Dual phase role of composite adsorbents made from cockleshell and natural zeolite in treating river water

In this study, the potential of dual-phase composite adsorbent to determine the removal efficiency of organic compounds such as COD, BOD, TP, and TN was investigated. The combination ratio of cockleshell and natural zeolite was optimized using D-optimal mixture design (DMD). The generated ratio was tested using run test in Easy Care PipeSystem (ECPS). Breakthrough curve was plotted to determine the total removal by composite adsorbent. In addition, linearization of the breakthrough curve by dynamic models was implemented to characterize the adsorption process by the composite adsorbent in ECPS column model. The linearization of breakthrough curve was done using mathematical models, Adam-Bohart, Yoon-Nelson and Thomas model. It was found that the optimal mixture ratio was at 75% cockleshells and 25% natural zeolite. Based on the experiments, the composite adsorbent showed high tendency to higher removal by 90% of targeted value. Based on the results, the composite adsorbent was fitted better with Yoon-Nelson and Thomas model rather than Adam-Bohart model. The generated models were able to characterize the adsorption process using composite adsorbent in the ECPS column system

Development of microbial biofilms on cellulosic fibers for organic matter removal in river water treatment

The present study focuses on the usage of natural cellulosic fibers like coconut fibers (CF) and oil palm fibers (OPF) as an organic substrate for biofilm formation in removing pollutants as opposed to numerous studies that utilized non-organic substrates like plastic and synthetic membrane. The corresponding adsorption ability was tested toward the organic matters (OM) removal in the contaminated river water. The experimental results showed that CF and OPF possessed a higher concentration of phenolic and alcoholic hydroxyl groups by hydrogen bonds have led to a thinner extracellular polymeric substance being formed. The rate at which OM is removed for biofilm attached on coconut fiber (BCF) and biofilm attached on oil palm fiber (BOPF) were identified to be 94.07% and 87.01%, respectively. At 3% outflow, the global mass transfer rate BCF and BOPF were 1.01 and 0.84 d–1. Further to that, the internal mass transfer was found to have an effective diffusivity of pollutants to biofilm. Yet, the mass transfer decreases with the decrease of OM concentration in water. Therefore, it is evident that natural cellulosic fibers are highly effective alternative carriers that can be used for biofilm growth in removing excess concentration of OM in river water

A novel surfactant molecular design with optimal performance, safety and health aspects for laundry detergent

Surfactants are one of the main ingredients in laundry detergent formulation used to improve the wetting ability of water, loosens and removes oil with the aid of wash action. Sodium lauryl sulfate (SLS) and diethanolamine (DEA) are two examples of chemicals used as surfactants in laundry detergents. Exposure to SLS and DEA has the potential to cause skin and eye irritation. In this study, surfactant candidates were designed by using Computer-aided Molecular Design (CAMD) tools with the integration of safety and health properties. The CAMD start with problem formulation, followed by model development, molecular design, optimization model and performance analysis. The important surfactant properties such as critical micelle concentration (CMC), hydrophilic-lipophilic balance (HLB) and molecular weight (MW) were considered. The safety and health properties of surfactant candidates are assessed using index-based methodology. The surfactant candidates with optimum property functionality, safety and health performance are presented. The potential surfactant candidate, 1-aminomethyl-2,3,4,5,6-pentamethylnonane-1,8-diol is suggested to be implemented into in the laundry detergent formulation as it offers lower CMC (0.00228 mol/L) and minimum safety and health risks (total index score of 6) to consumers