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NRF Thuthuka Project: Microplastics Removal from Wastewater using Machine Learning Optimization (TTK240430216739)
Summary
This project aimed to use machine learning to optimize two microplastic removal methods—ultrasonication and membrane filtration—from urban wastewater, leveraging artificial neural networks to identify optimal operating conditions for sustainable treatment at scale.
Increased microplastics contamination in wastewater is a challenge to the environment and public health. The removal of these pollutants requires innovative strategies for effective mitigation. This study aims to employ artificial neural network to optimize two promising microplastics removal methods from the urban water cycle: ultrasonication and membrane filtration. The project's overall objective is to advance sustainable technologies that supplement the efficacy of microplastics extraction from wastewater, addressing the environmental consequences. Leveraging ML, this research aims to optimize ultrasonication parameters and membrane filtration techniques while integrating interdisciplinary datasets to strengthen the robustness and applicability of ML models. A better understanding of the interplay between operational parameters and environmental impacts is anticipated by merging ML with the optimization processes. Such interdisciplinary (artificial intelligence-enabled prediction and optimization, chemical engineering, chemistry, and environmental science) measures can enhance microplastics removal efficiency and mitigate environmental harm, consequently enabling sustainable technologies to address microplastics pollution in wastewater. The research represents an important stride towards a data-driven paradigm in microplastics management, aligning with the following key United Nations Sustainable Development Goals: 6(clean water and sanitation), 11 (sustainable cities and communities), 12 (responsible consumption and production), 14 (life below water), and 15 (life on land). Furthermore, the project strives to support South African black female Chemical Engineering Hons, Masters, and Doctoral students, thus creating a pipeline of academic talent through rigorous academic training and development. These students are expected to find employment within Assistant Lecturer, Research Assistant, nGAP, andpost-doctoral research fellow positions.