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.
摘要：
木质纤维素是化石燃料的有希望的替代品。监测木质纤维素颗粒的质量和尺寸变化而不破坏过程可以帮助调整预处理和酶促水解。传统的筛分方法不足。开发了一种利用聚焦光束反射率测量（FBRM）的方法，以建立FBRM弦信息（弦长和计数）与通过筛分量化的颗粒特征（重量和尺寸）之间的数学相关性。结果表明,颗粒尺寸与平方加权的中值弦长(Lsqr)呈线性相关,R2为0.93。Further,可以使用Lsqr和弦计数（R20.98）预测实时散装颗粒质量。这些相关性适用于53μm至358.5μm的范围。玉米秸秆酶解的实时监测证明了FBRM的实际适用性。本研究介绍了一种在线表征木质纤维素颗粒的新方法，从而增强木质纤维素生物精炼厂。
