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The development of new methods of identification of active pharmaceutical ingredients (API) is a subject of paramount importance for research centers, the pharmaceutical industry, and law enforcement agencies. Here, a system for identifying and classifying pharmaceutical tablets containing acetaminophen (AAP) by brand has been developed. In total, 15 tablets of 11 brands for a total of 165 samples were analyzed. Mid-infrared vibrational spectroscopy with multivariate analysis was employed. Quantum cascade lasers (QCLs) were used as mid-infrared sources. IR spectra in the spectral range 980-1600 cm-1 were recorded. Five different classification methods were used. First, a spectral search through correlation indices. Second, machine learning algorithms such as principal component analysis (PCA), support vector classification (SVC), decision tree classifier (DTC), and artificial neural network (ANN) were employed to classify tablets by brands. SNV and first derivative were used as preprocessing to improve the spectral information. Precision, recall, specificity, F1-score, and accuracy were used as criteria to evaluate the best SVC, DEE, and ANN classification models obtained. The IR spectra of the tablets show characteristic vibrational signals of AAP and other APIs present. Spectral classification by spectral search and PCA showed limitations in differentiating between brands, particularly for tablets containing AAP as the only API. Machine learning models, specifically SVC, achieved high accuracy in classifying AAP tablets according to their brand, even for brands containing only AAP.

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Organic phosphoester (OPE) antioxidants are currently required due to their contribution to enhancing the quality of polymers, including polypropylene (PP). In this research, an integral methodology is presented for the efficient extraction of bis(2,4-dicumylphenyl) pentaerythritol diphosphite from industrial wastewater. Upon employing the solid-phase extraction (SPE) technique, the recovered compound is subjected to a comprehensive analysis of the recovered compound using high-performance liquid chromatography (HPLC), mass spectrometry (MS), thermal analysis (TGA), Fourier transforms infrared spectroscopy (FTIR), and differential scanning calorimetry (DSC). Subsequently, purified Bis(2,4-dicumylphenyl) pentaerythritol diphosphite was evaluated as a thermo-oxidative stabilizer after incorporation into PP resins. The relative standard deviation (RSD), Error (Er), linearity (R2), and percentage (%) recovery were less than 2.6, 2.5, more significant than 0.9995, and greater than 96%, respectively, for the inter-day and intra-day tests of the chromatographic method and the SPE. Except for chloroform, which was necessary due to the solubility properties of the investigated analyte, the use of environmentally friendly solvents, such as methanol and acetonitrile, was considered during the development of this research. The OPE extracted from industrial wastewater was characterized by FTIR, UV-Vis, DSC, TGA, and MS, allowing the elucidation of the structure of Bis(2,4-dicumylphenyl) pentaerythritol diphosphite (BDPD). The recovered OPE was mixed with PP resins, allowing it to improve its thermal properties and minimize its thermo-oxidative degradation. Organophosphorus flame retardant (OPE)' concentration in wastewater is alarming, ranging from 1179.0 to 4709.6 mg L-1. These exceed toxicity thresholds for aquatic organisms, emphasizing global environmental risks. Using a validated solid-phase extraction (SPE) technique with over 94% recovery, the study addresses concerns by removing organic contaminants and supporting circular economy principles. The high economic and environmental significance of recovering BDPD underscores the need for urgent global attention and intervention.

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Sorbitol derivatives and other additives are commonly used in various products, such as packaging or food packaging, to improve their mechanical, physical, and optical properties. To accurately and precisely evaluate the efficacy of adding sorbitol-type nucleating agents to these articles, their quantitative determination is essential. This study systematically investigated the quantification of sorbitol-type nucleating agents in food packaging made from impact copolymers of polypropylene (PP) and polyethylene (PE) using attenuated total reflectance infrared spectroscopy (ATR-FTIR) together with analysis of principal components (PCA) and machine learning algorithms. The absorption spectra revealed characteristic bands corresponding to the C-O-C bond and hydroxyl groups attached to the cyclohexane ring of the molecular structure of sorbitol, providing crucial information for identifying and quantifying sorbitol derivatives. PCA analysis showed that with the selected FTIR spectrum range and only the first two components, 99.5% of the variance could be explained. The resulting score plot showed a clear pattern distinguishing different concentrations of the nucleating agent, affirming the predictability of concentrations based on an impact copolymer. The study then employed machine learning algorithms (NN, SVR) to establish prediction models, evaluating their quality using metrics such as RMSE, R2, and RMSECV. Hyperparameter optimization was performed, and SVR showed superior performance, achieving near-perfect predictions (R2 = 0.9999) with an RMSE of 0.100 for both calibration and prediction. The chosen SVR model features two hidden layers with 15 neurons each and uses the Adam algorithm, balanced precision, and computational efficiency. The innovative ATR-FTIR coupled SVR model presented a novel and rapid approach to accurately quantify sorbitol-type nucleating agents in polymer production processes for polymer research and in the analysis of nucleating agent derivatives. The analytical performance of this method surpassed traditional methods (PCR, NN).

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This study outlines the investigation into how the compounds CO2, CO, and O2 interact with the active center of titanium (Ti) on the surface of MgCl2 and how these interactions impact the productivity of the Ziegler-Natta catalyst, ultimately influencing the thermal stability of the produced polypropylene. The calculations revealed that the adsorption energies of Ti-CO2-CO and O2 were -9.6, -12.5, and -2.32 Kcal/mol, respectively. Using the density functional theory in quantum calculations, the impacts of electronic properties and molecular structure on the adsorption of CO, O2, and CO2 on the Ziegler-Natta catalyst were thoroughly explored. Additionally, the Gibbs free energy and enthalpy of adsorption were examined. It was discovered that strong adsorption and a significant energy release (-16.2 kcal/mol) during CO adsorption could explain why this gas caused the most substantial reductions in the ZN catalyst productivity. These findings are supported by experimental tests showing that carbon monoxide has the most significant impact on the ZN catalyst productivity, followed by carbon dioxide, while oxygen exerts a less pronounced inhibitory effect.

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Biodegradable biopolymers from species of the animal kingdom or their byproducts are sustainable as ecological materials due to their abundant supply and compatibility with the environment. The research aims to obtain a biodegradable active material from chitosan, gelatin, and collagen from bocachico scales (Prochilodus magdalenae). Regarding the methodology, films were developed from gelatin, chitosan, and collagen from bocachico scales (Prochilodus magdalenae) at different concentrations using glycerol as a plasticizer and citric acid as a cross-linker. The films were obtained with the hydrated mass processed by compression molding and characterized according to humidity, water solubility, contact angle, mechanical properties, and structural properties. The results of the films showed a hydrophobic characteristic. First, the chitosan-collagen (CS/CO) films showed a yellowish color, while the gelatin-collagen (Gel/CO) films were transparent and less soluble than the gelatin-collagen (Gel/CO) films. Concerning mechanical properties, gelatin films showed higher stiffness and tensile strength than chitosan films. Furthermore, in the morphological analysis, more homogeneous chitosan films were obtained by increasing the concentration of citric acid. In general, chitosan, gelatin, and collagen extracted from the scales of the bocachico (Prochilodus magdalenae) are an alternative in the application of films in the food industry.

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The study focused on the evaluation of the influence of inhibitory compounds such as hydrogen sulfide (H2S) and methanol (CH3OH) on the catalytic productivity and properties of the polymers in the polymerization process with the Ziegler-Natta catalyst. The investigation involved experimental measurements, computational calculations using DFT, and analysis of various parameters, such as molecular weight, melt flow index, xylene solubility, and reactivity descriptors. The results revealed a clear correlation between the concentration of H2S and methanol and the parameters evaluated. Increasing the H2S concentrations, on average by 0.5 and 1.0 ppm, resulted in a drastic decrease in the polymer's molecular weight. A directly proportional relationship was observed between the flow rate and the H2S concentration. In the case of methanol, the change occurred from 60 ppm, causing a sharp decrease in the molecular weight of the polymer, which translates into an increase in the fluidity index and a decrease in solubility in xylene. The presence of these inhibitors also affected the catalytic activity, causing a reduction in the productivity of the Ziegler-Natta catalyst. Computational calculations provided a deeper understanding of the molecular behavior and reactivity of the studied compounds. The computational calculations yielded significantly lower results compared to other studies, with values of -69.0 and -43.9 kcal/mol for the Ti-CH3OH and H2S interactions, respectively. These results indicate remarkable stability in the studied interactions and suggest that both adsorptions are highly favorable.

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In this experimental-theoretical study, the effect of furan on Ziegler-Natta catalyst productivity, melt flow index (MFI), and mechanical properties of polypropylene were investigated. Through the analysis of the global and local reactivity of the reagents, it was determined that the furan acts as an electron donor. In contrast, the titanium of the ZN catalyst acts as an electron acceptor. It is postulated that this difference in reactivity could lead to forming a furan-titanium complex, which blocks the catalyst's active sites and reduces its efficiency for propylene polymerization. Theoretical results showed a high adsorption affinity of furan to the active site of the Ti catalyst, indicating that furan tends to bind strongly to the catalyst, thus blocking the active sites and decreasing the availability for propylene polymerization. The experimental data revealed that the presence of furan significantly reduced the productivity of the ZN catalyst by 10, 20, and 41% for concentrations of 6, 12.23, and 25.03 ppm furan, respectively. In addition, a proportional relationship was observed between the furan concentration and the MFI melt index of the polymer, where the higher the furan concentration, the higher the MFI. Likewise, the presence of furan negatively affected the mechanical properties of polypropylene, especially the impact Izod value, with percentage decreases of 9, 18, and 22% for concentrations of 6, 12.23, and 25.03 ppm furan, respectively.

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This research study examined how the use of dimethylformamide (DMF) as an inhibitor affects the propylene polymerization process when using a Ziegler-Natta catalyst. Several experiments were carried out using TiCl4/MgCl2 as a catalyst, aluminum trialkyl as a cocatalyst, and different amounts of DMF. Then, we analyzed how DMF influences other aspects of the process, such as catalyst activity, molecular weight, and the number of branches in the polymer chains obtained, using experimental and computational methods. The results revealed that as the DMF/Ti ratio increases, the catalyst activity decreases. From a concentration of 5.11 ppm of DMF, a decrease in catalyst activity was observed, ranging from 45 TM/Kg to 44 TM/Kg. When the DMF concentration was increased to 40.23 ppm, the catalyst activity decreased to 43 TM/Kg, and with 75.32 ppm, it dropped even further to 39 TM/Kg. The highest concentration of DMF evaluated, 89.92 ppm, resulted in a catalyst productivity of 36.5 TM/Kg and lost productivity of 22%. In addition, significant changes in the polymer's melt flow index (MFI) were noted as the DMF concentration increased. When 89.92 ppm of DMF was added, the MFI loss was 75%, indicating a higher flowability of the polymer. In this study, it was found that dimethylformamide (DMF) exhibits a strong affinity for the titanium center of a Ziegler-Natta (ZN) catalyst, with an adsorption energy (Ead) of approximately -46.157 kcal/mol, indicating a robust interaction. This affinity is significantly higher compared to propylene, which has an Ead of approximately -5.2 kcal/mol. The study also revealed that the energy gap between the highest occupied molecular orbital (HOMO) of DMF and the lowest unoccupied molecular orbital (SOMO) of the Ziegler-Natta (ZN) catalyst is energetically favorable, with a value of approximately 0.311 eV.

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Polypropylene synthesis is a critical process in the plastics industry, where control of catalytic activity is essential to ensure the quality and performance of the final product. In this study, the effect of two inhibitors, propanol and arsine, on the properties of synthesized polypropylene was investigated. Experiments were conducted using a conventional catalyst to polymerize propylene, and different concentrations of propanol and arsine were incorporated into the process. The results revealed that the addition of propanol led to a significant decrease in the Melt Flow Index (MFI) of the resulting polypropylene. The reduction in the MFI was most notable at a concentration of 62.33 ppm propanol, suggesting that propanol acts as an effective inhibitor by slowing down the polymerization rate and thus reducing the fluidity of the molten polypropylene. On the other hand, introducing arsine as an inhibitor increased the MFI of polypropylene. The maximum increase in the MFI was observed at a concentration of 0.035 ppm arsine. This suggests that small amounts of arsine affect the MFI and Mw of the produced PP. Regarding the catalyst productivity, it was found that as the concentration of propanol in the sample increased (approximately seven ppm), there was a decrease in productivity from 45 TM/kg to 44 TM/kg. Starting from 10 ppm, productivity continued to decline, reaching its lowest point at 52 ppm, with only 35 MT/kg. In the case of arsine, changes in catalyst productivity were observed at lower concentrations than with propanol. Starting from about 0.006 ppm, productivity decreased, reaching 39 MT/kg at a concentration of 0.024 ppm and further decreasing to 36 TM/kg with 0.0036 ppm. Computational analysis supported the experimental findings, indicating that arsine adsorbs more stably to the catalyst with an energy of -60.8 Kcal/mol, compared to propanol (-46.17 Kcal/mol) and isobutyl (-33.13 Kcal/mol). Analyses of HOMO and LUMO orbitals, as well as reactivity descriptors, such as electronegativity, chemical potential, and nucleophilicity, shed light on the potential interactions and chemical reactions involving inhibitors. Generated maps of molecular electrostatic potential (MEP) illustrated the charge distribution within the studied molecules, further contributing to the understanding of their reactivity. The computational results supported the experimental findings and provided additional information on the molecular interactions between the inhibitors and the catalyst, shedding light on the possible modes of inhibition. Solubles in xylene values indicate that both propanol and arsine affect the polymer's morphology, which may have significant implications for its properties and final applications.

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Currently, polypropylene (PP) is highlighted using sorbitol-based clarifying agents since these agents are high quality, low cost, and work as a barrier against moisture, which makes PP ideal for packaging food, beverages, and medical products, among others. The use of analytical methods capable of recovering these additives in wastewater streams and then reusing them in the PP clarification stage represents an innovative methodology that makes a substantial contribution to the circular economy of the PP production industry. In this study, a method of extraction and recovery of the Millad NX 8000 was developed. The additive was recovered using GC-MS and extracted with an activated carbon column plus glass fiber, using an injection molded sample, obtaining a recovery rate greater than 96%. TGA, DSC, and FTIR were used to evaluate the recovered additive's glass transitions and purity. The thermal degradation of the recovered additive was found to be between 340 and 420 °C, with a melting temperature of 246 °C, adopting the same behavior as the pure additive. In FTIR, the characteristic absorption peak of Millad NX 8000 was observed at 1073 cm-1, which indicates the purity of the extracted compound. Therefore, this work develops a new additive recovery methodology with high purity to regulate the crystallization behavior and of PP.

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