Insights into the heterogeneity of coal fly ash waste

Abstract

Coal is a well-known workhorse for power generation, particularly in developing countries, due to its favourable economic benefits such as low cost, wide availability, and minimal infrastructure. However, coal-fired power plants yield a substantial by-product, known as coal fly ash (CFA), with a global annual output of 1 billion tons during combustion. Only 60% of this CFA is presently used, whereas the rest is disposed of in the environment, contributing to severe environmental pollution. In contrast, CFA is a versatile material that can serve as an adsorbent, fertiliser, and in advanced material applications, offering a promising dimension for its use. This study addressed the multifaceted potential of CFA components, by probing its seldom-explored heterogeneity through advanced characterisation techniques. While existing research has predominantly focused on isolated extractions, neglecting broader applications, this study proposes a comprehensive strategy centred on the strategic implementation of washing cycles. Integral to this approach is an extensive characterisation campaign employing multi-modal imaging techniques, such as scanning electron microscopy and energy-dispersive X-ray spectroscopy combined with state-of-the-art deep learning algorithms and digital image processing techniques. Through these methods, this study uncovered and extracted various valuable constituents from CFA, notably cenospheres and materials conducive to zeolite synthesis, demonstrating their potential as effective adsorption agents. Furthermore, this study pioneered a novel methodology that combined X-ray microanalysis with deep learning to precisely classify and characterise cenospheres. This breakthrough facilitated a comprehensive understanding of these hollow structures and allowed quantification of their imperceptible physical structures to modify them as efficient adsorbents. The results of this study significantly contribute to elucidating the capabilities of CFA as a source of high-performance adsorption agents. By leveraging innovative techniques and holistic approaches, this study advances our understanding of CFA, and offers a pioneering methodology for sustainable waste management and resource recovery. Keywords: Coal fly ash, Cenosphere, X-ray microanalysis, Deep learning