NIR Spectroscopy Technique Research Articles

Substitution of an isovalent Te-ion in SnSe thin films for tuning optoelectrical properties

In present work, SnSe1-xTex thin films with varying Te concentrations were deposited on glass substrate through thermal evaporation technique. SnSe1-xTex thin films were characterized using X-ray diffraction (XRD), atomic force microcopy (AFM), X-ray photoelectron spectroscopy (XPS), UV–Vis NIR spectroscopy and room-temperature hall measurements technique. XRD patterns revealed that all the samples had a polycrystalline orthorhombic structure. Additionally, a low level of Te impurity improved the crystalline quality of the SnSe thin films. AFM images showed a noticeable alteration in the surface structure of the SnSe thin films caused by Te doping. UV–Vis NIR spectroscopy was employed to assess the optical characteristics of SnSe1-xTex thin films, revealing a variation in the optical band gap energy (Eg) between 1.75 and 1.89 eV, attributed to Te doping. The Hall effect measurement revealed n-type conductivity, and the carrier concentration decreased as the Te dopant concentration increased, corresponding to a decrease in antisite SnSe defects. The experimental findings suggest that adding a moderate amount of Te is a beneficial method for enhancing the optical and electrical properties of SnSe films. Furthermore, the Schottky device parameters of the Ag/SnSe1-xTex/Al:ZnO structure were established by analyzing the temperature-dependent Current-Voltage (I–V-T) characteristics through the thermionic emission current transport mechanism.

Nondestructive Metabolomic Fingerprinting: FTIR, NIR and Raman Spectroscopy in Food Screening

In recent years, there has been renewed interest in the maintenance of food quality and food safety on the basis of metabolomic fingerprinting using vibrational spectroscopy combined with multivariate chemometrics. Nontargeted spectroscopy techniques such as FTIR, NIR and Raman can provide fingerprint information for metabolomic constituents in agricultural products, natural products and foods in a high-throughput, cost-effective and rapid way. In the current review, we tried to explain the capabilities of FTIR, NIR and Raman spectroscopy techniques combined with multivariate analysis for metabolic fingerprinting and profiling. Previous contributions highlighted the considerable potential of these analytical techniques for the detection and quantification of key constituents, such as aromatic amino acids, peptides, aromatic acids, carotenoids, alcohols, terpenoids and flavonoids in the food matrices. Additionally, promising results were obtained for the identification and characterization of different microorganism species such as fungus, bacterial strains and yeasts using these techniques combined with supervised and unsupervised pattern recognition techniques. In conclusion, this review summarized the cutting-edge applications of FTIR, NIR and Raman spectroscopy techniques equipped with multivariate statistics for food analysis and foodomics in the context of metabolomic fingerprinting and profiling.

Integration of Vis–NIR Spectroscopy and Machine Learning Techniques to Predict Eight Soil Parameters in Alpine Regions

Visible and near-infrared spectroscopy (Vis–NIR, 350–1100 nm) has great potential for predicting soil properties. However, current research on the hyperspectral prediction of soil parameters in agricultural areas of alpine regions and the types of parameters included is limited, and optimal spectral treatments and predictive models applicable to different parameters have not been sufficiently investigated. Therefore, we evaluated the accuracy of predicting total nitrogen (TN), phosphorus pentoxide (TP2O5), total potassium oxide (TK2O), alkali-hydrolyzable nitrogen (AHN), effective phosphorus (AP), effective potassium (AK), soil organic matter (SOM), and pH in the Qinghai–Tibet Plateau using the Vis–NIR technique in combination with spectral transformations, correlation analysis, feature selection, and machine learning. The results show that spectral transformations improve the correlation between spectra and parameters but are dependent on the parameter type and the method used. Continuum removal (CR), logarithmic first-order differential (FDL), and inverse first-order differential (FDR) had the most significant effects. The feature bands were extracted using the SPA and modeled using partial least squares (PLSR), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and backpropagation neural networks (BPNNs). The accuracy was evaluated based on R2, RMSE, RPD, and RPIQ. We found that the PLSR model only enables the prediction of SOM and pH with lower accuracy than the remaining models. XGBoost can predict all of the parameters but only for AHN; the prediction performance is better than other methods (R2 = 0.776, RMSE = 0.043 g/kg, and RPIQ = 2.88). The RF, SVM, and BPNN models cannot predict AK, AP, and AHN, respectively. In addition, TP2O5, AP, and pH are best suited for modeling using RF (RPIQ = 2.776, 3.011, and 3.198); TN, AK, and SOM are best suited for modeling using BPNN (RPIQ = 2.851, 2.394, and 3.085); and AHN and TK2O are best suited for XGBoost and SVM, respectively (RPIQ = 2.880 and 3.217). Therefore, this study can provide technical and data support for the accurate and efficient acquisition of soil parameters in alpine agriculture.

The Determination of Ethanol Levels in Facial Freshener Using the NIR Spectroscopy and Chemometric Method

A facial freshener, also known as toner, is a cosmetic product that is commonly used to invigorate the face after a busy day. Ethanol serves as a key component in toner, serving multiple purposes such as being a solvent, preservative, and antimicrobial agent. However, it's important to note that toner formulated for normal skin types typically contain ethanol in small concentrations, adhering to a limit of not more than 10%. Therefore, this study aims to determine ethanol levels in toner using the NIR spectroscopy and chemometric techniques. The NIR spectra of the simulated samples were correlated with ethanol concentration using chemometric calibration model. The calibration models used were partial least square (PLS), principal component regression (PCR), and support vector regression (SVR). The calibration model was validated by leave one out cross validation (LOOCV) as well as the external validation, and the precision and accuracy of the method was evaluated. Among the calibration models, the PLS model exhibited the best performance, yielding an impressive R2 0.9976; with an RMSEC value of 0.4364 and RMSECV value of 0.4704. The internal validation yield R2 value more than 0.99 and RMSE of less than 0,4198. Furthermore, external validation showed the R2 and RMSEP value of 0.989 and 0.920 respectively. The %recovery and RSD value were 101.2% and 0.129%. Comparing ethanol measurements obtained through the NIR chemometric method with those obtained using gas chromatography as the reference method, no significant difference was observed at a 95% confidence levels, as indicated by a significance value of 0.231.

Cationic substitution engineering achieves higher efficiency and thermal stability of Cr3+-activated phosphor for pepper (Capsicum annuum L.) development

Nowadays, near-infrared phosphor-converted light emitting diodes (NIR pc-LEDs) attract wide attention since the NIR spectroscopy technique can exert itself in many fields. However, most of the developed NIR phosphors are still not commercially viable, because of low internal/external quantum yield and poor thermal resistance. Therefore, it is urgent to develop an efficient irradiance and thermal stable NIR phosphor. In this work, the new GdAl3-x-yGay(BO3)4: xCr3+ phosphors, compared with the original phosphor (x = 0.03, y = 0), when x = 0.03, y = 0.2, the luminescence intensity increased by 2.1 times, and the thermal resistance jumped from 92.0% to 96.7%. At the same time, with the increase of Ga3+, the spectra were gradually red shifted and FWHM widened, attributing to the nephelauxetic effect and the electron-phonon coupling effect enhanced, respectively. Particularly, under 420 nm excitation, the internal and external quantum yield of GdAl2.77Ga0.2(BO3)4: 0.03Cr3+ were 93.4% and 35.5%, respectively, which is higher than the previous research. The electric-optical conversion efficiency of the pc-LED was 10.76%. Finally, the phosphor application experiments revealed that the prepared phosphor has a very high commercial application potential.

Identification of Transgenic Agricultural Products and Foods Using NIR Spectroscopy and Hyperspectral Imaging: A Review

Spectroscopy and its imaging techniques are now popular methods for quantitative and qualitative analysis in fields such as agricultural products and foods, and combined with various chemometric methods. In fact, this is the application basis for spectroscopy and spectral imaging techniques in other fields such as genetics and transgenic monitoring. To date, there has been considerable research using spectroscopy and its imaging techniques (especially NIR spectroscopy, hyperspectral imaging) for the effective identification of agricultural products and foods. There have been few comprehensive reviews that cover the use of spectroscopic and imaging methods in the identification of genetically modified organisms. Therefore, this paper focuses on the application of NIR spectroscopy and its imaging techniques (including NIR spectroscopy and hyperspectral imaging techniques) in transgenic agricultural product and food detection and compares them with traditional detection methods. A large number of studies have shown that the application of NIR spectroscopy and imaging techniques in the detection of genetically modified foods is effective when compared to conventional approaches such as polymerase chain reaction and enzyme-linked immunosorbent assay.

A Super‐Broadband NIR Dual‐Emitting Mg2SnO4:Cr3+,Ni2+ Phosphor for Ratiometric Phosphor‐Converted NIR Light Source Applications

AbstractNear‐infrared (NIR) phosphor‐converted light‐emitting diodes (pc‐LEDs) have sparked tremendous interest in NIR spectroscopy. However, conventional NIR pc‐LEDs with a narrow full‐width at half‐maximum (FWHM) and single‐emission block the detection scope and detection accuracy for NIR spectroscopy analysis. Herein, a multicenter strategy is developed for the preparation of blue‐light‐excitable Mg2SnO4:Cr3+,Ni2+ phosphors with NIR dual‐emission (λem = 830/1480 nm, total FWHM = 532 nm). Benefiting from the unique NIR dual‐emission, a ratiometric measurement system with a self‐calibration function is established for highly precise and nondestructive detection. For the first time, a good linear relationship with a detection limit of 0.22 wt.% is achieved for quantitative, non‐invasive detection of water/ethanol mixtures in the field of NIR spectroscopy applications. Additionally, a super‐broadband pc‐LED with a NIR output power of 16.1mW@300 mA is fabricated, demonstrating its applications in high‐penetration imaging and anticounterfeiting. These results provide an approach to achieving NIR dual‐emission phosphor, thereby opening a new avenue for exploring ratiometric NIR spectroscopy techniques.

Optical characterization of Sb2S3 vacuum annealed films by UV–VIS–NIR spectroscopy and spectroscopic ellipsometry: Determining the refractive index and the optical constants

Using UV–VIS–NIR spectroscopy and spectroscopic ellipsometry (SE) techniques, we studied the optical characteristics of Sb2S3 thin films produced by a one-step thermal evaporation process and annealed for 2 h at various temperatures under vacuum atmosphere. The X-ray diffraction study shows that a structural transition from amorphous to polycrystalline nature occurred at vacuum annealing temperature of 200 °C. According to UV–VIS–NIR spectroscopic measurements, the Sb2S3 films showed a high absorption coefficient in the visible region (α > 104 cm−1) and a direct band gap energy that decreases from 2.00 eV to 1.63 eV as the annealing temperatures increase. Furthermore, we calculate the optical constants of the elaborated Sb2S3 films, such as refractive index n and extinction coefficient k, by fitting the ellipsometric measurements of the pseudo-refractive index < n > and the pseudo-extinction coefficient < k > . It was observed that the obtained values for n at 800 nm are 2.7, 2.9, 3.5, and 4.0 for as-deposited and annealed films, respectively, at 150, 200, and 250 °C. The dielectric properties were also determined using the Wemple DiDomenico (WDD) and Spitzer-Fan models.

Biomass and plastic co-pyrolysis for syngas production: Characterisation of Celtis mildbraedii sawdust as a potential feedstock

Celtis mildbraedii sawdust (CMS) from Ghana was characterised to investigate its suitability with polyethylene terephthalate (PET) for syngas production via co-pyrolysis. The physical and chemical properties assessed include proximate and ultimate compositions, pH value, higher heating value (HHV), and lignocellulosic composition. Also, the thermal behaviour at different heating rates (5, 10, and 20 K/min) and qualitative prediction of organic compounds of CMS were examined using thermogravimetric analysis (TG/DTG) and NIR spectroscopy techniques, respectively. Results of proximate analysis (moisture = 17.15±0.0 wt.%, ash = 1.13±0.4 wt.%, volatile matter = 68.39±0.4 wt.%, fixed carbon = 13.33±0.8 wt.%); ultimate analysis (C = 48.51 wt.%, H = 6.66 wt.%, N = 0.51 wt.%, S = 0.02 wt.%, O = 44.30 wt.%); pH values (cold phase = 7.60, hot phase = 6.30); HHV (15.37 – 18.03 MJ/kg); and lignocellulosic composition (extractives = 13.80±0.57 wt.%, hemicellulose = 21.95±3.89 wt.%, lignin = 17.35±0.35 wt.%, cellulose = 46.90±2.97 wt.%) were obtained. The maximum mass loss was 83.48% at 289.8 °C at 5 K/min. It was concluded that CMS is a highly potential biomass resource for syngas production with an empirical formula of CH1.64O0.69N0.009S0.0001.

Use of Artificial Neural Networks and NIR Spectroscopy for Non-Destructive Grape Texture Prediction.

In this article, a combination of non-destructive NIR spectroscopy and machine learning techniques was applied to predict the texture parameters and the total soluble solids content (TSS) in intact berries. The multivariate models obtained by building artificial neural networks (ANNs) and applying partial least squares (PLS) regressions showed a better prediction ability after the elimination of uninformative spectral ranges. A very good prediction was obtained for TSS and springiness (R2 0.82 and 0.72). Qualitative models were obtained for hardness and chewiness (R2 0.50 and 0.53). No satisfactory calibration model could be established between the NIR spectra and cohesiveness. Textural parameters of grape are strictly related to the berry size. Before any grape textural measurement, a time-consuming berry-sorting step is compulsory. This is the first time a complete textural analysis of intact grape berries has been performed by NIR spectroscopy without any a priori knowledge of the berry density class.

Differentiation of Organic Cocoa Beans and Conventional Ones by Using Handheld NIR Spectroscopy and Multivariate Classification Techniques.

The global market for organic cocoa beans continues to show sturdy growth. A low-cost handheld NIR spectrometer (900-1700 nm) combined with multivariate classification algorithms was used for rapid differentiation analysis of organic cocoa beans' integrity. In this research, organic and conventionally cultivated cocoa beans were collected from different locations in Ghana and scanned nondestructively with a handheld spectrometer. Different preprocessing treatments were employed. Principal component analysis (PCA) and classification analysis, RF (random forest), KNN (K-nearest neighbours), LDA (linear discriminant analysis), and PLS-DA (partial least squares-discriminant analysis) were performed comparatively to build classification models. The performance of the models was evaluated by accuracy, specificity, sensitivity, and efficiency. Second derivative preprocessing together with PLS-DA algorithm was superior to the rest of the algorithms with a classification accuracy of 100.00% in both the calibration set and prediction set. Second derivative algorithm was found to be the best preprocessing tool. The identification rates for the calibration set and prediction set were 96.15% and 98.08%, respectively, for RF, 91.35% and 92.31% for KNN, and 90.38% and 98.08% for LDA. Generally, the results showed that a handheld NIR spectrometer coupled with an appropriate multivariate algorithm could be used in situ for the differentiation of organic cocoa beans from conventional ones to ensure food integrity along the cocoa bean value chain.

Simultaneous Broadening and Enhancement of Cr3+ Photoluminescence in LiIn2 SbO6 by Chemical Unit Cosubstitution: Night-Vision and Near-Infrared Spectroscopy Detection Applications.

Near-infrared (NIR)-emitting phosphor materials have been extensively developed for optoelectronic and biomedical applications. Although Cr3+ -activated phosphors have been widely reported, it is challenging to achieve ultra-broad and tunable NIR emission. Here, a new ultra-broadband NIR-emitting LiIn2 SbO6 :Cr3+ phosphor with emission peak at 965 nm and a full-width at half maximum of 217 nm is reported. Controllable emission tuning from 965 to 892 nm is achieved by chemical unit cosubstitution of [Zn2+ -Zn2+ ] for [Li+ -In3+ ], which can be ascribed to the upshift of 4 T2g energy level due to the strengthened crystal field. Moreover, the emission is greatly enhanced, and the FWHM reaches 235 nm. The as-prepared luminescent tunable NIR-emitting phosphors have demonstrated the potential in night-vision and NIR spectroscopy techniques. This work proves the feasibility of chemical unit cosubstitution strategy in emission tuning of Cr3+ -doped phosphors, which can stimulate further studies on the emission-tunable NIR-emitting phosphor materials.

Simultaneous Broadening and Enhancement of Cr3+Photoluminescence in LiIn2SbO6by Chemical Unit Cosubstitution: Night‐Vision and Near‐Infrared Spectroscopy Detection Applications

AbstractNear‐infrared (NIR)‐emitting phosphor materials have been extensively developed for optoelectronic and biomedical applications. Although Cr3+‐activated phosphors have been widely reported, it is challenging to achieve ultra‐broad and tunable NIR emission. Here, a new ultra‐broadband NIR‐emitting LiIn2SbO6:Cr3+phosphor with emission peak at 965 nm and a full‐width at half maximum of 217 nm is reported. Controllable emission tuning from 965 to 892 nm is achieved by chemical unit cosubstitution of [Zn2+–Zn2+] for [Li+–In3+], which can be ascribed to the upshift of4T2genergy level due to the strengthened crystal field. Moreover, the emission is greatly enhanced, and the FWHM reaches 235 nm. The as‐prepared luminescent tunable NIR‐emitting phosphors have demonstrated the potential in night‐vision and NIR spectroscopy techniques. This work proves the feasibility of chemical unit cosubstitution strategy in emission tuning of Cr3+‐doped phosphors, which can stimulate further studies on the emission‐tunable NIR‐emitting phosphor materials.

Hybrid Spectral-IRDx: Near-IR and Ultrasound Attenuation System for Differentiating Breast Cancer From Adjacent Normal Tissue.

While performing surgical excision for breast cancer (lumpectomy), it is important to ensure a clear margin of normal tissue around the cancer to achieve complete resection. The current standard is histopathology; however, it is time-consuming and labour-intensive requiring skilled personnel. We describe a Hybrid Spectral-IRDx - a combination of the previously reported Spectral-IRDx tool with multimodal ultrasound and NIR spectroscopy techniques. We show how this portable, cost-effective, minimal-contact tool could provide rapid diagnosis of cancer using formalin-fixed (FF) and deparaffinized (DP) breast biopsy tissues. Using this new tool, measurements were performed on cancerous/fibroadenoma and its adjacent normal tissues from the same patients (N = 14). The acoustic attenuation coefficient (α) and reduced scattering coefficient (µ's) (at 850, 940, and 1060 nm) for the cancerous/fibroadenoma tissues were reported to be higher compared to adjacent normal tissues, a basis of delineation. Comparing FF cancerous and adjacent normal tissue, the difference in µ's at 850 nm and 940 nm were statistically significant (p = 3.17e-2 and 7.94e-3 respectively). The difference in α between the cancerous and adjacent normal tissues for DP and FF tissues were also statistically significant (p = 2.85e-2 and 7.94e-3 respectively). Combining multimodal parameters α and µ's (at 940 nm) show highest statistical significance (p = 6.72e-4) between FF cancerous/fibroadenoma and adjacent normal tissues. We show that Hybrid Spectral-IRDx can accurately delineate between cancerous and adjacent normal breast biopsy tissue. The results obtained establish the proof-of-principle and large-scale testing of this multimodal breast cancer diagnostic platform for core biopsy diagnosis.

Use of composite samples and NIR spectroscopy to detect changes in SOC contents

Depending on the land management, soils can behave as sources or sinks of carbon. Thus, monitoring the changes in the SOC (ΔSOC) is of significance. However, this monitoring is often challenging because the value of ΔSOC is typically small in comparison with the spatial variability, and a large sample size is required, which may incur prohibitive costs. In the absence of the necessary sample size, hypothesis testing may be performed under deficient statistical conditions, which may result in misleading conclusions. In this study, we compared several cost-effective approaches to solve the aforementioned problems: i) using composites, as the number of samples to be analysed is smaller, and the costs using a reference method do not represent a substantial amount; ii) using NIR spectroscopy, which is a fast and cheap technique, and allows the analysis of massive number of samples; and iii) the combination of these approaches. In particular, the approaches were compared by evaluating the corrected minimum detectable difference (MDDC), which corresponds to the MDD after the errors of the methods have been accounted for. Bulking into the composites reduced the analysis costs, and the variance was reduced as the sample size reduced. However, a larger penalisation of the random measurement errors increased the MDDC. Biased predictions were obtained when an NIR spectroscopy based national scale model was used to predict the SOC at the local scale, resulting in extremely high values of the MDDC. By using composites to adapt that model to the local conditions through spiking with the extra-weighting technique, the bias was considerably reduced, along with the MDDC. In addition to their role as a spiking subset, the composites exhibited a desirable effect when combined with the NIR spectroscopy technique, since they allowed to find the model that was predicting SOC contents with the lowest bias, and hence measuring the ΔSOC with the highest accuracy. This analysis was highly specific and cannot be applied using any other spiking subsets, and allowed to identify a model that obtained an MDDC smaller than that obtained using only the composites. Therefore, the combination of the composites and NIR spectroscopy can be used to monitor ΔSOC since it is inexpensive, accurate and robust, and the spatial distribution of the SOC contents is not lost. Moreover, the cost efficiency of this combined approach probably improves along successive rounds in the monitoring process.

Investigation of structural, optical, electrical and mechanical properties of transparent conducting ‘Ag’ electrodes

The high flexibility and excellent optoelectrical properties of thin metal films hold great potential for their use as transparent conducting electrodes in large-area flexible optoelectronic devices. Thermally evaporated transparent conducting silver (Ag) thin films (48–75 nm) are characterized using X-ray diffraction, scanning electron microscopy, scanning probe microscopy, UV–Vis–NIR spectroscopy, Hall effect, Nanoindentation and Kelvin probe techniques. Significant textured growth along (111) crystal plane direction is observed. The film with least thickness exhibits interesting wrinkled surface morphology. Surface roughness is observed to increase with film thickness. High transmittance and considerable transparency are observed in UV and NIR regions, respectively. Surface work function (4.7–4.9 eV) is determined from Kelvin probe measurements. Nanoindentation studies indicate reduced hardness with increasing film thickness. These experiments suggest that Ag film of thickness 63 nm shows better optical and electrical properties and may be a potential transparent conducting supplement for specific applications like transparent electrodes and interconnects.

Development of near‐infrared online grading device for long jujube

AbstractAimsSoluble solids content (SSC) is an essential indicator for evaluating the internal quality of fresh jujube, which can be used to classify the quality grade of fresh jujube.MethodsIn this study, SSC was determined as the research index of the internal quality in Lingwu long jujube to classify their quality grade. The online rapid nondestructive grading device for jujube quality was designed, including the design of the hardware system and a software system. The performance of the device was evaluated by additional samples.ResultsBy grading external samples, the correct rate of classification of SSC was 86.7% (the first, second, and third grade were 100, 85.7, and 71.4%, respectively), and the residual predictive deviation (RPD) value of optimal model was 2.8 (&gt;2.5).ConclusionsThe acquired results revealed that, the device could be used in production.Practical ApplicationsIn this study, we developed an online nondestructive sugar grading device for fresh jujubes, including the design of hardware systems, the development of software systems. NIR spectroscopy technique coupled with chemometric selection method of characteristic variables were used to build a prediction model for SSC in fresh jujubes. In addition, the model and device were evaluated by external samples, the accuracy of the result was high, and it could be used for the grading of the sugar content of fresh jujube and could potentially extend the quality parameter grading applied to other fruit. This study provided the basis for the development of nondestructive rapid grading system related to the quality of fruit and vegetable.

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.

Intersubband Absorption in Gallium Arsenide Implanted with Silicon Negative Ions

Gallium arsenide (GaAs) implanted with silicon forming intersubband of SiGaAs is a promising material for making novel electronic and optoelectronic devices. This paper is focused on finding optimum fluence condition for formation of intersubband of SiGaAs in GaAs sample after implantation with 50[Formula: see text]keV silicon negative ions with fluences varying between [Formula: see text] and [Formula: see text] ions cm[Formula: see text]. The GaAs samples were investigated using X-ray photoelectron spectroscopy (XPS), UV-Vis.-NIR spectroscopy and X-ray diffraction (XRD) techniques. The X-ray photoelectron spectra for unimplanted sample showed peaks at binding energy of 18.74[Formula: see text]eV and 40.74[Formula: see text]eV indicating Ga3d and As3d core level, whereas the corresponding core level peaks for implanted sample were observed at binding energy of 19.25[Formula: see text]eV and 41.32[Formula: see text]eV. The shift in Ga3d and As3d core levels towards higher binding energy side in the implanted sample with respect to unimplanted sample were indicative of change in chemical state environment of Ga–As bond. The relative atomic percentage concentration of elemental composition measured using casa XPS software showed change in As/Ga ratio from 0.89 for unimplanted sample to 1.13 for sample implanted with the fluence of [Formula: see text] ion cm[Formula: see text]. The UV-Vis-NIR spectra showed absorption band between 1.365[Formula: see text]eV and 1.375[Formula: see text]eV due to the formation of intersubband of SiGaAs for fluences greater than [Formula: see text] ion cm[Formula: see text]. The GaAs crystallite size calculated using Brus formula was found to vary between 162[Formula: see text]nm and 540[Formula: see text]nm, respectively. The XRD spectra showed the presence of Bragg’s peak at 53.98∘ indicating (311) silicon reflection. The silicon crystallite size determined from full width at half maxima (FWHM) of (311) XRD peak was found to vary between 110[Formula: see text]nm and 161[Formula: see text]nm, respectively.

PH Prediction of Perlis Sunshine Mango Using NIR Spectrometer

To evaluate the various internal quality attributes of fruits, NIR spectroscopy techniques are undoubtedly quick and non-destructive tools. Acidity (pH) is one of the main quality attributes in mango fruits. Generally, it is being predicted in destructive way. The aim of this research was to develop calibration model and prediction of pH in Perlis Sunshine mangoes using NIR spectrometer. The transmission spectra of Sunshine mangoes were acquired in the wavelength range from 300 to 1000 nm. The effects of different types of pre-processing methods and spectra treatments, such as baseline correction, multiplicative scatter correction (MSC), Savitzky-Golay (SG) smoothing, second order derivative (SG) and normalisation were analyzed. The prediction models were developed by partial least squares (PLS) regression. The coefficient of determination (R2) of pH was 0.928 and the standard error of cross-validation (SECV) was 0.153. The results indicated that by using the NIR measurement system, in the suitable spectral range, it is possible to predict the pH of mango fruits by non-destructively.