Transflectance Spectra Research Articles

Studying spectroscopic, cyclic voltammetry, and electrical properties of novel 4-amino antipyrine derivative for photonic applications

The present work aims to synthesize a new antipyrine derivative and then study its optical properties in the form of thin films with the aim of using the obtained results in the fabrication and designing of new optoelectronic devices. A N1,N3-bis(1,5-dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)malonamide, dpdp novel organic compound has been successfully synthesized in dimethylformamide (DMF) medium by the chemical reaction between 4-aminoantipyrine and malonyl chloride. The obtained dpdp compound is characterized quantitatively and qualitatively by using micro elemental analysis, FTIR spectroscopy, 1H– & 13C–NMR, and thermogravimetric measurements. Two steps weight loss of 84 % (calcd. mass loss 37.25 %) is recorded in the temperature range of 25 °C to 800 °C. Thin films of the novel organic dpdp were successfully grown by the thermal evaporation technique. FSEM images show the surface topology of the as-deposited thin film which is characterized by high quality, continuous, and crystalline granular surface with an average particle size of 70 nm. The cyclic voltammetric analysis showed that the energy difference between the HOMO and LUMO equals 2.43 eV. The calculated values of the optical band gap transitions deduced from the diffuse reflectance spectra are found to be 2.27 eV, and 3.44 eV for the powder and the as-deposited dpdp thin films, respectively. The photoluminescence spectra analysis showed that the as-deposited film dpdp is characterized by a main green peak centered at 530 nm. The optical transflection spectra showed that the calculated values of the indirect optical band gap transitions are found to be 3.53 eV for the as-deposited thin film which slightly increased to 3.63 eV after annealing at 373 K and 423 K for 4 h. Spectral variations of the refractive index and the specific polarizability showed one peak around 400 nm which fades by annealing treatment at 373 K and 423 K. The dc electrical resistivity activation energy of the free charge carriers was estimated.

Smart Error Sum Based on Hybrid Two-Trace Two-Dimensional (2T2D) Correlation Analysis.

Based on hybrid 2D correlation analysis, we recently derived and introduced a "smart error sum," a sophisticated loss function that can be used for solving nonlinear inverse problems like the determination of optical constants and oscillator parameters from a series of optical spectra in the infrared spectral region. The advantage of the smart error sum compared to the conventional sum of squared errors lies in its ability to marginalize multiplicative systematic errors such as, for example, reflectance values above unity in transflection spectra. This is enabled by a transformation, which allows fits to not exclusively focus on forcing fit spectra to agree with experimental spectra at every wavenumber point by all means, but also to take correlations such as spectral similarities and their changes with certain perturbations into account. In this work, we extend our approach to accommodate the treatment of individual spectra, instead of only series, based on hybrid two-trace two-dimensional (2T2D) correlation analysis. We evaluate and prove the value of our approach by individually analyzing experimental transflection spectra of polymethyl methacrylate (PMMA) layers on gold substrates. The comparison of the results with those obtained by the original smart error sum based on the whole set of spectra as well as those resulting from conventional fitting of series and individual spectra (using the conventional sum of squared errors) confirms the validity and soundness of the 2T2D smart error sum.

Mid-infrared spectroscopy of liquids by using a modified button sample holder

A new approach for mid-infrared spectroscopy measurements of liquids is described. Thin layers of liquid samples are analyzed by using a modified button sample holder that incorporates a reservoir. To obtain spectra, buttons containing liquid samples are placed at the infrared beam focus of a praying mantis diffuse reflection optical system. Infrared radiation absorption path lengths can be adjusted by changing the quantity of liquid added to the reservoir. Thin film transflection spectra are similar to those obtained by transmission measurements. Transflection spectra of thicker layer liquids also resemble transmission measurements, but with increased relative intensities for low absorptivity peaks. Unlike transmission measurements, transflection spectra retain overlapping peak profiles for highly absorbing vibration bands due to multiple path length dynamic range effects. For a fixed effective path length (i.e. constant liquid volume), linear calibration plots of absorbance or integrated absorbance versus concentration are obtained. The button sample holder provides a methodology that is complementary to the transmission cell and attenuated total reflection (ATR) techniques for infrared analyses of neat solids and liquids, and is especially useful for characterizing thick samples and high absorptivity bands.

Determination of α-guaiene and azulene chemical content in patchouli aromatic oil (Pogostemon cablin Benth.) from Indonesia by Near-infrared spectroscopy

This study evaluated the α-guaiene and azulene chemical composition of patchouli aromatic oil from Indonesia by Near-infrared Spectroscopy (NIRS) combined with chemometric treatments. 84 oil samples collected around Indonesia were used, Konawe, Kolaka, Bogor, Garut, Aceh, Jambi, and Masamba. The spectral data were obtained using Fourier Transformed Near-infrared (FT-NIR) spectrometer in 1000 to 2500 nm. Several pretreatments processed the resulted transflectance spectra, and then partial least squares regression (PLSR) was applied. The data obtained from the spectra were evaluated based on the physical and chemical properties of the oil. α-guaiene and azulene chemical content were measured by liquid chromatography-mass spectrometry as a reference method. The best calibration for α-guaiene and azulene was second derivative with normalization mean centre, as data pretreatments. Both models had a high correlation coefficient (r>0.90), a low coefficient of variation (CV<2.98%), and an elevated ratio of standard error of prediction to standard deviation (RPD >3), which proved the applicability of NIRS to quality evaluation of patchouli oil.

Estimation of main chemical content of nutmeg oleoresin by using near infrared spectroscopy

Determination of the main chemical content of nutmeg oleoresin is usually carried out by the GCMS method that time-consuming and expensive. It is required a faster and cheaper method for the determination of chemical contents of nutmeg oleoresin. The purpose of this study was to estimate the main chemical composition of Banda nutmeg oleoresin by NIR Spectroscopy. Transflectance of nutmeg oleoresin were measured by the NIR spectrometer. The samples were then subjected to composition analysis using GCMS. The transflectance spectra were processed using some data pretreatments, and the calibration between transflectance and chemical composition were carried out by using Partial Least Square (PLS) and Principle Component Regression (PCR) method. The best estimation for myristicin by NIRS was obtained using original spectra and 3 factors of PLS ( r=0.95, SEC=1.56%, SEP=1.71%, CV=10.18%, RPD = 2.60, and consistency of 91%). The best estimation by NIRS for myristic acid was also obtained using original spectra and 5 factors of PLS ( r=0.95, SEC=3.94%, SEP=3.82%, CV=32.47%, RPD = 2.75, and consistency of 103%). Whereas for safrole was obtained by using data pre-treatment of de-trending and 7 factors of PLS (r = 0.98, SEC=0.08%, SEP = 0.10%, CV =10.87%, RPD = 3.82, and consistency of 82%).

Rapid detection of quality of Japanese fermented soy sauce using near-infrared spectroscopy.

This study investigated the feasibility of rapidly evaluating the final quality of Japanese fermented soy sauce (shoyu) using NIR spectroscopy and partial least-squares (PLS) regression. In total, 110 shoyu samples that had been entered in the annual soy sauce competition from 2016 to 2018 were collected and analyzed. The transmittance spectra (400-1800 nm) and the transflectance spectra (680-2500 nm) of these samples were acquired and processed by different pre-treatments. PLS regression was applied to the raw and processed spectra to construct models based on a calibration set (76 shoyu samples from 2016 and 2017) and to evaluate these models using a validation set (34 shoyu samples from 2018), according to their values for bias and root mean square error of prediction (RMSEP). The results showed that the models constructed using the full spectra of transflectance performed better than those using transmittance spectra. Comparing the influence of different regions in the transflectance spectra enabled the accuracy of the models to be improved. The model constructed from transflectance spectra from the 1800 to 2500 nm region using pre-treatment of second derivative was superior to the other models, with a bias value of -2 and the lowest RMSEP value of 13 in the validation set. To further narrow the wavelength range, the models constructed using the spectral region from 2050 to 2400 nm also showed a better performance for predicting the sensory quality of soy sauce products. This study has demonstrated that the NIR spectroscopy technique could be used as an alternative routine quality control procedure, which can rapidly and economically classify the quality of soy sauce products.

Concept and methodology of characterising infrared radiative performance of urban trees using tree crown spectroscopy

Urban trees play an important role in cooling urban microclimates and regulating outdoor thermal comfort. To better understand their contribution to these processes, it is crucial to elucidate urban trees' radiative thermal performance, especially in the infrared (IR) region (approximately 50% of solar radiation). Yet, owing to significant conceptual and methodological challenges, studies on the radiative performance of trees have mainly focused on individual leaves rather than crown-level characteristics. Here we applied a novel conceptual and methodological framework to characterise the crown-level IR radiative performance of 10 lime trees (Tilia cordata), a common urban tree in the UK and Europe. Our results show that reflected and transmitted solar energy from leaves is dominated (>70%) by IR radiation. At the leaf level, transmission and reflection spectra are similar between trees (differences typically < 10% in IR region), including those under significantly different urban stress conditions. However, at the crown-level, substantial variations in IR transflectance spectra (maximum difference > 40% in IR region) were found between trees. These variations were largely due to crown structural differences (leaf number, density, angles), rather than leaf solar interaction character (leaf-level transmittance or reflectance, leaf colour). Crown transflectance measured from the four cardinal directions was significantly different in the IR region (maximum differences circa 30%), and changed substantially with solar time. Hence, a tree's surroundings received very different, and time dependent, levels of solar IR radiation. These findings have significant implications for species selection and control of environmental stress factors in urban microclimates.

Multivariate Classification of UHT Milk as to the Presence of Lactose Using Benchtop and Portable NIR Spectrometers

Lactose hydrolyzed milk was developed in the 1970s to serve individuals with lactose intolerance. This demand for lactose-free products by lactose-intolerant consumers has created a market segment for this food whose quality control has to be guaranteed. In order to assess milk samples for lactose content, this work proposes an analytical methodology to classify regular and lactose-free ultra high temperature (UHT) milks using multivariate classification methods and NIR spectra obtained in FT-NIR and ultra-compact NIR spectrometers, aiming at field analysis. For this, 71 samples were purchased; 41 were lactose-free UHT milk and 30 regular UHT milk. Diffuse transflectance spectra were obtained by FT-NIR (833 to 2500 nm, 4 cm−1 of resolution and mean of 16 scans), and by ultra-compact NIR (908 to 1676 nm, with 12.5 nm of resolution and mean of 50 scans). The classification models were obtained by PLS-DA and LDA techniques with robust variables selection by SPA and GA, evaluating different spectral pre-processing (MSC, SNV, and derivatives). The three models developed (PLS-DA, GA-LDA, and SPA-LDA) with benchtop equipment spectra correctly classified all samples with sensitivity and specificity of 100%. For the portable equipment spectra, PLS-DA and GA-LDA models obtained sensitivity and specificity of 100%. The SPA-LDA model, however, presented sensitivity and specificity of 80 and 100%, respectively. These results indicate that methodologies using NIR equipment, especially the ultra-compact NIR, with multivariate classification techniques are feasible in discrimination between regular and lactose-free milk in the field, thus enabling a quick and precise analysis.

Removing interference-based effects from the infrared transflectance spectra of thin films on metallic substrates: a fast and wave optics conform solution

A hybrid formalism combining elements from Kramers-Kronig based analyses and dispersion analysis was developed, which allows removing interference-based effects in the infrared spectra of layers on highly reflecting substrates. In order to enable a highly convenient application, the correction procedure is fully automatized and usually requires less than a minute with non-optimized software on a typical office PC. The formalism was tested with both synthetic and experimental spectra of poly(methyl methacrylate) on gold. The results confirmed the usefulness of the formalism: apparent peak ratios as well as the interference fringes in the original spectra were successfully corrected. Accordingly, the introduced formalism makes it possible to use inexpensive and robust highly reflecting substrates for routine infrared spectroscopic investigations of layers or films the thickness of which is limited by the imperative that reflectance absorbance must be smaller than about 1. For thicker films the formalism is still useful, but requires estimates for the optical constants.

Real-time simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by near-infrared spectroscopy.

This paper proposes and proves a real-time and non-destructive strategy for sensitive and simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by near-infrared (NIR) spectroscopy. In this experiment, 88 samples of tazarotene gel (0.41–0.65 mg g−1 of tazarotene) were prepared using the standard addition method. Among them, 47 samples were inoculated with 50 μl of different concentrations of Escherichia coli (E. coli) DH5a in Luria–Bertani (LB) broth to give 1–4 log CFU g−1 of E. coli DH5a in the gel, 6 samples with 50 μl of LB broth, and 35 samples with nothing. Based on the gel NIR transflectance spectra, E. coli DH5a in the gel was detected by the counter propagation artificial neural network (CP-ANN) model with a classification accuracy of 100.0%, while tazarotene in the gel was simultaneously determined by the partial least squares regression (PLS) model with a root mean square error of cross-validation of 0.0232 mg g−1. Furthermore, 9 samples of real tazarotene gel were used to verify the practicality of the established NIR spectroscopy. The developed NIR strategy can be used to correctly and quickly release the pharmaceutical gels, required for sensitive and simultaneous control of microbial contamination and the active pharmaceutical ingredient (API) content, to the next stage.

Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithm

This paper proposes a new variable selection method for nonlinear multivariate calibration, combining the Successive Projections Algorithm for interval selection (iSPA) with the Kernel Partial Least Squares (Kernel-PLS) modelling technique. The proposed iSPA-Kernel-PLS algorithm is employed in a case study involving a Vis-NIR spectrometric dataset with complex nonlinear features. The analytical problem consists of determining Brix and sucrose content in samples from a sugar production system, on the basis of transflectance spectra. As compared to full-spectrum Kernel-PLS, the iSPA-Kernel-PLS models involve a smaller number of variables and display statistically significant superiority in terms of accuracy and/or bias in the predictions.

A feasibility study on the non-invasive analysis of bottled Compound E Jiao oral liquid using near infrared spectroscopy

The aim of this study was to explore the feasibility of near infrared (NIR) spectroscopy for the quantitative analysis of Compound E Jiao oral liquid, a popular oral TCM preparation, through intact glass vials. Transmission spectra were acquired with a sample holder tailored to the instrument's sample compartment. Total flavonoids, total saponins and soluble solid contents were considered as quality indicators of this oral preparation and calibration models were built using partial least-squares regression (PLSR) algorithm. The sample set was comprised of production samples as well as laboratory samples prepared by a concentrating-diluting method so as to extend the concentration range beyond the production variation. The developed models gave root mean square error of prediction (RMSEP) of 0.084mgmL−1 for total flavonoids, 0.014mgmL−1 for total saponins and 0.21% for soluble solid contents. To better evaluate the prediction performance, an independent set of ten production samples was introduced for the external validation. The models are compared with those built with the transflectance spectra collected in the destructive way. The results of paired t-test and F-test at a significance level of 0.05 revealed that the two sets of models exhibited comparable model performance. The overall results demonstrate that the proposed non-destructive method can be used as an advantageous alternative in the quality inspection of Compound E Jiao oral liquid production.

Rapid evaluation of craft beer quality during fermentation process by vis/NIR spectroscopy

The present work aimed to carry out a preliminary study to verify the possibility of employing an optical, portable and inexpensive non-destructive device, based on vis/NIR, spectroscopy, directly on the production line of craft beer.Three types of craft beer were analyzed. For each type of craft beer, transflectance spectra were acquired in the wavelength range of 450–980nm and at different stages of fermentation. Spectral sampling for each craft beer was conducted on filtered and non-filtered samples.The vis/NIR device was tested for the quick evaluation of soluble solid content (SSC) and pH. Spectra were elaborated in order to perform principal component analysis (PCA) and to build partial least square (PLS) regression models.The PCA results show that vis/NIR spectroscopy could be effective in discriminating between non-filtered (condition in the process line) and filtered samples. PLS models are promising for both the prediction of SSC and pH.

Electric field standing wave effects in FT-IR transflection spectra of biological tissue sections: Simulated models of experimental variability

The so-called electric field standing wave effect (EFSW) has recently been demonstrated to significantly distort FT-IR spectra acquired in a transflection mode, both experimentally and in simulated models, bringing into question the appropriateness of the technique for sample characterization, particularly in the field of spectroscopy of biological materials. The predicted effects are most notable in the regime where the sample thickness is comparable to the source wavelength. In this work, the model is extended to sample thicknesses more representative of biological tissue sections and to include typical experimental factors which are demonstrated to reduce the predicted effects. These include integration over the range of incidence angles, varying degrees of coherence of the source and inhomogeneities in sample thickness. The latter was found to have the strongest effect on the spectral distortions and, with inhomogeneities as low as 10% of the sample thickness, the predicted distortions due to the standing wave effect are almost completely averaged out. As the majority of samples for biospectroscopy are prepared by cutting a cross section of tissue resulting in a high degree of thickness variation, this finding suggests that the standing wave effect should be a minor distortion in FT-IR spectroscopy of tissues. The study has important implications not only in optimization of protocols for future studies, but notably for the validity of the extensive studies which have been performed to date on tissue samples in the transflection geometry.

The use of near infrared spectroscopy and multivariate techniques to differentiate Escherichia coli and Salmonella Enteritidis inoculated into pulp juice

This study shows the application and usefulness of near infrared (NIR) transflectance spectra measurements in the identification and classification of Escherichia coli and Salmonella Enteritidis from commercial fruit pulp (pineapple). Principal component analysis (PCA), soft independent modeling of class analogy (SIMCA) analysis and partial least-squares discriminant analysis (PLS-DA) were used in the analysis. It was not possible to obtain total separation between the samples using PCA and SIMCA. PLS-DA presented good performance achieving prediction ability of 87.5% for E. coli and 88.3% for S. Enteritidis, respectively. For the best models, the sensitivity and specificity was 0.87 and 0.83 for PLS-DA with second derivative spectra. These results suggest that NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in fruit pulp for modeling linear class boundaries.

Quantification of Casein Fractions and of Some of Their Genetic Variants in Phosphate Buffer by near Infrared Spectroscopy

Milk casein and casein fraction contents have a great influence on milk rennet properties and cheese yield so that the selection of dairy cattle with genetic characteristics suitable for milk transformation is of great interest to dairy farms and firms. The possibility of a rapid and accurate determination of these parameters would be very useful to predict milk aptitude to cheese making. This work aimed to determine casein fractions and their genetic variants content using near infrared (NIR) spectroscopy in reconstituted casein samples by comparing the performance of different NIR equipment (a monochromator instrument and a Fourier transform instrument) and different modes of measurement (reflectance and transflectance) in order to evaluate the best operative conditions for this application. Fifty-eight raw milk samples, collected from different farms in the Asturias region, Spain, were analysed for protein (TP%) and non caseinic nitrogen (NCN%) content using the Kjeldahl method. Casein content was calculated as the difference between TP and NCN content. Casein fractions (αs0-, αs1-, αs2-, κ-casein) and genetic variants of β-casein (βB- βA1-, βA2-casein) were determined by a capillary electrophoresis system. Samples were ultra-centrifuged to obtain native casein and then reconstituted in phosphate buffer (pH = 6.8) at the same original milk concentration, previously determined by the Kjeldahl method. Spectra were collected at 37°C with a FT-NIR instrument in transflectance mode and a monochrometer in both transflectance and reflectance mode. Partial least square (PLS) analyses performed on transflectance spectra showed good prediction ability for all variables—(min R2 = 0.80 for κ-casein; max R2 = 0.94 for βA2–casein), with the exception of αs2-casein. NIR spectroscopy has the ability to determine and quantify casein genetic variants and could be used to select milk for its final purpose and to predict the aptitude of milk to cheese-making.

Electric field standing wave artefacts in FTIR micro-spectroscopy of biological materials

FTIR absorption micro-spectroscopy is a widely used, powerful technique for analysing biological materials. In principle it is a straightforward linear absorption spectroscopy, but it can be affected by artefacts that complicate the interpretation of the data. In this article, artefacts produced by the electric-field standing-wave (EFSW) in micro-reflection-absorption (transflection) spectroscopy are investigated. An EFSW is present at reflective metallic surfaces due to the interference of incident and reflected light. The period of this standing wave is dependent on the wavelength of the radiation and can produce non-linear changes in absorbance with increasing sample thickness (non-Beer-Lambert like behaviour). A protein micro-structure was produced as a simple experimental model for a biological cell and used to evaluate the differences between FTIR spectra collected in transmission and transflection. By varying the thickness of the protein samples, the relationship between the absorbance and sample thickness in transflection was determined, and shown to be consistent with optical interference due to the EFSW coupled with internal reflection from the sample top surface. FTIR spectral image data from MCF 7 breast adenocarcinoma cells was then analysed to determine the severity of the EFSW artefact in data from a real sample. The results from these measurements confirmed that the EFSW artefact has a profound effect on transflection spectra, and in this case the main spectral variations were related to the sample thickness rather than any biochemical differences.

Detection and identification of selected bacteria, inoculated on chicken breast, using near infrared spectroscopy and chemometrics

Near-infrared transflectance spectra of chicken breast muscle inoculated with Listeria innocua FH 2333, Pseudomonas fluorescens 2088, Pseudomonas putida 49128, Pseudomonas mendocina or Escherichia coli K12 were investigated in order to examine the potential of NIRS to detect microbes on a food matrix. Inoculated samples were stored at 36 °C for 24 h. Two control groups were used in this study, one of fresh uninoculated samples analysed directly after removal of the muscle from the carcass and another of uninoculated chicken stored at 36 °C for 24 h. The findings of this study suggest the NIR spectroscopy can detect and differentiate between inoculated and uninoculated chicken breast muscle. In addition, it can discriminate fresh from non-fresh (in this case samples that are inoculated or not and stored at 36 °C) samples. On the other hand, NIR spectroscopy failed to differentiate between the five different strains used as inoculates for this study. These results suggest that the make up of the microflora of chicken fillets is not the deciding factor in detecting and differentiating chicken fillet samples. Instead, it seems that the total quantity of microflora present in conjunction with the physical changes associated with spoilage and, in particular, the differences in microbial concentration and level of muscle decomposition of inoculated and uninoculated samples, may be responsible for the separations observed in this analysis. This reason could also be the deciding factor for the separations achieved between the fresh samples and the other two groups.

Reflection contributions to the dispersion artefact in FTIR spectra of single biological cells

Fourier transform infrared spectra of a single cell in transflection geometry are seen to vary significantly with position on the cell, showing a distorted derivative-like lineshape in the region of the optically dense nucleus. A similar behaviour is observable in a model system of the protein albumin doped in a potassium bromide disk. It is demonstrated that the spectrum at any point is a weighted sum of the sample reflection and transmission and that the dominance of the reflection spectrum in optically dense regions can account for some of the spectral distortions previously attributed to dispersion artefacts. Rather than being an artefact, the reflection contribution is ever present in transflection spectra and it is further demonstrated that the reflection characteristics can be used for cellular mapping.

Detection and Identification of Bacteria in an Isolated System with Near-Infrared Spectroscopy and Multivariate Analysis

Near-infrared (NIR) transflectance spectra of Listeria innocua FH, Lactococcus lactis, Pseudomonas fluorescens, Pseudomonas mendocina, and Pseudomonas putida suspensions were collected and investigated for their potential use in the identification and classification of bacteria. Unmodified spectral data were transformed (first and second derivative) using the Savitzsky-Golay algorithm. Principal component analysis (PCA), partial least-squares discriminant analysis (PLS2-DA), and soft independent modeling of class analogy (SIMCA) were used in the analysis. Using either full cross-validation or separate calibration and prediction data sets, PLS2 regression classified the five bacterial suspensions with 100% accuracy at species level. At Pseudomonas genus level, PLS2 regression classified the three Pseudomonas species with 100% accuracy. In the case of SIMCA, prediction of an unknown sample set produced correct classification rates of 100% except for L. innocua FH (77%). At genus level, SIMCA produced correct classification rates of 96.7, 100, and 100% for P. fluorescens, P. mendocina, and P. putida, respectively. This successful investigation suggests that NIR spectroscopy can become a useful, rapid, and noninvasive tool for bacterial identification.