ADSORPTION OF FOOD COLORING ALLURA RED DYE (E129) FROM AQUEOUS SOLUTIONS USING ACTIVATED CARBON

The adsorption behavior of Allura red (E129) from aqueous solutions onto activated carbon was successfully investigated. All factors affecting the adsorption process were carefully studied and the conditions were optimized. Adsorption of E129 onto activated carbon was found to increase by decreasing the mass of activated carbon, pH and ionic strength of the solution and by increasing temperature. The adsorption capacity of the activated carbon for Allura red was relatively high. Under the optimum conditions, the maximum adsorption capacity for E129 dye was 72.85 mg/g. Three adsorption models; Langmuir, Freundlich and Temkin model were investigated regarding the adsorption of E129. The models’ parameters KL, qm, R2, (n) were determined and found to be 0.0222, 72.85 mg/g, 0.9057-0.9984, and 0.992, respectively. Also, pseudo first and second-order kinetic models were tested to determine the best-fit model to the adsorption of E129 dye onto activated carbon. The results showed that the adsorption of E129 onto activated carbon obeyed both the Freundlich isotherm and pseudo second-order kinetic models. Moreover, thermodynamic studies indicated that the adsorption of E129 dye onto the activated carbon was spontaneous.Â

Drivable path detection using CNN sensor fusion for autonomous driving in the snow

This work targets the problem of drivable path detection in poor weather conditions including on snow covered roads. A successful drivable path detection algorithm is vital for safe autonomous driving of passenger cars. Poor weather conditions degrade vehicle perception systems, including cameras, radar, and laser ranging. Convolutional Neural Network (CNN) based multi-modal sensor fusion is applied to path detection. A multi-stream encoder-decoder network that fuses camera, LiDAR, and Radar data is presented here in order to overcome the asymmetrical degradation of sensors by complementing their measurements. The model was trained and tested using a manually labeled subset from the DENSE dataset. Multiple metrics were used to assess the model performance

Enhancing The Adsorption Capacity of Commercial Kaolin for Efficient Removal of Lead Ions from Aqueous Solutions

The sorption of lead ions (Pb+2) from aqueous solutions using commercial kaolin (KC) was investigated. The effects of various factors such as dosage, different pH media, different concentration, and temperature on the adsorption process were investigated. The Langmuir model was determined to fit the Pb+2sorption model on KC. Langmuir model parameters qm, KL, and R2, were found to be 31.2, 0.0014, and 0.9908 mg.g-1 respectively. The qmax of the Pb+2 on KC was 31.2 mg.g-1 at pH 5.7, 500 mg of KC, and 25?C. Free energy (?G), enthalpy (?H), and entropy (?S) were calculated to understand the nature of the sorption  process. Negative ?G, negative ?H, and positive ?S were found to indicate the adsorption process is non-spontaneous, exothermic, and random, respectively. A pseudo-second-order (PSO) model was followed for the adsorption process. The percentage extractions (%ER) found ranged from 102.5- 90.8 % for stimulation mineral water and tap water samples. This research provides valuable insights for the development of efficient and sustainable methods for water treatment and environmental remediation

Enhanced Electrocatalytic Oxygen Reduction Reaction of TiO₂ Nanotubes by Combining Surface Oxygen Vacancy Engineering and Zr Doping

This work examines the cooperative effect between Zr doping and oxygen vacancy engineering in anodized TiO2 nanotubes (TNTs) for enhanced oxygen reduction reactions (ORRs). Zr dopant and annealing conditions significantly affected the electrocatalytic characteristics of grown TNTs. Zr doping results in Zr4+ substituted for Ti4+ species, which indirectly creates oxygen vacancy donors that enhance charge transfer kinetics and reduce carrier recombination in TNT bulk. Moreover, oxygen vacancies promote the creation of unsaturated Ti3+(Zr3+) sites at the surface, which also boosts the ORR interfacial process. Annealing at reductive atmospheres (e.g., H2, vacuum) resulted in a larger increase in oxygen vacancies, which greatly enhanced the ORR activity. In comparison to bare TNTs, Zr doping and vacuum treatment (Zr:TNT–Vac) significantly improved the conductivity and activity of ORRs in alkaline media. The finding also provides selective hydrogen peroxide production by the electrochemical reduction of oxygen