Abbas, Alaa (2025) Carbon NanoStructures/Metal Oxide Modified Anodes in Microbial Fuel Cells for Wastewater Treatment/Power Production. [Tesi di dottorato]

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• Sistema commerciale multilaterale e tutela degli interessi facenti capo a soggetti non statali. (deposited 09 Nov 2009 09:25)
  • Carbon NanoStructures/Metal Oxide Modified Anodes in Microbial Fuel Cells for Wastewater Treatment/Power Production. (deposited 21 Ott 2025 09:26) [Attualmente visualizzato]

Abstract

This PhD study, supported by ENI Energy Corporate within the Young Talent from Africa program, is dedicated to advancing microbial fuel cell (MFC) technology with special attention to soil microbial fuel cells (SMFCs) powered by wastewater. SMFCs represent a promising option for generating clean energy due to their simple operating conditions, low-cost inputs, and minimal infrastructure requirements. The study seeks to optimize anode materials to increase microbial interactions and general MFC performance and enable real-world applications. The thesis has three main parts: a literature review, anode fabrication, and a process simulation based on machine learning for predicting performance. The literature review summarises current MFC technology, challenges in preparing electrode materials, and developments for better energy efficiency and stability. Chapter 3 outlines the construction of cobalt-molybdate oxide (CoMoO₄) nanorod- supported anodes selected due to their high conductivity. Experimental data reveal considerable improvement in electrochemical activity and microbial attachment, e.g., power densities twice that of plain carbon-based anodes. The improved performance illustrates the potential for utilizing advanced materials to improve microbial fuel cell (MFC) performance. Chapter 4 examines flame oxidation-treated stainless steel electrodes with other surface modifications. While laboratory tests indicated that the modified electrodes showed improved performance over their unmodified equivalents, field tests in actual practice indicated that unmodified stainless steel performed better than the modified versions. This observation highlights the importance of microbial colonization on simpler surfaces, implying that low-cost and easily conformable materials might prove more effective in actual use. Chapter 5 describes machine learning techniques and neural networks to predict MFC performance from experimentally obtained data for various configurations. Although there were some positive trends in the predictions, accuracy was limited by the high scatter in the power production values in the data. The power output is influenced by variations in system conditions and, as such, needs large and ongoing datasets to capture this wide range. The chapter discusses the challenges of applying machine learning to MFCs and emphasizes the importance of standardized experimental conditions and quality data for improving prediction robustness. This PhD thesis assists in understanding MFC technology by investigating new anode materials and their impact on performance at the laboratory and practical scales. It demonstrates the potential for low-cost, abundant materials and the challenge of modelling MFC systems with the future development of sustainable microbial fuel cell technology in mind.

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