and processing dramatically decreases its quality and economic value. A low resolution mid-infrared reflection instrument using four wavelengths (3100, 2900, 2300, and 1500 cm^-1) was designed and constructed to distinguish cotton samples from 16 common contaminants (e.g. plastic and grease). These wavelengths were identified from associated high-resolution FT-IR spectra using multivariable analysis (i.e. Principal Component Analysis, Cluster Analysis, and Multiple Curve Regression).

Linking mineralogy and spectroscopy of highly aqueously alteredCMandCIcarbonaceous chondrites in preparation for primitive asteroid sample return

AbstractThe highly hydrated, petrologic type 1CMandCIcarbonaceous chondrites likely derived from primitive, water‐rich asteroids, two of which are the targets forJAXA's Hayabusa2 andNASA'sOSIRIS‐REx missions. We have collected visible and near‐infrared (VNIR) and mid infrared (MIR) reflectance spectra from well‐characterizedCM1/2,CM1, andCI1 chondrites and identified trends related to their mineralogy and degree of secondary processing. The spectral slope between 0.65 and 1.05 μm decreases with increasing total phyllosilicate abundance and increasing magnetite abundance, both of which are associated with more extensive aqueous alteration. Furthermore, features at ~3 μm shift from centers near 2.80 μm in the intermediately alteredCM1/2 chondrites to near 2.73 μm in the highly alteredCM1 chondrites. The Christiansen features (CF) and the transparency features shift to shorter wavelengths as the phyllosilicate composition of the meteorites becomes more Mg‐rich, which occurs as aqueous alteration proceeds. Spectra also show a feature near 6 μm, which is related to the presence of phyllosilicates, but is not a reliable parameter for estimating the degree of aqueous alteration. The observed trends can be used to estimate the surface mineralogy and the degree of aqueous alteration in remote observations of asteroids. For example, (1) Ceres has a sharp feature near 2.72 μm, which is similar in both position and shape to the same feature in the spectra of the highly alteredCM1MIL05137, suggesting abundant Mg‐rich phyllosilicates on the surface. Notably, bothOSIRIS‐REx and Hayabusa2 have onboard instruments which cover theVNIRandMIRwavelength ranges, so the results presented here will help in corroborating initial results from Bennu and Ryugu.

Mid-infrared reflectance and transmittance characterization of phosphorus and boron diffused silicon solar wafers

Characterization of doped silicon layers using infrared spectroscopy is a fast and non-destructive method, but data interpretation requires proper simulation and modelling of the free carrier absorption (FCA) in the mid-infrared wavelength range. This work demonstrates an optical model capable of describing the infrared reflectance and transmittance of silicon solar wafers with pyramidal texture and doped layers. The model's ability to accurately describe a broad variety of samples is discussed.

Prediction of phosphorus sorption indices and isotherm parameters in agricultural soils using mid-infrared spectroscopy

Phosphorus is a macro nutrient essential for optimum crop growth and animal health. The soil’s ability to supply P in an available form is influenced by sorption capacity and P binding energies in soil. These properties are usually derived from sorption isotherms that are time consuming and difficult for routine analysis. Mid-infrared diffuse reflectance Fourier transform (MIR DRIFT) spectroscopy is a rapid analysis technique that can potentially replace extractive and digestive techniques traditionally used in soil analysis. This study explored the application of MIR DRIFT in combination with chemometrics, to predict indicators of soil fertility and quality, specifically, P sorption properties. Using an archive of 11 great soil groups a P sorption reference library was generated using five different sorption models; (1) single point sorption index; (2) Langmuir sorption isotherm in the 0–25 mg l−1 P range; (3) Langmuir sorption isotherm in the 0–50 mg l−1 P range; (4) Freundlich sorption isotherm in the 0–25 mg l−1 P range; and (5) Freundlich sorption isotherm in the 0–50 mg l−1 P range. Thirteen reference values were generated for each sample for calibration and validation of P sorption models developed from MIR DRIFT spectra. Validation of the single point P sorption index and Langmuir parameters were satisfactory for rough screening with the exception of the Langmuir binding energy in the 0–50 mg l−1 P range (k50 [8]). The P sorption capacity remaining was the best predicted parameter and the Freundlich sorption isotherm predictions were poor. The results indicated that there is potential for benchtop MIR to describe P sorption properties in agricultural soil to improve management decisions and that soil specific models could be developed to further enhance prediction performance.

Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis

The objective of this study was to compare mid-infrared reflectance spectroscopy (MIRS) analysis of milk and near-infrared reflectance spectroscopy (NIRS) analysis of feces with regard to their ability to predict the dry matter intake (DMI) of lactating grazing dairy cows. A data set comprising 1,074 records of DMI from 457 cows was available for analysis. Linear regression and partial least squares regression were used to develop the equations using the following variables: (1) milk yield (MY), fat percentage, protein percentage, body weight (BW), stage of lactation (SOL), and parity (benchmark equation); (2) MIRS wavelengths; (3) MIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (4) NIRS wavelengths; (5) NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (6) MIRS and NIRS wavelengths; and (7) MIRS wavelengths, NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity. The equations were validated both within herd using animals from similar experiments and across herds using animals from independent experiments. The accuracy of equations was greater for within-herd validation compared with across-herds validation. Across-herds validation was deemed the more suitable method to assess equations for robustness and real-world application. The benchmark equation was more accurate [coefficient of determination (R2) = 0.60; root mean squared error (RMSE) = 1.68 kg] than MIRS alone (R2 = 0.30; RMSE = 2.23 kg) or NIRS alone (R2 = 0.16; RMSE = 2.43 kg). The combination of the benchmark equation with MIRS (R2 = 0.64; RMSE = 1.59 kg) resulted in slightly superior fitting statistics compared with the benchmark equation alone. The combination of the benchmark equation with NIRS (R2 = 0.58; RMSE = 1.71 kg) did not result in a more accurate prediction equation than the benchmark equation. The combination of MIRS and NIRS wavelengths resulted in superior fitting statistics compared with either method alone (R2 = 0.36; RMSE = 2.15 kg). The combination of the benchmark equation and MIRS and NIRS wavelengths resulted in the most accurate equation (R2 = 0.68; RMSE = 1.52 kg). A further analysis demonstrated that Holstein-Friesian cows could predict the DMI of Jersey × Holstein-Friesian crossbred cows using both MIRS and NIRS. Similarly, the Jersey × Holstein-Friesian animals could predict the DMI of Holstein-Friesian cows using both MIRS and NIRS. The equations developed in this study have the capacity to predict DMI of grazing dairy cows. From a practicality perspective, MIRS in combination with variables in the benchmark equation is the most suitable equation because MIRS is currently used on all milk-recorded milk samples from dairy cows.

Near-infrared, mid-infrared or combined diffuse reflectance spectroscopy for assessing soil fertility in rice fields in sub-Saharan Africa

Assessment and monitoring of soil resources is needed for ensuring environmental sustainability of rice production in sub-Saharan Africa (SSA). Diffuse reflectance spectroscopy has the potential to offer means to evaluate and monitor soils at large scale in an efficient, affordable and timely manner. However, its accuracy for predicting chemical and physical properties of soils under rice cultivation is little known. The objectives of this study were to i) determine physical and chemical soil fertility properties which can be accurately analyzed using near infrared (NIR) (700–2500 nm), mid-infrared (MIR) (2500–16,670 nm), or a combination of both (NIR-MIR) (700–16,670 nm) spectral libraries, ii) compare their prediction potential for identifying the most suitable spectral range for simultaneous analysis of soil fertility properties, and iii) assess degrees of variation of 29 soil fertility properties for 2845 soil samples collected from 42 study sites in 20 SSA countries. Diffuse reflectance spectroscopy data were obtained using a Fourier-transform infrared spectrometer (FT-IR) Tensor 27 with a high-throughput screening (HTS-XT) extension unit. About 10% of the whole sample set was chosen for conventional wet chemistry soil analysis, and was used for developing best fitted models with partial least squares regression (PLSR) that can estimate soil fertility properties using infrared (IR) spectra. The prediction performances were evaluated by R2, RMSE and RPIQ. Good prediction models (0.75 < R2 ≤ 0.86 and 1.36 ≤ RPIQ ≤ 3.78) were obtained for 13 soil properties consisting of pH H2O 1:2, exchangeable Ca, exchangeable Mg, sum of exchangeable cations, CEC, ECEC, base saturation percentage, total N, total organic C, clay content, silt content, phosphorus sorption index (PSI) and extractable Al. Satisfactory predictions (0.53 ≤ R2 ≤ 0.75 and 0.59 ≤ RPIQ ≤ 2.56) were obtained for pH H2O 1:2.5, exchangeable K, extractable Mn, Cu, and B, and sand content. NIR, MIR, and combined NIR-MIR diffuse reflectance spectroscopy demonstrate the best prediction potential for 14, 21, and 76% of the studied soil fertility properties, respectively. Except soil pH, most of soil properties are moderate to highly variable (CV = 21–131%). On average, soils in rice fields are characterized by moderate acidity, and low total N, available P and B. In conclusion, the combined NIR-MIR diffuse reflectance spectroscopy can offer an alternative to conventional wet chemistry methods for assessing soil fertility properties in rice fields in SSA, except for those having poor prediction potentials.

In situ fabrication of ZnO nanorods/Ag hybrid film with high mid-infrared reflectance for applications in energy efficient windows

Energy efficient windows are playing an important role in view of the fabrication of Energy-Saving and Eco-Friendly devices which show high energy efficiency among energy conservation buildings. In order to modulate middle-far range infrared radiation, a new strategy based on modulating semiconducting oxides ordered array structure and coating of metal element was proposed for energy efficient windows. In this work, ZnO nanorods/Ag hybrid film with high transmittance in visible region and high reflectance in mid-infrared region was prepared via hydrothermal method and silver-mirror coating above quartz glass that has great potential application in energy efficient windows for infrared radiation cooling. In detail, ZnO nanorods arrays were prepared via in situ fabrication with spin-coating method and hydrothermal process at low temperature. While Ag nanoparticles were coated on as-prepared ZnO nanorods via a silver-mirror method which is also in line with the concept of energy conservation. According to characterization results, ZnO nanorods were grown along the wurtzite c axis perpendicular to the quartz substrate, and Ag nanoparticles were coated on ZnO nanorods with a tight interrelation. ZnO nanorods/Ag hybrid film showed high transmittance of 62% in the visible region and high reflectance above 90% in the mid-infrared region. Therefore, ZnO nanorods/Ag hybrid film obtained in this work indicates excellent optical performance in visible transmission and mid-infrared reflection, and this hybrid film is illustrated to be good candidates for saving energy in the field of energy efficient windows.

Original plant traceability of Dendrobium species using multi-spectroscopy fusion and mathematical models.

Dendrobium is the largest genus of orchids most of which have excellent medicinal properties. Fresh stems of some species have been consumed in daily life by Asians for thousands of years. However, there are differences in flavour and clinical efficacy among different species. Therefore, it is necessary for a detector to establish an effective and rapid method controlling botanical origins of these crude materials. In our study, three spectroscopies including mid-infrared (MIR) (transmission and reflection mode) and near-infrared (NIR) spectra were investigated for authentication of 12 Dendrobium species. Generally, two fusion strategies, reflection MIR and NIR spectra, were combined with three mathematical models (random forest, support vector machine with grid search (SVM-GS) and partial least-squares discrimination analysis (PLS-DA)) for discrimination analysis. In conclusion, a low-level fusion strategy comprising two spectra after pretreated by the second derivative and multiplicative scatter correction was recommended for discrimination analysis because of its excellent performance in three models. Compared with MIR spectra, NIR spectra were more responsible for the discrimination according to a bi-plot analysis of PLS-DA. Moreover, SVM-GS and PLS-DA were suitable for accurate discrimination (100% accuracy rates) of calibration and validation sets. The protocol combined with low-level fusion strategy and chemometrics provides a rapid and effective reference for control of botanical origins in crude Dendrobium materials.

Near-infrared optics of nanoparticles embedded silica thin films.

This work investigates experimentally the near-infrared optical properties of SiO2 thin film embedded with tungsten (W) nanoparticles at varying volume fractions. The samples are prepared by using the technique of magnetron sputtering. The formation and distribution of W nanoparticles are characterized using transmission electron microscopy, and the volume fraction of W nanoparticles is validated by Auger electron spectroscopy. Near- and mid-infrared diffuse reflectance measurements are conducted using Fourier transform infrared spectroscopy. The samples exhibit wavelength selective optical response in the near-infrared region and are suitable for applications involving selective thermal emitters/absorbers. Measured reflectance data is utilized to estimate the effective dielectric function of the nano-composites. Calculated reflectance spectra in different samples are compared to the measured spectra using the experimentally measured dielectric function of these samples in the near-infrared region. Reflectance spectra after thermal annealing at different temperature are compared to show how the thermal treatment affects the optical properties of samples. Optimized structures are proposed for thermal emitters and absorbers with different volume fractions of W nanoparticles.

Prediction of soil carbon levels in calcareous soils of Iran by mid-infrared reflectance spectroscopy

ABSTRACTThe objective of this study was to assess the predictive performance of midDRIFTS-PLSR models in quantifying total carbon (TC), total organic carbon (TOC), total inorganic carbon (TIC), total nitrogen (TN), hot water extractable carbon and nitrogen (CHWE, NHWE), pH, and the clay, silt, and sand content of soils. A total of 68 soil samples were taken across an agroecological region in southwest Iran, and analyzed in the laboratory using mid-DRIFTS-PLSR. midDRIFTS-PLSR calibration models were developed, and external validation was performed for each of the soil properties via an independent algorithm. The calibration and validation models allowed for a sufficient prediction of TC, TIC, and TOC with residual prediction deviations ≥3 and R2 values >0.9. The precise prediction ofcarbon fractions, such as TC, TIC, and TOC, in a rapid and inexpensive manner confirmed that midDRIFTS analysis was a rapid-throughput and cost-effective technique for monitoring soil carbon at the regional scale.