VIS-NIR Range Research Articles

Multispectral Imaging for Hemoglobin Estimation by PCA.

Tissular blood perfusion is helpful to assess the health condition of a subject and even monitor superficial lesions. Current state of the art is focused on developing non-invasive, quantitative and accessible methods for blood flow monitoring in large areas. This paper presents an approach based on multispectral images on the VIS-NIR range to quantify blood perfusion. Our goal is to estimate the changes in deoxygenated hemoglobin. To do so, we employ principal component analysis followed by a linear regression model. The proposal was evaluated using in-vivo data from a vascular occlusion protocol, and the results were validated against photoplethysmography measurements. Although the number of subjects in the protocol was limited, our model made a prediction with an average similarity of 91.53% with a mean R-squared adjusted of 0.8104.

Fabrication and characterization of Ge/graphene heterojunction on a flexible polyimide substrate

To fabricate a flexible near-infrared (NIR) photodetector, the Ge/graphene (Ge/Gr) heterojunction was fabricated by using pulsed laser deposition on copper-supported graphene, and then the heterojunction was transferred onto flexible polyimide (PI) substrate. The Ge/Gr heterostructure grown at 530 °C demonstrates a flat surface and good crystalline quality. Compared with the as-grown Ge/Gr heterojunction on Si substrate, the Raman spectra of the transferred Ge/Gr heterojunction have no significant change, which indicates the successful transfer of the heterojunction. The Ge/Gr heterojunction has significantly enhanced absorption characteristics in the VIS-NIR range, exhibits rectification ratio up to 13.5 at ± 3 V and stable photoresponse to the NIR light at zero voltage bias.

Supporting soil and land assessment with machine learning models using the Vis-NIR spectral response

Soil Vis-NIR spectral response had been widely proposed as an alternative to costly and time-consuming laboratory determination of soil physical and chemical properties. However its use for measuring soil quality index directly has not been well explored. This study compares the effectiveness of different machine learning models on a large spectral library using a database collected by the European Union project “Land Use and Coverage Area frame Survey” (LUCAS). Three approaches to predicting mineral soil features by processing their spectral response for the Vis-NIR range were tested. Prediction models of clay content, pH in CaCl2, organic carbon (SOC), calcium carbonate (CaCO3), nitrogen (N), and cation exchange capacity (CEC) were analyzed. Three types of models were assessed: a Stacked AutoEncoder, a convolutional neural network, and a stack model composed of a set of multilayer perceptron algorithms with two different regression estimation solutions. Modeling with CNN was identified as the optimal solution. Similar, and in some cases, better results can be obtained from ensembles of machine learning algorithms. The estimates of soil characteristics made with the help of the Stacked AutoEncoder showed the greatest errors. The use of soil feature estimates to support soil and land classification was also analyzed. An indicator describing the state of the topsoil is presented, which assists the objective classification of soils. The research showed that the accuracy of the estimation of the proposed Topsoil Quality Index (TQI) estimated directly based on Vis-NIR spectral response and indirectly based on estimated values of selected soil features is practically identical. The research confirms the suitability of Vis-NIR spectroscopy for topsoil assessment.

Development of Calibration Models to Predict Mean Fibre Diameter in Llama (Lama glama) Fleeces with Near Infrared Spectroscopy.

Simple SummaryIn the Puna region of Argentina, llama fibre production has enormous social, economic and environmental potential, but is still in its early stages of development. For this reason, classification and quality analysis systems used today are still deficient. Near infrared reflectance spectroscopy is a technological resource used in the agroindustry for quality analysis of organic compounds. In this work we studied the feasibility of this technology to evaluate the mean fibre diameter, which is one of the most important quality parameters in the textile industry. Despite some limitations, which are mainly related to fibre heterogeneity, the results obtained were encouraging as spectroscopy could be used in screening programmes as a sustainable, fast and low-cost method to improve fibre quality validation.Llama fibre has the potential to become the most valuable textile resource in the Puna region of Argentina. In this study near infrared reflectance spectroscopy was evaluated to predict the mean fibre diameter in llama fleeces. Analyses between sets of carded and non-carded samples in combination with spectral preprocessing techniques were carried out and a total of 169 spectral signatures of llama samples in Vis and NIR ranges (400–2500 nm) were obtained. Spectral preprocessing consisted in wavelength selection (Vis–NIR, NIR and discrete ranges) and multiplicative and derivative pretreatments; spectra without pretreatments were also included, while modified partial least squares (M-PLS) regression was used to develop prediction models. Predictability was evaluated through R2: standard cross validation error (SECV), external validation error (SEV) and residual predictive value (RPD). A total of 54 calibration models were developed in which the best model (R2 = 0.67; SECV = 1.965; SEV = 2.235 and RPD = 1.91) was obtained in the Vis–NIR range applying the first derivative pretreatment. ANOVA analysis showed differences between carded and non-carded sets and the models obtained could be used in screening programs and contribute to valorisation of llama fibre and sustainable development of textile industry in the Puna territory of Catamarca. The data presented in this paper are a contribution to enhance the scarce information on this subject.

Direct Laser Writing for the Formation of Large‐Scale Gold Microbumps Arrays Generating Hybrid Lattice Plasmon Polaritons in Vis–NIR Range (Advanced Optical Materials 12/2021)

Evaldas Stankevicius and co-workers (article number 2100027) demonstrate the formation of large-scale gold microbump arrays generating hybrid lattice plasmon polaritons in the visible to near-infrared range using direct laser writing technique. The demonstrated method shows relevant technological progress in the formation of large-scale metallic gratings by using a cost-effective laser-based technique. It provides new opportunities for hybrid lattice plasmon polariton (HLPP)-based applications in biotechnology, photonics, and plasmonics.

Direct Laser Writing for the Formation of Large‐Scale Gold Microbumps Arrays Generating Hybrid Lattice Plasmon Polaritons in Vis–NIR Range

AbstractSurface plasmon polaritons (SPPs) based light–matter interactions play a major role in photonic sensor applications. In order to implement such sensors in microchip devices or reduce the fabrication costs, a method with high flexibility and large‐scale capabilities must be developed. Here, the formation of large‐scale gold microbumps arrays by using a direct laser writing technique is presented. The fabricated arrays exhibit the hybrid lattice plasmon polaritons in the Vis–NIR range, in the same range as metallic gratings fabricated by lithography‐based techniques. The peak of hybrid lattice plasmon resonance depends on the period of the fabricated arrays, the thickness of the gold film, coupled light polarization, and sample orientation. The experimental results are in good agreement with the theoretical estimation. The demonstrated method shows relevant technological progress in the formation of large‐scale metallic gratings by using a cost‐effective laser‐based technique. It provides new opportunities for hybrid lattice plasmon polariton (HLPP)‐based applications in biotechnology, photonics, plasmonics, and so on.

Optical properties of Bromothymol Blue/PVA Composite: Development of flexible high performance laser filter

The present work reports the development of bromothymol blue (BTB) dye incorporated PVA composite films for flexible laser filter applications. The flexible films are prepared via simple solution casting technique. Different weight percentages (0.1%, 1.0% and 4.0%) of BTB are incorporated in the polymer matrix. The structural, morphological and ductility properties of the films are studied by using XRD, FESEM and stress-strain measurement techniques, confirming the successful inclusion of the dye in PVA matrix. The band gap of the BTB/PVA samples is decreased to ~2eV from 4.7eV, the band gap of pure PVA, which indicates the change in optical properties of the system due to the introduction of the dye. The 1.0% BTB/PVA composite films show almost zero transmittance in the 200-550nm wavelength range, but remain transparent in the rest of the visible-NIR range. 1.0% BTB/PVA film based laser filter shows excellent performance to block light from a high power laser (~5mW) of the wavelength ~540nm even when the filter is exposed continuously for 36 minutes. A figure of merit (FOM) parameter is introduced in this work to estimate the efficiency and applicability of polymer based laser filters. 1.0% BTB/PVA film based laser filter shows fairly high FOM proving its ability as a strong candidate for flexible laser filter applications.

Copper Oxide Spectral Emission Detection in Chalcopyrite and Copper Concentrate Combustion

In this research, the spectral detection of copper oxide is reported from different combustion tests of chalcopyrite particles and copper concentrates. Combustion experiments were performed in a bench reactor. In all the tests, the radiation emitted from the sulfide particle reactions was captured in the VIS–NIR range. The obtained spectral data were processed by using the airPLS (adaptive iteratively reweighted penalized least squares) algorithm to remove their baseline, and principal component analysis (PCA) and the multivariate curve resolution method alternate least squares (MCR-ALS) methods were applied to identify the emission lines or spectral bands of copper oxides. The extracted spectral pattern is directly correlated with the emission profile reported in the literature, evidencing the potential of using spectral analysis techniques on copper sulfide combustion spectra.

Tissue Optical Clearing in the Ultraviolet for Clinical Use in Dentistry to Optimize the Treatment of Chronic Recurrent Aphthous Stomatitis

The immersion optical clearing (OC) treatment with a highly concentrated glycerol solution has induced three new tissue windows in the UV spectral range of gingival tissues – from 200 to 250 nm, from 250 to 300 nm and from 300 to 400 nm. By combining the immersion OC technique in human tissues with UV-spectroscopy, it was possible to verify and study the major OC mechanisms – tissue dehydration and refractive index matching, and that the OC efficiency is higher in the deep-UV than in the visible-NIR range. Since all biological tissues present high scattering in the UV range, the presented technology, which basically reduces the strong light scattering in the UV range, has a broad application area in medicine. The effectiveness of the developed technology combining UV phototherapy and OC in application to treatment of aphthous recurrent stomatitis in children was demonstrated.

An Ultra-Portable Vis-NIR Spectrometer with an Integrated Light Source for Chemometric Applications

On-site material inspection and quality analysis of food and agricultural produce require portable sensing systems. We report the development of a miniaturized spectrometer with an integrated light source operating in the visible and near-infrared range, for chemometrics based material-sensing applications. The proposed system uses off-the-shelf light source and detector. The electronic circuit is designed, developed, and tested in-house. To validate the system’s usability, a set of classification experiments are carried out with measured spectra from culinary white powders and medicinal pills. Several classification algorithms are used to build predictive models and the best-suited ones give prediction accuracies of 80% and 92.6% respectively. A regression model built to estimate the curcumin content in turmeric shows a coefficient-of-determination of 0.97 for prediction. With more than 90% repeatability in the measured reflectance spectra, robustness of the device is demonstrated. Realization of a portable spectrometer, along with a framework for building appropriate prediction models, is expected to spur the development of point-of-use material sensing in the Vis-NIR range.

Flexible and high-performance broadband nanoflowers tin sulfide photodetector

A significant prerequisite for the development of a high-performance photodetector remains its low dark current value, because it promotes sensitivity and signal-to-noise ratio, in addition to low detectability light power density. Nevertheless, the fabricated photodetectors, which are based on deposited tin sulfide (SnS) films onto a flexible (PET at pH 5) and glass substrates, exhibited relatively high dark current values around (0.2 µA) and (several µA), respectively. This study proposes a novel approach for a better control of the photoresponse characteristics of nanostructured SnS film which resulted from reducing the deposition growth rate by adjusting the pH of the reaction solution to 5.8. The film was deposited onto a flexible substrate of polyethylene terephthalate (PET) using an inexpensive chemical bath deposition method. The as-fabricated photodetector exhibited a low dark current value approximately (~ 24 nA) at 5 V bias voltage and a good response in a broad range covering the UV up to the near-infrared. Besides, light-emitting diodes (380, 530, 750, and 850 nm) were used to investigate the photoresponse characteristics of the photodetector. The latter manifested fast photoresponse times (rise and decay) and good sensitivity for all used illumination wavelengths. Furthermore, under various illumination power densities of 850 nm, the photocurrent manifested a good dependence upon power density. Based on the obtained excellent photoresponse characteristics, this photodetector is promising for the photoelectronic flexible device in the UV–Vis–NIR range.

Optical characterization and γ-irradiation response of conductive transparent oxide of SnO2:Sb films

We are concerned in synthesizing conductive transparent oxide (CTO) films by spray pyrolysis deposition (SPD) for SnO2 (undoped) and SnO2:Sb (doped) film. The average value of the optical energy gap for CTO films of SnO2 and SnO2:Sb were found 4.01and 3.92 eV, respectively for direct transition before gamma irradiation. The optical conductivity of undoped and doped CTO film was calculated 8 × 1014 and 24 × 1014 Ω-1cm-1, respectively. The average value of refractive index for SnO2 and SnO2:Sb films was found 1.93 and 1.67, respectively at 0.0 kGy. The average value of refractive index of annealed SnO2:Sb films was decreased from 2.07 to 1.55 after γ-irradiation (22.0 kGy). The values of real part for the thermal annealed SnO2:Sb films were found positive before and after γ-irradiation in Vis-NIR range; accordingly the thin film material is said to have an intrinsically capacitive optical response. The imaginary part values of annealed SnO2:Sb film were decreased after γ-irradiation (22.0 kGy) in Vis-NIR range but still have positive value; so the material is said to have a resistive optical response. The optimum contact angle of doped CTO films was found 30° with hydrophilic surface. This property of CTO could be applied as covers for solar cells and other devices to keep its efficiency during rains and high humidity.

Novel bio-based composite phase change materials with reduced graphene oxide-functionalized spent coffee grounds for efficient solar-to-thermal energy storage

Spent coffee grounds (SCGs), a kind of highly recyclable and useable biomass, are often ignored, discarded, and further become a serious environmental threat. In this work, effective high-value utilization of SCGs in the field of composite phase change materials (CPCMs) was proposed. SCGs with the introduction of 1–5 wt% reduced graphene oxide (RGO) were used as supporting material to stabilize the shape of the CPCMs to solve problems of leakage and low light-to-heat conversion. RGO-modified SCGs (SCGs@RGO) have a better three-dimensional porous structure than pristine SCGs, therefore absorbing 60.3 wt% PEG and having excellent leakage-proof performance and showing slight thermal conductivity enhancements. SCGs@RGO has strong absorption in the full UV–Vis–NIR range, hence it exhibits extremely strong light-to-heat conversion capacity and stores solar thermal energy in a short time (245 s) of light. Besides, PEG/SCGs@RGO CPCMs show good reusability, chemical stability, crystalline stability, and excellent thermal stability in phase change tests up to 100 cycles.

Self‐Organized Gold Network–Vanadium Dioxide Hybrid Film for Dynamic Modulation of Visible‐to‐Near‐Infrared Light

Composites of phase change material (PCM) and structured metal (SM) are promising templates for photonic applications combining advantages of both insulator–metal transition (IMT) hysteresis and strong light–matter interactions. While significant progress has been made for applications including active modulators, photonic memories, and thermal emitters in the THz‐microwave regime, the fabrication and application of PCM–SM for the visible–near‐infrared (vis–NIR) waves are still limited by the difficulties associated with fabricating nanostructures in a controllable and scalable manner. Herein, a self‐organized gold network–vanadium dioxide hybrid film fabricated by a simple spin‐coating process following the metal deposition, as a litho‐free PCM–SM template in a vis–NIR regime, is demonstrated. Using Fabry–Perot‐type interference, which enhances IMT‐induced refractive index changes, resonance shift of as much as 260 nm and reflection modulation depth of ≈49% in vis–NIR range are then demonstrated. Tuning of the resonance peak from 575 to 950 nm with the control of VO2 thickness, in addition to the manipulation of hysteresis characteristics with the control of self‐organized gold network is also demonstrated. As application examples, thermoactive color film and electrically controlled photonic logic gates in vis–NIR are presented.

Dual defects and build-in electric field mediated direct Z-scheme W18O49/g-C3N4−x heterojunction for photocatalytic NO removal and organic pollutant degradation

In this work, dual defects mediated W18O49/g-C3N4−x heterojunction was prepared by in-situ hydrothermal method. The conversion from Ⅱ-type to Z-scheme heterojunction was achieved due to the formation of build-in electric field from g-C3N4−x to W18O49. Tests results indicated that the LSPR hot electrons of W18O49 could directly drive oxygen reduction reaction to generate O2− species and the partial electrons of g-C3N4−x were captured by O defect states of W18O49 to stabilize its free charge density, resulting in the continuous generation of high-energy hot electrons. The photo-generated carriers had the stronger redox ability compared with g-C3N4−x and W18O49 due to the Z-scheme charge transfer paths. Combined with the promoted exciton dissociation induced by N vacancies, the enhanced light absorption and accelerated carriers’ separation induced by near-field enhancement effect in visible-NIR range of oxygen vacancies, W18O49/g-C3N4−x heterojunction exhibited enhanced photocatalytic performance for NO removal and full-solar-spectrum-driven pollutants degradation.

A Chemometric Study of Vis-NIR Reflectance Spectra of Turmeric Powders to Quantify Total Curcuminoids

This study focuses on the synergistic application of spectroscopy and multivariate analysis for refined quantification of total curcuminoids in powdered turmeric samples. Quantifying the pharmacologically active curcumin is a direct way of analyzing the quality of a particular turmeric sample, and hence paving the way to establish its market value. In this study, the spectra of sieved turmeric powders were collected in the Vis-NIR range (wavelength 360-1030 nm) and subjected to multivariate analysis. The content of total curcuminoids was first accurately quantified by high performance liquid chromatography (HPLC), which served as the reference data. The combination of multiplicative scatter correction, de-resolving, orthogonal scatter correction, and the first derivative of the spectra were used as pre-processing steps to filter the informative features of the spectra by reducing noise. This sample set included curcuminoids in the range of 1-4% as established by HPLC. The correlation between the processed spectra and the curcumin content was examined by the partial least squared regression (PLSR) algorithm through the construction of two kinds of models. A coarse model for broad classification, having 66 samples of 15 scans each (total – 990 spectra), was used as training data, which gave a correlation coefficient (r2) of 0.92 at PLS factor 7. Cross validation was performed on a test data of 10 samples which yielded a root mean squared error of cross validation (RMSECV) of 0.219. Along with this, the ratio of prediction to deviation (RPD) was calculated to estimate the robustness of the model in the long run, and was found to be 3.06. Owing to the diversity in the range of values and the need for poignant accuracy in quantifying the total curcuminoids through its spectrum, two sets of finer models were constructed. The result of the coarse model’s prediction along with the error (\U0001d465±Δ\U0001d465) for a test sample determined which of the finer models was best suited to give the final predicted value of curcumin. The first set of fine models covered the range of 1-2%, 2-3% and 3-4%, while the second set comprised models in the range of 1.5-2.5% and 2.5-3.5%, to eliminate ambiguity for predicted values falling on the border. For each of the finer models, r2 was in the range of 0.90-0.96 (Figure 1(a)), RMSECV was between 0.06-0.13 (Figure 1(b)) and RPD was greater than 4, all confirming good accuracy.Extensive research has been conducted on similar lines with most of them, if not all, exploiting the NIR range (wavelength 700-2500nm) to pick up signatures of specific chemical bonds arising due to their different modes of vibration, and correlating the measured spectrum with the reference curcumin value. For this study, the key takeaway in terms of novelty is the use of curcumin’s signature peak (wavelength 400-450nm) with the added benefits of chemometrics through the construction of a coarse and fine model. The easily available miniaturized light source and detectors in this spectral range along with a robust deployable chemometric model set the stage for the development of portable handheld devices. In conclusion, it is safe to say that the Vis-NIR spectroscopy combined with powerful tools of multivariate analysis could be used as a rapid, non-destructive method for a wide range of curcuminoid measurement in powdered turmeric samples of diverse origins Figure 1

Vision system for detection of defects on apples using hyperspectral imaging coupled with neural network and Haar cascade algorithm

The article is devoted to the development of algorithms for detecting defective apples transported on a roller conveyor using a vision system. In developing the algorithms, the possibility of classifying various regions of interest (intact and damaged by rot, scab, codling moth, as well as the conveyor) by the principal component method was investigated. When choosing the optimal spectral region for cluster analysis, spectrograms obtained in various spectral ranges, including Vis-NIR (400–1000 nm), NIR (780–1000 nm), and Vis (400–780 nm) were used. The PCA method showed that for the successful classification of the conveyor area, intact, decayed and damaged by the codling moth, it is necessary to use spectrograms in the Vis-NIR range. To classify these ROIs, it was proposed to use a direct distribution neural network with two hidden layers of 128 and 64 layers, respectively, the “relu” activation function in the hidden layers and the “softmax” activation function in the output layer. The optimal network configuration was determined experimentally. This configuration showed a classification accuracy of 0.847 on a test sample of 6,000 apples. Since the samples of spectrograms of scab and stem regions do not differ, for their classification in parallel with the neural network, it was proposed to use the Haar cascade classifier trained on 2000 two-dimensional images of apples in the visible region containing scab and stem regions. The classification accuracy was at least 0.95. The developed algorithm is intended for use in the robotic sorting of apples.

Visible and near-infrared spectroscopy with chemometrics are able to predict soil physical and chemical properties

Comparing to conventional laboratory methods, visible–near-infrared reflectance (vis–NIR) spectroscopy is a more practical and cost-effective approach for estimating soil physical and chemical properties. This paper aims to build statistical machine learning models to investigate the efficiency of spectral data for comprehensive evaluation of the soil quality indicators. Seventeen physical and chemical properties were measured using standard methods as indicators of soil quality. Soil samples were scanned in the laboratory in the vis–NIR range (350–2500 nm), the calibration set of 31 samples and the validation set of 13 samples for cross-validation and independent validation; twenty-four preprocessing methods were tested to improve predictions, and a partial least squares regression (PLSR) was used to predict soil quality indicators. Comparing model indices, the model constructed based on the PLSR machine learning method has a good predictive power (R2 > 0.9, ratio of performance to deviation (RPD) > 3.0). For physical and chemical properties, the bulk density (BD, R2 = 0.97, RPD = 5.90), soil organic matter (SOM, R2 = 0.98, RPD = 8.56), pH (R2 = 0.95, RPD = 4.40), and TN (R2 = 0.98, RPD = 6.67) concentration were predicted. This indicates that the method is suitable for the prediction of these soil elements in this study area. For the heavy properties, except for Mn, Zn, Cd, and As, the other five heavy metal concentrations were well predicted. It can be seen that the prediction ability of the construction model is Hg, Cr, Pb, Ni, and Cu in order of superiority to inferiority. The results show that a combination of spectroscopic and chemometric techniques can be applied as a practical, rapid, low-cost, and quantitative approach for evaluating soil physical and chemical properties in Shaanxi, China.

Anisotropic Au-ZnO photocatalyst for the visible-light expanded oxidation of n-hexane

In this work we present a novel metal-semiconductor heterostructure that contains triangular and prism-shaped plasmonic gold nanostructures directly synthesized and assembled onto ZnO nanostructures. Spatially-resolved (SR) high-resolution electron energy loss spectroscopy (EELS) at the local (sub-nanometer scale) level confirmed the field enhancement of the local electromagnetic fields in the surroundings of the triangular and prism-shaped Au nanostructures and in the interfacial junction between Au and ZnO. Different LED excitation sources have been systematically selected in the whole UV–vis-NIR range to evaluate the photocatalytic response of the Au-ZnO heterostructures towards the oxidation of n-hexane, selected as a model VOC present in indoor environments. The Au-ZnO exhibits visible expanded photo-response with the more energetic interband and intraband electrons and the higher LED irradiation wavelengths and it is able to outperform its ZnO plain counterpart.

Study of optical properties of graphene flakes and its derivatives in aqueous solutions.

In this work, we study optical spectroscopy of graphene flakes and its derivatives such as graphene oxide and reduced graphene oxide in the same surfactant-free aqueous solution. We show that transmittance (T) and absorbance (A) spectra of different graphene suspension is nearly feature-less as a function of wavelength (λ) in the VIS-NIR range (350-1000 nm) except graphene oxide solution and the smallest graphene flakes, and they change linearly with concentration. The optical absorption coefficient (at 660 nm) of pure graphene solution seems to be flake-size dependent, changing from ∼730 mL·mg-1m-1 (for ∼25 µm flake size) to ∼4400 mL·mg-1m-1 (for ∼2 µm flake size), and it is several times higher than in the case of graphene oxide, which also varies with type and level of doping/defects (checked by FTIR and statistical Raman spectroscopy). Finally, we show wavelength-dependent evolution of optical absorption coefficient in the VIS-NIR range, which is roughly mimicking the A(λ) function but is strongly material-dependent. Our study could be useful for application of graphene solution in optofluidic devices, functional inks or printed flexible optoelectronics.