The manufacture of detergent products such as laundry detergents, household cleaners and fabric softeners are of increasing interest to the consumer oriented chemical industry. Surfactants are the most important ingredient in detergent formulations, as they are responsible for the bulk of the cleaning power. In this research, a methodology has been developed to design a detergent product using computational tools. Different surfactant systems, such as single anionic, single nonionic, and binary mixtures of anionic-nonionic surfactants are covered in this work. Important surfactant properties such as critical micelle concentration (CMC), cloud point (CP), hydrophiliclipophilic balance (HLB) and molecular weight (MW) have been identified. A group contribution (GC) method with the aid of computer modelling was used to determine the CMC, CP, and MW of surfactant molecules. The design of a surfactant molecule can be formulated as a multi-objective optimization problem that tradeoffs between CMC, CP, HLB and MW. Consequently, a list of plausible nonionic surfactant structures has been developed with the selected surfactant being incorporated into a binary surfactant mixture. Additives such as antimicrobial agents, anti-redeposition agents, builders, enzymes, and fillers were also considered and incorporated into a hypothetical detergent formulation together with the binary surfactant mixture. The typical ingredients and their compositions in detergent formulations are presented in the final stage of the detergent product design.

In a recent study, it was determined that the usage of Li-Ion batteries in electric vehicles (EVs) represent a huge portion of the overall usage. In order to foster a sustainable future, Li-Ion batteries in EVs generally undergo a disassembly during the recycling process, which is intended for secondary purposes or recover useful materials and components. However, the current disassembly process is significantly time consuming and expensive. Hence in this research, a disassembly framework is presented, which focuses on improving the disassembly efficiency. The framework consists of a hybrid disassembly workstation that utilizes modified automated robotic arms and a specialized tool to allow an improvement in the disassembly time. The framework focuses on optimizing several identified parameters. These parameters (Design, Safety, and Cost) were identified through a comprehensive review and analysis of the schematics and properties of conventional EV battery packs along with the disassembly procedures being currently in practice. Additionally, the framework also consists of a conceptualized disassembly procedure developed based on the potential improvements of the hybrid disassembly. The framework proposed would allow a 5-step reduction in the overall disassembly steps, and thus would be highly suited to be adopted in the EV disassembly industry.

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