Machine learning-based modeling of malachite green adsorption on hydrochar derived from hydrothermal fulvification of wheat straw.

This study investigated the efficiency of hydrochar derived from hydrothermal fulvification of wheat straw in adsorbing malachite green (MG) dye. The characterizations of the hydrochar samples were determined using various analytical techniques like SEM, EDX, FTIR, X-ray spectroscopy, BET surface area analysis, ICP-OES for the determination of inorganic elements, elemental analysis through ultimate analysis, and HPLC for the content of sugars, organic acids, and aromatics. Adsorption experiments demonstrated that hydrochar exhibited superior removal efficiency compared to feedstock. The removal efficiency of 91 % was obtained when a hydrochar dosage of 2 g L-1 was used for 20 mg L-1 of dye concentration in a period of 90 min. The results showed that the study data followed the Freundlich isotherms as well as the pseudo-second order kinetic model. Moreover, the determined activation energy of 7.9 kJ mol-1 indicated that the MG adsorption was a physical and endothermic process that increased at elevated temperatures. The study also employed an artificial neural network (ANN), a machine learning approach that achieved remarkable R2 (0.98 and 0.99) for training and validation dataset, indicating high accuracy in simulating MG adsorption by hydrochar. The model's sensitivity analysis demonstrated that the adsorbent dosage exerted the most substantial influence on the adsorption process, with MG concentration, pH, and time following in decreasing order of impact.

Application of cadmium-doped ZnO for the solar photocatalytic degradation of phenol.

In this study, photocatalysis of phenol was studied using Cd-ZnO nanorods, which were synthesized by a hydrothermal method. The Cd-ZnO photocatalyst was characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy, and Fourier transform infrared (FT-IR) and UV-Vis spectroscopy. XRD patterns exhibit diffraction peaks indexed to the hexagonal wurtzite structures with the P63mc space group. SEM images showed that the average size of the Cd-ZnO nanorods was about 90 nm. Moreover, the nanorods were not agglomerated and were well-dispersed in the aqueous medium. FT-IR analysis confirmed that a surface modifier (n-butylamine) did not add any functional groups onto the Cd-ZnO nanorods. The dopant used in this study showed reduction of the bandgap energy between valence and conduction of the photocatalyst. In addition, effect of various operational parameters including type of photocatalyst, pH, initial concentration of phenol, amount of photocatalyst, and irradiation time on the photocatalytic degradation of phenol has been investigated. The highest phenol removal was achieved using 1% Cd-ZnO for 20 mg/l phenol at pH 7, 3 g/l photocatalyst, 120 min contact time, and 0.01 mole H2O2.

Concentration, Source, and Potential Human Health Risk of Heavy Metals in the Commonly Consumed Medicinal Plants.

A trend toward the use of traditional and herbal medicines has developed nowadays, and there is a growing concern regarding them being polluted with heavy metals. This study measured the heavy metal concentrations in eight different types of medicinal herbs and eight different types of herbal distillates sold in the markets in Sanandaj, Kurdistan, Iran. The concentration of some metals (Cd, Cu, Mn, Fe, Zn, Al, Co, Ni, Cr, Pb, and Mg) was quantified by inductively coupled plasma mass spectrometry, and the associated health risk for adults and children was estimated. The mean concentration of all the metals was within the permissible limits set by the WHO. The medicinal herbs contained significantly more Al, As, Cd, Cr, Fe, Mn, Ni, Pb, and Zn (p < 0.02) than the herbal distillates. However, the concentrations of Cu and Hg were higher in the herbal distillates. The non-carcinogenic risks of consumption of traditional medicines in adults and children were assessed based on the target hazard quotients (THQs). The THQs for individual metals (except Al and Cr) from individual herbs were less than 1, which is considered as safe for human consumption.

Evaluation of trace element concentration in cancerous and non-cancerous tissues of human stomach.

Gastric cancer has a high mortality rate in west of Iran. Various environmental elements are proposed as cancer risk factors including trace elements. Trace elements can induce initiation or progression of carcinogenesis via oxidative stress and DNA injury. The aim of this study was to measure and compare some trace element concentration (Ca, Cu, Fe, As, Mg, Ni, Cd and Cr) in gastric cancer tissues and normal tissues. For this purpose, 35 patients with gastric cancer and 30 without any cancer were biopsied. Biopsies were taken from cancerous tissue and non-cancerous tissue of gastric cancer patients and gastric tissue of normal patients. The analysis of trace elements was performed using Inductively coupled plasma mass spectrometry (ICP-MS). Data analysis was carried out using SPSS and STATA 12 software. The research found that the concentrations of Fe, Mg, and As were higher in cancerous tissues compared with non-cancerous tissues whereas Cr, Cu, Ca, and Ni concentrations were higher in non-cancerous tissues of cancerous patients. When comparisons were made for cancer and normal samples, copper was the only metal, which was significantly higher in cancerous samples (p < 0.05) and Cr mean concentration in normal tissues was significantly higher compared with cancerous tissues (P = 0.02). Chi-Square test showed that there was no significant relationship in the demographic information between cancerous and normal patients except for location with K2 = 7.604. Increased Cu and As concentration in gastric patients (both tissues) propose that these elements may have carcinogenic effects, although further study is suggested.