Abstract
Lignocellulose presents a promising alternative to fossil fuels. Monitoring the mass and size changes of lignocellulosic particles without disrupting the process can assist in adjusting pretreatment and enzymatic hydrolysis, where conventional sieving methods fall short. A method utilizing focused beam reflectance measurement (FBRM) was developed to establish mathematical correlations between FBRM chord information (chord length and count) and particle characteristics (weight and size) quantified through sieving. Results indicate particle size exhibits a linear correlation with the square weighted median chord length (Lsqr) with R2 at 0.93. Further, real-time bulk particle mass can be predicted using Lsqr and chord count (R2 0.98). These correlations are applicable in range 53 μm to 358.5 μm. Real-time monitoring of enzymatic hydrolysis of corn stalks has demonstrated the practical applicability of FBRM. This study introduces a novel approach for online characterization of lignocellulosic particles, thereby enhancing lignocellulosic biorefineries.
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