This study investigated the efficient removal of cadmium ions from aqueous solutions using calcium oxide nanoparticles (CaO NPs) synthesized from waste hen eggshells using a Sol-gel method and supported on corncob bio-adsorbent. The synthesized CaO NPs were characterized using FT-IR, XRD, specific surface area, and TGA. Batch adsorption experiments were conducted to examine the influence of process parameters such as adsorbent dosages, initial Cd (II) concentrations, pH values, and contact times. XRD analysis revealed that the synthesized CaO nanoparticles had a size of 24.34 nm and a specific surface area of 77.4 m²/g. The optimal conditions for achieving the highest percent removal of cadmium (99.108%) were found to be an initial concentration of 55 ppm, pH 7, adsorbent dose of 0.75 g, and contact time of 50 min. The experimental removal efficiency closely matched the predicted value (99.0%), indicating the suitability of the method used in optimizing the removal of Cd (II) ions from aqueous solutions. These findings, corroborated by predicted values, underscore the efficacy of our method in optimizing cadmium removal. Based on these findings, it can be concluded that corncob-supported CaO NPs are optimized for their highest efficiency and hold great promise as a cost-effective and environmentally friendly solution for wastewater treatment with a focus on cadmium removal.

The primary goal of this research is to lower the hexavalent chromium (Cr (VI)) concentration that has occurred from the growth of the tannery industry. As a result, the potential for heavy metal concentration is increasing day by day. Industrial effluent containing Cr (VI) contributes significantly to water pollution. Chromium hexavalent ion (Cr (VI)) in wastewater is extremely hazardous to the environment. It is critical to address such a condition using activated carbon derived from biomass. Adsorption is one of the most successful methods for removing hexavalent chromium from wastewater. Treated wastewater has no substantial environmental contamination consequences. The ash content, moisture content, volatile matter content, and fixed carbon content of wet coffee husk were 3.51, 10.85, 68.33, and 17.31, respectively. The physicochemical properties of coffee husk-based activated carbon (CHBAC) obtained during experimentation were pH, porosity, the yield of CHBAC, bulk density, point of zero charges, and specific surface area of 5.2, 58.4 percent, 60.1 percent, 0.71 g/mL, 4.19, and 1396 m²/g, respectively, indicating that CHBAC has a higher capacity as an adsorbent medium. For optimization purposes, the parameters ranged from pH (0.3–3.7), dose (2.3–5.7) , and contact time (0.3–3.7) hr. The quadratic models were chosen for optimization, and the value for the model was significant since it was less than 0.05, but the lack of fit model was inconsequential because it was more than 0.05. The optimum adsorption obtained with numerical optimization of Cr (VI) was 97.65 percent. This was obtained at a pH of 1.926, a dose of 4.209 g/L, and a contact time of 2.101 hours. This result was observed at a pH of 1.93, a dosage of 4.2 g/L, and a contact duration of 2.1 hours. The desirability obtained during numerical optimization was 1. Coffee husk-based activated carbon has a bigger surface area, and it has a stronger ability to absorb hexavalent chromium from tannery wastewater effluents.

In this study, a description was given for the adsorbent CaSiO₃ for allure proximate examination and determination like particle density, main part density, and porosity analysis. This is performed before management of batch adsorption experiments. Both kinetics and balance studies for the adsorbent were examined. The influences of various process parameters like lead concentration, pH, adsorbent dosage, and contact temporal length for process removal were explored. The removal efficiency of CaO from eggshell was enhanced to increase after mixing it with silica coagulate compared with added scholar’s findings for the same limit. The maximum removal efficiency (99.58%) was obtained by limiting the pH, adsorbent dosage, initial lead concentration, and contact time at 4, 1.8 g, 35 g/L, and 140 minutes, respectively. Thus, blending CaO from eggshells with silica gel can increase the adsorption competency of CaO. Lead removal is well integrated into the Langmuir isotherm model with an equivalent factor of 0.991. The kinetic data of adsorption fit well into a pseudo‐first‐order model with a correlation coefficient of 0.90111. The pseudo‐second‐order model was the rate‐determining step involved in the lead adsorption process for calcium silicate (CaSiO₃) adsorbents.

This study was aimed at extracting, optimizing, and characterizing the neem seed oil through Box-Behnken design. The effects of extraction parameters such as temperature (50-80°C), particle size (0.15–0.3 mm), and time (60-180 min) were considered. The extraction of oil was studied using the soxhlet extraction process, applying n-hexane as a solvent. The quadratic model was suggested to demonstrate optimal extraction parameters of 132.677 min, 64.416°C of temperature, and 0.212 mm of particle size using numerical optimization. The experimental yield of oil at optimum conditions 44.141%, which was close to the model-anticipated value. The physicochemical properties suggested that neem oil had an ash content of 2.1%, moisture content 4.61%, density 0.875 g/cm3, viscosity 33.5 mm2/s, specific gravity 0.88, saponification value 206.7 mg KOH/, iodine value 122.5 g I2/100 g, acid value 1.81 mg KOH/g, and cetane number of 75. The extraction parameters had a significant effect on the yield of neem seed oil. However, the temperature and particle size had a higher effect compared to the extraction time. The most important unsaturated fatty acid is oleic acid (60.924 %). The properties of the oil revealed that the neem seed oil can be used as a potential source of material for industrial applications. It can be concluded that neem seeds have the potential to be used as industrial feedstocks in the future.

In this study, leftover injera waste from the southwestern parts of Ethiopia was used as a raw material for bioethanol production. The conversion of this biomass into ethanol involved processing techniques, which include hydrolysis, fermentation, and distillation. This research focuses on determining optimal parameters that are temperature, acid concentration, and hydrolyzing time in a hydrolysis stage. Using response surface analysis, the suggested model is quadratic and has three independent factors, which had significant effects on the yield of ethanol. In this analysis, the temperature and hydrolyzing time had a positive relationship with the yield of ethanol whereas acid concentration had a negative relation. The optimum yield of ethanol obtained was 79.07. The yield optimized in g/g was 29.99, which was obtained at a temperature of 109.99°C, at an acid concentration of 1.00, and hydrolyzing time of 49.59 minutes. For this analysis, the mathematical model equation was developed and the R² value was 99.9 and its desirability was 0.8867. The property of ethanol was characterized by the many parameters used in different standardization. The density, viscosity, flammability, boiling points, and pH were determined as 0.803 gcm⁻³, 1.1 cP, 14°C, 80°C, and 6.65, respectively.