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Microwave pretreatment of switchgrass for bioethanol production.

机译:微波对柳枝s进行生物乙醇生产的预处理。

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Lignocellulosic materials are promising alternative feedstocks for bioethanol production. These materials include agricultural residues, cellulosic waste such as newsprint and office paper, logging residues, and herbaceous and woody crops. However, the recalcitrant nature of lignocellulosic biomass necessitates a pretreatment step to improve the yield of fermentable sugars. The overall goal of this dissertation is to expand the current state of knowledge on microwave-based pretreatment of lignocellulosic biomass.;Existing research on bioenergy and value-added applications of switchgrass is reviewed in Chapter 2. Switchgrass is an herbaceous energy crop native to North America and has high biomass productivity, potentially low requirements for agricultural inputs and positive environmental impacts. Based on results from test plots, yields in excess of 20 Mg/ha have been reported. Environmental benefits associated with switchgrass include the potential for carbon sequestration, nutrient recovery from run-off, soil remediation and provision of habitats for grassland birds. Published research on pretreatment of switchgrass reported glucose yields ranging from 70-90% and xylose yields ranging from 70-100% after hydrolysis and ethanol yields ranging from 72-92% after fermentation. Other potential value-added uses of switchgrass include gasification, bio-oil production, newsprint production and fiber reinforcement in thermoplastic composites.;Research on microwave-based pretreatment of switchgrass and coastal bermudagrass is presented in Chapter 3. Pretreatments were carried out by immersing the biomass in dilute chemical reagents and exposing the slurry to microwave radiation at 250 watts for residence times ranging from 5 to 20 minutes. Preliminary experiments identified alkalis as suitable chemical reagents for microwave-based pretreatment. An evaluation of different alkalis identified sodium hydroxide as the most effective alkali reagent. Under optimum pretreatment conditions, 82% glucose and 63% xylose yields were achieved for switchgrass, and 87% glucose and 59% xylose yields were achieved for coastal bermudagrass following enzymatic hydrolysis of the pretreated biomass. The optimum enzyme loadings were 15 FPU/g and 20 CBU/g for switchgrass and 10 FPU/g and 20 CBU/g for coastal bermudagrass. Dielectric properties for dilute sodium hydroxide solutions were measured and compared to solid loss, lignin reduction and reducing sugar levels in hydrolyzates. Results indicate that the dielectric loss tangent of alkali solutions is a potential indicator of the severity of microwave-based pretreatments.;Modeling of pretreatment processes can be a valuable tool in process simulations of bioethanol production from lignocellulosic biomass. Chapter 4 discusses three different approaches that were used to model delignification and carbohydrate loss during microwave-based pretreatment of switchgrass: statistical linear regression modeling, kinetic modeling using a time-dependent rate coefficient, and a Mamdani-type fuzzy inference system. The dielectric loss tangent of the alkali reagent and pretreatment time were used as predictors in all models. The statistical linear regression model for delignification gave comparable root mean square error (RMSE) values for training and testing data and predictions were approximately within 1% of experimental values. The kinetic model for delignification and xylan loss gave comparable RMSE values for training and testing data sets and predictions were approximately within 2% of experimental values. The kinetic model for cellulose loss was not as effective and predictions were only within 5-7% of experimental values. The time-dependent rate coefficients of the kinetic models calculated from experimental data were consistent with the heterogeneity (or lack thereof) of individual biomass components. The Mamdani-type fuzzy inference system was shown to be an effective means to model pretreatment processes and gave the most accurate predictions (3%) for cellulose loss.
机译:木质纤维素材料是用于生物乙醇生产的有前途的替代原料。这些材料包括农业残留物,纤维素废料(例如新闻纸和办公用纸),伐木残留物以及草木作物。然而,木质纤维素生物质的顽强特性需要预处理步骤以提高可发酵糖的产率。本论文的总体目标是扩大基于微波的木质纤维素生物质预处理的知识。第二章综述了柳枝bio的生物能源和增值应用的现有研究。柳枝is是北方原生的草本能源作物美国,生物量生产率高,对农业投入物的要求可能较低,并对环境产生积极影响。根据测试区的结果,已报告产量超过20 Mg / ha。柳枝associated的环境效益包括固碳,从径流中回收养分,土壤修复以及为草地鸟类提供栖息地的潜力。柳枝pre预处理的已发表研究报告说,水解后的葡萄糖产率为70-90%,木糖的产率为70-100%,发酵后的乙醇产率为72-92%。柳枝switch的其他潜在增值用途包括气化,生物油生产,新闻纸生产和热塑性复合材料中的纤维增强。;第3章介绍了基于微波的柳枝and和沿海百慕大草的预处理研究。稀释化学试剂中的生物质,并将浆液在250瓦的微波辐射下停留5至20分钟。初步实验确定了碱是适用于微波预处理的合适化学试剂。对不同碱的评估表明氢氧化钠是最有效的碱试剂。在最佳预处理条件下,经过预处理的生物质经过酶促水解后,柳枝glucose达到了82%的葡萄糖和63%的木糖产率,沿海coastal草达到了87%的葡萄糖和59%的木糖产率。柳枝switch的最佳酶负载量为15 FPU / g和20 CBU / g,沿海百慕大草的最佳酶负载为10 FPU / g和20 CBU / g。测量了稀氢氧化钠溶液的介电性能,并将其与固体损耗,木质素还原和水解产物中糖含量降低进行了比较。结果表明,碱溶液的介电损耗角正切是潜在的微波预处理的严重程度的指标。预处理过程的建模可以是从木质纤维素生物质生产生物乙醇的过程​​模拟中的宝贵工具。第4章讨论了三种基于微波的柳枝pre预处理过程中的去木质素和碳水化合物损失建模的不同方法:统计线性回归建模,使用时间相关速率系数的动力学建模和Mamdani型模糊推理系统。在所有模型中,碱性试剂的介电损耗正切和预处理时间均用作预测指标。用于去木质素的统计线性回归模型给出了可比的均方根误差(RMSE)值,用于训练和测试数据,并且预测值大约在实验值的1%以内。脱木质素和木聚糖损失的动力学模型为训练和测试数据集提供了可比较的RMSE值,并且预测值大约在实验值的2%以内。纤维素损失的动力学模型不是那么有效,并且预测仅在实验值的5-7%之内。从实验数据计算的动力学模型的时间依赖性速率系数与单个生物质组分的异质性(或缺乏异质性)一致。 Mamdani型模糊推理系统被证明是对预处理过程进行建模的有效手段,并给出了最准确的纤维素损失预测(<3%)。

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