New fuel indexes to predict ash behavior for biogenic silica production

One of the main challenges in biomass combustion for energy and material applications are existing uncertainties for the prediction of slag formation in the bottom ash. Slagging indexes, which are calculated based on the fuel ash composition, can play an important role as simple tools to address this challenge. However, in order to use a fuel index, it is pivotal to consider its relevant scope and its applicability according to its chemical background. In this work, a self-developed Python code was employed to find relevant fuel indexes for the prediction of slag formation with high correlation coefficient based on experimental data from the combustion of rice husk and rice straw. Pre-treatment and fuel blending were utilized to mitigate slag formation in these silica-rich biomass fuels. Results showed that the selected newly defined fuel index, i.e. (K + Na + Mg) / P [mol/mol], which includes ash forming elements relevant for slag formation during the combustion of silica-rich biomass, improves average coefficient of determination for the prediction of the slag formation between 800 and 1100 °C to 0.9187. By employing gas sorption as well as a scanning electron microscopy analysis, it was also shown that the fuel indexes are able to classify the silica-rich ashes for material applications in terms of slag formation on microscopic level and the changes in silica purity. At temperatures higher than 900 °C, porosity of the ashes decreases substantially because of ash sintering on microscopic level. This also applies for acid-leached fuels although their slag formation tendency on macroscopic level is lower than 30 %. These findings are highly relevant to secure sustainable operation of biomass boilers and high-quality biogenic silica production from silica-rich biomass assortments for material applications.