Diffuse Reflectance Mode Research Articles

Fabrication of phosphorus-doped graphitic carbonitride towards the photodegradation of ciprofloxacin and sulfamethoxazole

AbstractHerein, we present the application of a phosphorus-doped graphitic carbon nitride (P-g-C3N4) for the photodegradation of ciprofloxacin and sulfamethoxazole in water. The photocatalyst was prepared from doping g-C3N4 with phosphorus using different compositions of phosphoric acid (2%, 4%, and 6% w/v). The resultant photocatalysts (2%P-g-C3N4, 4%P-g-C3N4, and 6%P-g-C3N4) were characterized using Fourier transform infrared (FTIR), X-ray diffraction spectroscopy (XRD), scanning electron microscopy–energy-dispersive X-ray (SEM–EDX), and ultraviolet–visible diffuse reflectance mode spectrophotometry (UV–Vis DRS). Photocatalytic degradation studies of the targeted pollutants were performed and monitored using UV–Vis and liquid chromatography coupled with mass spectroscopy (LC–MS). The UV–Vis DRS showed a shift from 2.70 to 2.48 eV in the band gap after doping g-C3N4 with phosphorus. The degradation of sulfamethoxazole by P-g-C3N4 was found to be significantly higher (70%) as compared to g-C3N4 (50%). On the other hand, the removal of ciprofloxacin was found to be 60% for P-g-C3N4, while 50% was found to be the removal efficiency of g-C3N4. The high removal efficiencies were associated with the generated electron holes together with the hydroxyl radicals which played a predominant role in the successful degradation of ciprofloxacin and sulfamethoxazole. Recyclability studies showed that the photocatalyst obtained a high photocatalytic degradation of 65% toward sulfamethoxazole after five cycles. Degradation by-products such as anthralin acid (m/z 307) for ciprofloxacin and monohydroxylated I10 (m/z 269) for sulfamethoxazole were detected using LC–MS. Therefore, P-g-C3N4 serves as a promising photocatalyst for the effective remediation of wastewater generated by pharmaceutical industries.

Flash combustion synthesis using two different fuels and characterization of LiF-doped TiO2 for the photocatalytic applications

The flash combustion method was used to prepare LiF-doped TiO2 photocatalysts materials using glycine or urea as a fuel with different weight percentage of LiF. The synthesized powders have been characterized by thermogravimetric analysis (TG), scanning electron microscope (SEM) with energy dispersive spectrometer (EDX) analyzer, the specific surface area measurement was performed by BET. The crystallization and the phase transformation anatase-rutile for the powders have been verified by XRD. SEM micrographs for these powders shows the presence of nanoparticles. To investigate the optical band gap of the synthesized samples, UV–Vis spectroscopy was conducted using the diffuse reflectance mode (DRS). The O2−/F− substitution and the presence of Ti3+ centers was confirmed by electron paramagnetic resonance (EPR) analysis. The photocatalytic activity of the TiO2-xLiF powders were evaluated through the photocatalytic degradation of Methylene blue (MB) in water under UV–visible light exposure. The results indicated that during the flash combustion synthesis, the nature of the fuel and the percentage of the doping element led to the presence of different polymorphs of TiO2 which influences the photocatalytic efficiency attributed to the synergistic effect between the two phases (anatase and rutile). The LiF-doped TiO2 powders synthesized by flash combustion in both cases (by using glycine or urea) showed high performance in MB degradation compared to commercial TiO2 and undoped synthesized TiO2 powders, with an optimal degradation of 99 % achieved with 2 wt % LiF-doped TiO2 using glycine as a fuel and after 6 h of UV–Vis irradiation.

Rapid multi-indicator quality evaluation of Eucommia ulmoides by near-infrared spectroscopy combined with chemometrics

ObjectiveUsing near-infrared spectroscopy and chemometrics, to establish a method for determination of multiple indicators in Eucommia ulmoides (EU) to achieve its rapid quality evaluation. Method83 batches of EU decoction slices were collected, and the content of pinoresinol diglucoside, chlorogenic acid and geniposidic acid in them was determined by high-performance liquid chromatography, the content of total flavonoids was determined by UV–Vis spectrophotometry, while the antioxidant activity of EU was measured by methods of DPPH, ABTS and FRAP, respectively. The near-infrared spectra of EU were acquired in diffuse reflectance mode, which were subjected to multivariate statistical analysis in relation with the above measured values. In order to achieve good model performance, various methods for spectra pretreatment and wavelength selection were explored. Especially, with the help of four wavelength selection methods based on swarm intelligence optimization, such as genetic algorithm (GA), gray wolf algorithm (GWO), improved global flower pollination algorithm (mgFPA), and improved sine and cosine optimization algorithm (ISCA), the partial least squares regression models were improved prominently. The model quality was evaluated by calculating the coefficient of determination (R2), root mean square error (RMSE) and residual prediction deviation (RPD) in the sets of calibration and prediction. ResultsRegardless of which indicator in EU, the model performance was fairly good, especially after the wavelength selection by GA and other three methods, where R2 > 0.9, RPD > 3 in both calibration and prediction, indicating that the models had good prediction accuracy. Based on the overall algorithmic efficiency and model results, we have the following ranking: GA > GWO > mgFPA > ISCA. ConclusionThe present models provide a novel method for rapid and comprehensive quality evaluation of EU, which may be of great significance for quality evaluation and quality control of EU.

Self-powered and broadband CuSCN/Si heterojunction photodetector for multi-color imaging based on diffuse reflection mode

Copper thiocyanate (CuSCN) has been widely used in photodetectors (PDs). However, the reported CuSCN-based PDs are suffered from narrow operating wavelength range and relatively low photodetection performance. Here, we fabricate an CuSCN/Si heterojunction PD by a simple low-temperature solution spin-coating method achieving excellent performance. Our designed CuSCN/Si PD exhibits a broadband response range covering ultraviolet–visible-infrared, a high detectivity of 2.26 × 1012 Jones coming from an ultralow dark current of 23 pA, and a decent responsivity of 11 mA W−1, a high linear dynamic range of 122 dB, and short response time of 25/150 μ (rise and decay time). Moreover, we demonstrate multi-color imaging across the wide wavelength range, indicating the CuSCN/Si PD has a promising potential in the imaging field. This work may pave the way for fabricating low-cost, nontoxicity, and high-performance CuSCN-based PD and broadening its applications.

Synthesis, Spectroscopic, and Antibacterial Characterizations of Cadmium-Based Nanoparticles.

In the current study, the co-precipitation technique was employed for the synthesis of Cadmium oxide (CdO) and Copper‒doped Cadmium oxide (Cu‒CdO) nanoparticles. The synthesized samples were subjected to powder X-Ray diffraction (P-XRD), Field emission scanning electron microscopy (FE-SEM), Energy-dispersive X-ray (EDX), Fourier transforms Infrared (FT-IR), UV-Vis spectroscopy, photoluminescence (PL), laser-induced fluorescence spectroscopy and antibacterial investigations. According to the P-XRD analysis, both the samples were simple cubic in structure and have average grain sizes of 54 and 28nm, respectively. FE-SEM was deployed to explore the surface textures of the samples. EDX technique was used to look at the elemental compositions of the samples. The technique of FT-IR was employed to identify the vibrational modes. UV-Vis spectra in diffuse reflectance mode were obtained and the optical bandgaps of the CdO and Cu‒CdO samples were obtained as 4.52eV and 2.83eV, respectively. The photoluminescence studies were conducted at an excitation wavelength of 300nm and emission peaks were red-shifted in both samples. Fluorescence spectroscopy was applied to explore the lifetimes of synthesized nanoparticles. The technique of Agar-well diffusion was applied to assess the antibacterial performance of the generated nanoparticles against Micrococcus Luteus (gram-positive) and Escherichia coli (gram-negative) bacterium at variable concentrations. Both samples in the current study are significantly effective against both bacterial strains.

Bio-mediated synthesis of CuO nano bundles from Gomutra (cow urine): Synthesis, characterization, photodegradation of the malachite green dye and SBH mediated reduction of 4-nitrophenol

We synthesized CuO nano bundles-like structures from Gomutra (cow urine). Urea and uric acid, which are present in the gomutra, act as reducing and capping agents, resulting in unique CuO nano bundles-like structure formation. No such morphological formation was observed from synthetic urea. X-ray diffraction (XRD), Scanning electron microscopy (SEM), Energy dispersive X-ray analysis (EDAX), UV–Visible, Fourier transforms infrared (FT-IR), Brunauer -Emmett-Teller (BET), and (photoluminescence) PL-Spectrofluorometer were used to analyze bio-mediated synthesized CuO nano bundle-like structures. From XRD analysis, the CuO nano bundle exhibits a monoclinic system with an average crystalline size of 15.76 nm. SEM results signified nano bacillus-like structures, resembling nano bundle-like designs in aggregate. EDAX anticipated the presence of only Cu and O atoms. FT-IR validates the existence of Cu and O bonds. The band gap was calculated using the DRS [Diffused reflectance mode] technique, and the value was found to be 1.29 eV. The BET and BJH [Barret-Joyner-Halenda] analysis estimated the surface area and pore size to be 28.24 Cm3/g and 11.5 nm. Intense emission peaks are seen at 465 nm from the PL spectrometer. Electron-hole transfer behavior in CuO nano bundles stemmed from Electrochemical impedance spectroscopy (EIS technique). The photocatalytic performance of malachite Green was examined in an aqueous medium, and degradation efficiency was found to be 98.2% in 70 min [min] with a rate constant of 0.0303 min−1. The catalyst ensured good activity for up to five cycles and was also found to be stable from SEM and XRD results. In addition, intermediated products were analyzed by the LC-MS, Electron Spin Resonance (ESR), and TOC [Total organic carbon] techniques. Required supporting evidence was elucidated in the Schematic pathway. CuO nano bundles also exhibited good catalytic behavior for reducing 4-nitrophenol in the ultrasonication method at room temperature with the whole reduction of nitro groups was proven by UV– Visible, FT-IR, and LC-MS technique, and the rate constant was found to be 0.3142 min−1. The present result clearly highlights that CuO nano bundles synthesized using gomutra can play a critical role in removing hazardous dyes from effluents of textile and dye industries. Further expanding the application of these nano bundles will promote an effective complementary and alternative strategy for treating refractory pollutants from wastewater.

Diffuse reflectance infrared spectroscopy of adsorbates in liquid phase

Infrared spectroscopy is widely used to analyse the surface of solid materials central to modern chemical processes. For liquid phase experiments, the attenuated total reflection mode (ATR-IR) requires the use of waveguides that can limit a broader applicability of the technique for catalysis studies. Here, we demonstrate that high quality spectra of the solid-liquid interface can be collected in diffuse reflectance mode (DRIFTS) thus opening future applications of infrared spectroscopy.

Multifunctional microcapsules based on ZnO and n-octadecane: From thermal energy storage to photocatalytic activity

Energy management is one of the most important issues to be addressed in the near future in many fields, one of which is buildings. In this sense, new phase change materials (PCM) are being widely studied for storing energy. Encapsulating PCM is a good way to incorporate these materials into different applications in which energy storage is useful. In this study, microcapsules based on ZnO containing n-octadecane as a phase change material were synthesized and characterized with regard to their structural, morphological and optical properties according to several synthesis parameters, such as the proportion of precursors, stirring rate and ageing time. The microcapsules were characterized using x-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, and UV–Vis spectroscopy in diffuse reflectance mode. The presence of n-octadecane inside the capsules was confirmed. Their thermal behaviour was analysed by means of differential scanning calorimetry. Heating/cooling cycles were performed, after which the microcapsules presented good stability. Furthermore, the encapsulation efficiency was estimated from melting and crystallization enthalpy values, reaching a value of 23.1%. Moreover, the isobaric specific heat of the microcapsules is higher than that of ZnO, which means that substituting ZnO with microcapsules in buildings leads to an important increase in the amount of sensible heat stored. Finally, the photocatalytic activity of the microcapsules was analysed by studying the photodegradation of Crystal Violet dye. The degradation rate increased when the microcapsules were present, so the photocatalytic activity of the microcapsules was confirmed under UV and visible irradiation, which is of interest because they can be used to remove organic pollutants from buildings.

A design of laser triangulation system with combined diffuse and specular reflection modes for dull and shiny surface measurements

Conventional laser triangulations are designed to measure the depth or height on a dull or rough surface. This can be done by projecting a light perpendicularly to the surface and capturing the spot of the diffuse reflection which is scattered from the surface. However, for a shiny or smooth surface, the specular reflection dominates, and it is difficult to detect diffuse reflection. We may modify the system setting to capture the specular reflection, with the cost of losing the diffuse reflection information. In this article, we proposed a design of dual diffuse and specular reflection mode of laser triangulation. The advantage is that there is no need to repeat alignment and calibration processes when we change the measuring mode, so we can easily select the measuring mode that is suitable for each surface. We have described the system setting and the calibration results where we can achieve the resolution of micrometre for both measuring modes.

Application of miniaturized near-infrared spectrometer for indirectly determining flesh thickness of intact polished coconut

Consumers prefer polished coconut with a certain flesh thickness that is associated with maturity. At present, sorting mature polished coconuts is conducted manually. A portable near-infrared spectrometer in the range 900–1700 nm was adopted to determine the flesh thickness non-destructively. Averaged near-infrared spectra scanned in diffuse reflectance mode in three sections of the coconut bottom were used to create the predictive model using partial least squares regression. Samples from two harvests of the polished coconut were used. The first harvest samples were used to build and validate the model, and the second harvest samples were used to test the model performance independently. The final validated model, based on the samples from two harvests, provided acceptable performance, with values for the correlation coefficient, standard error of cross-validation, and bias of 0.89, 0.68 mm, and − 0.006 mm, respectively. The near-infrared absorbance contained only shell spectral information that was confirmed by testing the penetration depth. The highest loading weight of the best model corresponded with the lignin absorption peak.

Rootstock’s and Cover-Crops’ Influence on Grape: A NIR-Based ANN Classification Model

In this study, a multivariate analysis combined with near-infrared (NIR) spectroscopy was employed to classify intact grape berries based on the rootstock x cover crops combination. NIR spectra were collected in diffuse reflection mode using a TANGO FT-NIR spectrometer (Bruker, Germany) with 8 cm−1 resolution and 64 scans in the wave number range of 4000–10,000 cm−1. The chemometric analyses were performed with the statistical software R version 4.2.0 (2022-04-22). Elimination of uninformative variables was accomplished with a PCA and a genetic algorithm (GA). The discrimination performance of a linear discriminant analysis (LDA) model was not enhanced with either a PCA- or a GA-based selection. A multiclass classification model was built with an artificial neural network (ANN). The best fit multiclass classification model on test data was obtained with the GA-ANN model that gave a classification accuracy of close to 80% for samples belonging to the four classes. These results demonstrate that NIR spectroscopy could be used as a rapid method for the classification of berries based on their rootstock x cover-crops combination.

Reliable classification of nutmeg fruits from some geographical origins using SWNIR spectroscopy associated with PLS-DA and SVM methods: Case Study in Aceh Province, Indonesia

Essential oils of nutmeg (Myristica fragrans) can have different qualities due to the soil and industrial process, as Indonesia’s main nutmeg production areas are enormous, especially in Aceh province. The lack of information on detecting chemical constituents and classifying nutmeg from Aceh province makes the price of nutmeg from Aceh unable to compete. Therefore, this study aims to reliably classify nutmeg fruits of some geographical origins in Aceh Province using shortwave near-infrared (SWNIR) spectroscopy associated with partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM). The SWNIR used in this study has a wavelength of 381 to 1065 nm at a resolution of 3 nm and a diffuse reflectance mode. The fruit comes from four geographical areas of origin in the province of Aceh. A total of forty SWNIR spectral data were further classified using two algorithms, namely PLS-DA and SVM. The results show that SWNIR can correctly classify nutmeg from some sub-districts in Aceh province with the help of the PLS-DA and SVM algorithms. From this study, the following SVM algorithm is recommended to be used to classify nutmeg from the province of Aceh with an outstanding level of precision.

Development of a Portable Near-Infrared Spectroscopy Tool for Detecting Freshness of Commercial Packaged Pork.

Real-time monitoring of meat quality requires fast, accurate, low-cost, and non-destructive analytical methods that can be used throughout the entire production chain, including the packaged product. The aim of this work was to evaluate the potential of a portable near-infrared (NIR) spectroscopy tool for the on-site detection of freshness of pork loin fillets in modified atmosphere packaging (MAP) stored on display counters. Pork loin slices were sealed in MAP trays under two proportions of O2/CO2/N2: High-Ox-MAP (30/40/30) and Low-Ox-MAP (5/20/75). Changes in pH, color, thiobarbituric acid reactive substances (TBARS), Warner−Bratzler shear force (WBSF), and microbiology (total viable counts, Enteriobacteriaceae, and lactic acid bacteria) were monitored over 15 days post-mortem at 4 °C. VIS-NIR spectra were collected from pork fillets before (through the film cover) and after opening the trays (directly on the meat surface) with a portable LABSPEC 5000 NIR system in diffuse reflectance mode (350−2500 nm). Quantitative NIR models by partial least squares regression (PLSR) showed a promising prediction ability for meat color (L*, a*, C*, and h*) and microbiological variables (R2VAL > 0.72 and RPDVAL > 2). In addition, qualitative models using PLS discriminant analysis obtained good accuracy (over 90%) for classifying pork samples as fresh (acceptable for consumption) or spoiled (not acceptable) based on their microbiological counts. VIS-NIR spectroscopy allows rapid evaluation of product quality and shelf life and could be used for on-site control of pork quality.

A comparison of benchtop and micro NIR spectrometers for infant milk formula powder storage time discrimination and particle size prediction using chemometrics and denoising methods

This study compared benchtop and micro NIR spectrometers in diffuse reflection mode (1158–2169 nm) to (i) discriminate infant milk formula (IMF) powder samples (n = 500) by storage time (0–12 months) and to (ii) predict IMF powder particle size parameters. Reference particle size parameters were determined using laser-light-scattering. Fast Fourier transform (FFT) and wavelet transform (WT) denoising methods were employed on micro NIR spectra to remove noise and enhance spectral features. Partial least square discriminant analysis (PLS-DA) and partial least squares regression (PLSR) modelling approaches were used to discriminate IMF by storage time and predict powder particle size, respectively. The models developed using the micro NIR denoised spectra had correct identifications (CI p ) of 89–100% for IMF storage time discrimination and RPDPs of 2.29–2.98 for particle size prediction, which were comparable to the model performances achieved using the benchtop NIR spectra (CI p values of 81.3–100% for IMF storage time discrimination and RPDPs of 2.08–3.07 for particle size prediction). This study demonstrated that the potential of micro NIR spectroscopy combined with chemometrics and denoising methods as a suitable process analytical technology (PAT) tool for IMF powder storage time discrimination and particle size prediction along the IMF distribution chain from production to consumer. • Benchtop and micro NIR models can assess IMF powder storage time and particle size. • IMF powder storage time was discriminated using PLS-DA modelling. • IMF powder particle size was predicted using PLSR modelling. • FFT and WT denoising methods are suitable to remove micro NIR spectral noise. • Micro NIR models had overall better performance than benchtop NIR models.

Real-time measuring energy characteristics of cane bagasse using NIR spectroscopy

Online measurement of moisture content (MC) and higher heating value (HHV) is desired for supporting the thermal conversion process in power plants. The main objective of this study was to develop a reliable and accurate method for online measuring of the HHV and MC of dried and as received sugarcane bagasse, respectively, using near-infrared (NIR) spectroscopy. Simulation of the conveyor belt in power plants and online energy quality analysis of bagasse for combustion process were designed. One hundred samples of bagasse were collected from different sugar mills at various locations of large piles of bagasse stored in both indoor and outdoor buildings. A long-wave spectrometer with a wavelength range of 860–1755 nm was used for scanning using diffuse reflection mode. The models were developed by partial least squares (PLS) regression using spectral sets obtained from the raw spectra, the preprocessed full spectra from the traditional approach, and the preprocessed spectra from the multi-block technique. The multi-blocks of the spectral pre-treatment technique provided effective models for both MC and HHV prediction. The best model for MC had a coefficient of determination of prediction (R2p) and the root mean square error of prediction (RMSEP) of 0.90 and 3.9% wb respectively. In the meantime, the best model for HHV had R2p and the RMSEP of 0.71 and 188.7 J g−1. This research demonstrated that NIR spectroscopy provides a feasible and reliable method for online analysis of MC and could be used for screening of HHV of bagasse.

Diffuse reflectance mid infra-red spectroscopy combined with machine learning algorithms can differentiate spectral signatures in shallow and deeper soils for the prediction of pH and organic matter content

Precision and sustainable agriculture requires information about soil pH and organic matter (OM) content at higher spatial and temporal scales than current agronomic sampling and analytical methods allow. This study examined the accuracy of spectral models using high throughput screening (HTS) in diffuse reflectance mode in mid Infra-red (MIR)/DRIFT combined with machine learning algorithms to predict soil pH(CaCl2) and %OM in shallow and deeper topsoils compared to laboratory methods. Models were developed from an archive of samples taken on a 4 km2 grid from the northern half of Ireland (Terra Soil project), which includes 18,859 samples (9,396 shallow + 9,463 deeper). The application of Cubist models showed that for different depths there are minor different spectral group associations with pH and %OM values. These differences resulted in a loss of accuracy in the extrapolation of the topsoil model to predict values from deeper topsoils or vice versa. Therefore we recommend the use of samples from both depths to build a calibration model.The proposed methodology was able to determine %OM and pH using a unique multivariate regression model for both depths, with RMSEP values of 1.12 and 0.89 %; RPIQ values of 42.34 and 38.48; R2val of 0.9989 and 0.9993 for %OM determinations in shallow and deeper topsoils, respectively. For pH determinations the RMSEP values obtained were 0.25 and 0.34; RPIQ values of 6.04 and 4.94; R2val 0.9385 and 0.8954. Both regression models are classified as excellent predictions models, yielding RPIQ values >4.05 for shallow and deeper topsoils. The results demonstrated the high potential of HTS-DRIFT combined with machine learning algorithms as a rapid, accurate, and cost-effective method to build large soil spectral libraries, displaying predicted results similar to two separate soil laboratory methods (pH and LOI).

Controlled assembly of heterogeneous aggregates of clay, iron hydr(oxydes) and polysaccharide: Effects of preparation conditions

The preparation of well-defined organo-mineral assemblies under controlled conditions is required to improve our understanding of the formation and surface reactivity of micrometric aggregates, ubiquitous in soils and continental aquatic media. We aim at investigating the building of organo-mineral assemblies with a specific focus on the assembly mode and its consequence on the final properties of the micrometric aggregates. In this work, the preparation and detailed characterization of clay-size aggregates composed of a clay mineral (illite), organic polymer (Dextran polysaccharide) and iron (hydr)oxide are reported, with a focus on the structural organization of the generated aggregates. A step-by-step strategy was developed, and three sets of clay-size composites were prepared with illite particles as a starting material. In two first steps, two distinct sets of two-component composites were obtained according to different procedures. Illite‑iron (hydr)oxide composites were obtained by alkaline hydrolysis of iron in the presence of illite particles, and illite-Dextran aggregates were obtained through the addition of Dextran polysaccharide to an illite suspension. In a third step, three-component micro-aggregates were obtained by subsequent addition of Dextran to suspensions containing the formed illite‑iron (hydr)oxide composite. The so-prepared 2- and 3- component aggregates were investigated by electrophoresis, electron microscopy, X-ray absorption and FTIR spectroscopies. For materials containing Dextran, electrophoretic mobility measurements evidenced variations of surface charge, combined with an increase of aggregate size highlighted by dynamic light scattering. Electron microscopy and EXAFS at iron K-edge evidenced the precipitation of nanoparticles of iron (hydr)oxide onto clay mineral surfaces. FTIR data in transmission and diffuse reflectance modes supported not only the adsorption of Dextran but also the preferential localization of Dextran at the external surfaces of the aggregates. All in all, data collected on the two- and three-component materials demonstrated that the presence of iron (hydr)oxide nanoparticles on the surface of illite strongly modified the organization of organic and mineral constituents.

Polyvinylpyrrolidone capped electrospun CH3NH3PbCl3 perovskite film as the electron transport layer in perovskite solar cell application

Due to the inherent moisture instability problem of hybrid lead halide perovskites, polymer additives have to turn out to be a significant research area to enhance the moisture stability of these materials. It has been found that polymer engineering on the absorber layer of solar cells significantly improves chemical stability and overall device performance. This work reports the fabrication of pristine and polyvinylpyrrolidone (PVP) polymer capped methylammonium lead chloride (CH3NH3PbCl3) perovskite film via the electrospinning method. A structural study using an X-ray diffractometer shows a sharp fall in average crystallite size from 66.05 nm to 39.69 nm when PVP is used in the synthesis procedure. A similar trend is also seen in the microscopic analysis, which depicts that the particle size has decreased for PVP added CH3NH3PbCl3 perovskite film in comparison to CH3NH3PbCl3 pristine film. The surface coverage and uniformity of the film is much more in the presence of PVP. It has been noted from energy dispersive X-ray analysis that the oxygen content is ∼16% more in the pure film, i.e. PVP hinders the effect of moisture in perovskite film, which is the prime objective of this work. Moreover, the optical properties have been analyzed using diffuse reflectance mode of UV–Vis-NIR spectroscope. Finally, the use of CH3NH3PbCl3 as the electron transport layer has been demonstrated in Glass/FTO/CH3NH3PbCl3/CH3NH3SnI3/Spiro-OMeTAD/Au structured perovskite solar cell using the SCAPS-1D simulator. The above-mentioned cell exhibits a power conversion efficiency (PCE) of 21.65%, fill factor (FF) of 72.21%, 32.44 mA/cm2 of short circuit current density (Jsc), and 0.924 V open-circuit voltage (Voc).

Correlation between surface roughness and spectral features in IR-reflection spectroscopy

Modifications of IR spectral features were reported in the literature when surfaces with diverse morphologies were analysed. In this study, five surfaces at different average roughness (Sa) were created on a massive slice of malachite with the final aim to investigate possible variations of spectral features collected through non-contact infrared reflection spectroscopy. Modifications were investigated as a function of Sa, with five frequency intervals being considered. The spectral acquisition was carried out by two portable spectrometers equipped with specific non-invasive optical heads, operating in External Reflection (ER) and Diffuse Reflection (DR) modes, respectively. A comparison study of the collected spectral profiles is proposed in this work. The analysis of spectra produced by surfaces at different roughness allowed for evaluating the effectiveness of each device in the different spectral ranges. The ER spectra were generally more resolved and cleaner compared to the DR ones. The ER module was able to return spectra whose features - both specular and diffuse - consistently follow the variation of Sa in the investigated spectral ranges. A lack of sensitivity was instead registered when working in DR mode, especially in the frequency intervals where the contribution of the diffuse component dominates the spectra.

Avocado dehydration negatively affects the performance of visible and near-infrared spectroscopy models for dry matter prediction

This study aims to test the hypothesis that skin dehydration can cause the development of cork-like layers in the avocado fruit skin which may negatively affect Vis-NIR spectroscopy. To test this, dehydration treatment was applied on avocado fruit by storing them at low relative humidity (RH) during ripening treatment. Furthermore, to demonstrate that the hypothesis was not only valid for a single instrument and in general valid for any type of Vis-NIR instrument the avocados were also measured with two different spectrometers i.e., lab-based, and hand-held. Since the two instruments have two different measurement geometries i.e., diffuse reflection and interaction, the study also tests which geometry was best for the measurement of DMC in dehydrated avocados. The results showed that the dehydration of avocado fruit negatively affects the performance of Vis-NIR calibrations compared to the non-dehydrated fruit. The root mean squared error of cross-validation (RMSEcv) on internal test set for dehydrated and non-dehydrated fruit were up to 1.49 % dw/fw and 1.02 % dw/fw, respectively. The hypothesis was true for both lab-based and hand-held instruments, and the root mean squared error of prediction on internal test set were up to 28 % higher for dehydrated fruits. The performance of interaction measurement mode was better (RMSEcv = 0.98 % dw/fw) than the diffuse reflection mode (RMSEcv = 1.21 % dw/fw) for non-dehydrated fruit, however, both modes achieved similar performance (RMSEcv = ∼1.42 % dw/fw) for dehydrated fruit. The poorer performance of Vis-NIR models on dehydrated avocado fruit can be accepted as a limitation of Vis-NIR spectroscopy for avocado fruit analysis.