Chemical Review and Letters
Volume:6 Issue: 1, Winter 2023

The analog of 4-aminoantipyrine (4-amino-1,5-dimethyl-2-phenyl-1,2-dihydro-3H-pyrazole-3-one), is interesting in the field of pharmacology and pharmaceutical chemistry and plays an important role as the ingredients for the production of the drugs and medicines. In the current study, a series of Schiff (including two new compounds) bases have been synthesized from 4-aminoantipyrine and substituted benzaldehydes via a simple and easy procedure in a short time with high yields. The structures of products have been characterized by (FTIR, 1HNMR, 13CNMR, and Elemental Analysis).

Cannabis is a widely used psychoactive substance in society, especially among the youngest. The use of this substance has been consistently associated with various health problems, many of which have in common an alteration in the cognitive manifestations of behavior, including memory, attention, emotion and decision-making. Evidence was found that cannabinoids, the active substance in Cannabis, negatively impact short-term memory, working memory, and decision-making. Likewise, cannabinoids affect attention and the interaction between cognitive events and emotion. This information can be used as a biological plausibility argument to interpret a series of clinical and epidemiological findings in which the use of Cannabis has been shown to be related to problems such as traffic accidents, psychosis, depression, poor academic performance, among others.

In this context, a rapid sonoelectrochemical decolorization of aqueous Basic Yellow 28 (BY 28) solutions on a batch reactor using an ultrasound probe (20 kHz) combined with a rectifier was studied. The residual dye was determined by UV-Vis spectrophotometric technique (λ=440 nm). A 25 central composite design (CCD; half-fraction) has been chosen to elucidate the combined effect of five process variables; applied potential, ultrasonic power, pH, electrolyte concentration and temperature. The decolorization percentage (a measure of remediation) and the energy efficiency (a measure of energy saving) were considered responses that were optimized simultaneously using the desirability function. Under the optimum conditions of applied potential (11.15V), ultrasonic power (592.7 W), pH (5), KCl concentration(0.08 mol L-1) and temperature (20.8°C), 99.99% decolorization percent and 0.83 mmolkW-1h-1 energy efficiency was predicted, that was close to obtained experimental results (97.5± 1.1% and 0.75±0.06 mmolkWh-1). The degradation products formed were studied using UV-Vis and HPLC-UV after sonoelectrochemical degradation.

The two-component reaction of 2-thiouracil and dialkyl acetylenedicarboxylate in solvent-free conditions occurred under thermal conditions and dialkyl 5-oxo-5H-[1,3]thiazolo[3,2-a]pyrimidine-2,3-dicarboxylate derivatives produced were formed. The reaction proceeded smoothly and cleanly under mild reaction conditions. The structures of the products were confirmed by IR, 1H NMR, 13C NMR, and elemental analysis. We also used ethyl phenylacetylenecarboxylate and methyl acetylenecarboxylate in this reaction, but no reaction happened. Stability, dipole moment, and global reactivity parameters of the dimethyl 5-oxo-5H-[1,3]thiazolo[3, 2-a]pyrimidine-2,3-dicarboxylate molecule were calculated at the CAM-B3LYP/6-311G(d,p) level of theory.

Adsorption capacity of nano metal oxide synthesized from waste hen egg shell for the removal of methylene blue dye from aqueous solution was investigated using batch and density function theory (DFT) process. The prepared egg shell nano particle (PESNP) were characterized using done using proximate X-ray fluorescence, Scanning electron microscopy, (SEM) and Thermogravimetric analysis. The results obtained indicated that PESNP is a good adsorbent for methylene blue. Their adsorption capacity was found to be influenced by initial dye concentration, adsorbent dose, pH, temperature and by the period of contact. The adsorption of the dye onto PESNG was found to be physical, spontaneous and best described by Freundlich and Temkin adsorption models. Adsorption kinetic study indicated that a pseudo second order kinetics is favoured. Result from the quantum chemical study indicated that the adsorption of methylene blue onto PESNP will preferentially occur through the sulphonium sulphur, nitrogen and benzene ring.

Currently the use of agricultural waste as a low-cost adsorbent have attracted much attention of researchers. The removal of cadmium (II), copper (II) and lead (II) ions from aqueous solution using peels of Chrysophyllum albidum (African Star Apple) was studied. The sorption studies were carried out by varying adsorbent dose, contact time and temperature. The experimental results showed that the adsorption removal efficiency of Chrysophyllum albidum peels on cadmium (II), copper (II) and lead (II) ions had a direct relationship with adsorbent dose and contact time while the Temperature study showed an inverse relationship. The maximum adsorption efficiencies of the adsorbent were 95.30, 93.22 and 92.78 % for Cd2+, Cu2+ and Pb2+ respectively. Sorption kinetic data fitted well with the pseudo second order kinetic model. The experimental data were analyzed using Freundlich, Langmuir and Temkin isotherm equations. The best fit was obtained by Temkin isotherm for Cd2+ and Freundlich isotherm for Cu2+ and Pb2+ ions. The Arrhenius and Eyring activation energy showed that rate of Cd2+ adsorption is more rapid than rate of Cu2+ and Pb2+ adsorption. The thermodynamic data revealed that the Cd(II) and Pb(II) ion uptake was exothermic while Cu(II) ion was endothermic and they were all spontaneous in nature. From these results, Chrysophyllum albidum peel could be recommended as an adsorbent for metal ion removal from aqueous solution.

The objective of this research is to adsorbe Orange 3R dye by a new catalyst chitosan-montmorillonite magnetic (CTS-MMT-Fe3O4) was used as an effective adsorbent for the adsorption of anions. In this research, the adsorption of Orange 3R dye as an anionic sulphonated reactive azo dye, from aqueous solution by CTS-MMT-Fe3O4 nanocomposite was investigated. The synthesized nanocomposite was characterized by FTIR (Fourier transform infrared), XRD (X-Ray diffraction) and SEM (Scanning Electron Microscopy) to evaluate the surface morphology. Adsorption experiments were conducted at room temperature in batch system. The effects of pH, initial concentration of dye, contact time and adsorbent dosage were investigated. Kinetic and equilibrium sorption parameters were evaluated pseudo-first and pseudo-second order rate models and Langmuir and Freundlich isotherms. The results indicated that the adsorption of dye onto adsorbent was better described by the pseudo second-order compared to by the pseudo-first-order. Also, the experimental data were better fitted to the Langmuir model with high R2 value (R2=0.99) than Freundlich model for adsorption. The thermodynamic studies showed that the adsorption is spontaneous and feasible. The present study indicated that CTS-MMT-Fe3O4 could be employed as an effectively adsorbent for the adsorption of Orange 3R from industrial and other effluents.

Air pollution is one of the greatest public health threats worldwide. All substances appear in excessive quantities in the atmosphere, such as particulate matter, nitrogen oxides, or sulfur oxides, maybe its ingredients. Depending on their size and nature, these compounds may cause a greater risk of suffering from respiratory or cardiovascular diseases for exposed people, as well as exacerbation and increased mortality due to these illnesses. Smaller particles may penetrate the brain’s blood barrier and thus affect the central nervous system. To study the impact of air pollution on individual mental health, this study uses data from the Iranian Student Mental Health Survey (IRSMHS) and a precise Poisson regression model based on the air quality index (API). According to the study, air pollution significantly impacts individual mental health. Depression and mental health are worse when air pollution levels are high. Furthermore, heterogeneity analysis determined that men and urban populations were more sensitive to air pollution, while this effect did not appear in women and rural groups. As part of the effort to improve people’s mental health, this article stresses the importance of intensifying efforts to control air pollution and winning the battle to defend the blue sky as soon as possible.

Whenever metals and metal-based materials interact with their environment (chemically, biochemically, or electrochemically), surface loss occurs, a process termed as corrosion. Corrosion is one of the important challenges which leads to the reduction of product life. In recent years, due to the growing interest of the world in protecting the environment and the harmful effects of using chemicals on ecological balance, the traditional approach with respect to corrosion inhibitors has gradually changed. Azole compounds have received a lot of attention in the oil, gas, and petrochemical industries since their structures prevent corrosion in acidic and alkaline environments. Also, due to having elements such as nitrogen and sulfur in their structure, they have been used widely as anti-fungal and anti-bacterial materials in the pharmaceutical industry as well. In this study, azole organic compounds, the encapsulation methods, and the mechanism of action of these compounds on the corrosion behavior of metallic surfaces have been investigated.

COSMO-SAC modeling is a reliable method to determine the activity coefficient of the mixtures and is used to predict low molecular weight organic materials hydration enthalpy. A dataset of 96 organic molecules’ activity coefficients in the different solvents (water, ethanol, methanol, toluene, and benzene) mixtures have been obtained in full range composition with COSMO-SAC. The created database has been merged with the FreeSolv dataset to include the hydration enthalpy of these materials as input of machine learning training besides the Van der Waals diameter, other important molecular descriptive. The support vector regressor, random forest regressor, and gradient boosting decision tree regressor have been used for data training and prediction of hydration enthalpy of the organic and pharmaceutical materials. Variation of training and testing rates is most effective parameter in the prediction of enthalpy of hydration. The random forest regression is the most accurate method in the prediction of the enthalpy of hydration with 1.5 % RMSD with a train: test ratio of 0.25:0.75 between the studied methods.