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At least 19 records

TEA Modeling to Quantify Economic Implications for Biorefinery Processing of Isolated Anatomical Fractions of Corn Stover

The Feedstock-Conversion Interface Consortium (FCIC; https://www.energy.gov/sites/prod/files/2020/01/f70/beto-fcic-overview-web.pdf), a collaboration of nine national laboratory partners, seeks to understand impacts of feedstock attributes on biorefinery performance. It is hypothesized that different individual anatomical fractions of corn stover vary in composition and recalcitrance, such that processing each fraction on its own through dedicated campaigns may enable better biorefinery economics overall relative to processing the whole stover material. This presentation focuses on techno-economic analysis (TEA) modeling to quantify the yield and cost ramifications for processing isolated anatomical fractions of corn stover through a low-temperature conversion biorefinery, reflecting a biochemical processing pathway consisting of biomass deconstruction through pretreatment and enzymatic hydrolysis, sugar fermentation and upgrading to hydrocarbon fuels, and lignin upgrading to value-added coproducts. Commercial-scale process simulation and economic evaluation leveraged experimental and analytical data from FCIC researchers for conversion of whole corn stover plus three individual anatomical fractions (cobs, husks, and stalks) across key steps of the conversion process. Our assessment found encouraging potential for biorefinery economic gains that may be achieved through this approach. TEA results indicated fuel yields varying from 29-44 gallons gasoline equivalent (GGE)/dry ton for the individual anatomical fractions compared to whole stover at 34 GGE/ton, equating to minimum fuel selling prices (MFSPs) between $6.37-$10.18/GGE for the fractions versus $8.76/GGE for whole stover (when lignin is burned), or $9.15-$15.19/GGE for the fractions versus $13.11/GGE for whole stover (when lignin is upgraded to coproducts, based on current experimental performance levels). Cobs and husks demonstrated the ability to achieve the highest fuel yields and lowest MFSPs, outperforming whole stover, while stalks led to the opposite result, as a composite reflection of compositional differences and process convertibility. Notably, even when taking the weighted average of the results reflecting each anatomical fraction weighted by its corresponding makeup of corn stover, this feasibility TEA screening supports feedstock cost allowances on the order of roughly $22-$29/ton as may reflect accommodating additional biomass fractionation equipment during feedstock pre-processing upstream of the conversion biorefinery gate to separate corn stover into such constituent fractions. Or viewed differently, the weighted average MFSP for the fractions was found to be $0.31-$0.32/GGE lower than the MFSP for the whole stover basis across either lignin scenario, when maintaining a fixed biomass feedstock cost. These findings highlight favorable implications for biorefinery economics as may be achieved by moving to a staged campaign approach for processing different corn stover fractions sequentially. Further opportunities exist for future work to fill in data gaps for remaining anatomical constituents (e.g. leaves) that were not included in the initial experimental studies, though are expected to maintain similar trends.

biochemical processing pathway↗

NMR relaxometry characterization of water adsorption in corn stover anatomical fractions

Nuclear magnetic resonance (NMR) relaxometry is applied to provide direct measurement of water adsorption in anatomical fractions of corn stover. NMR transverse T 2 relaxation time distribution measurements indicate multiple water populations, which vary with anatomical fraction and water adsorption. Measured T 2 data are used to calculate thermodynamic properties of Brunauer-Emmet-Teller adsorption theory using a model to estimate mono and bilayer relaxation. T 2 data are used directly to determine rotational diffusion correlation times indicating adsorption interaction strength. T 1 -T 2 longitudinal-transverse relaxation time correlation measurements quantify differences in the molecular level structural order of the adsorbate surface water as a function of water activity, i.e. relative humidity or water vapor partial pressure. The T 1 /T 2 ratio provides a measure of the surface energy related to the adsorption strength and surface diffusive mobility of the water adsorbate and differentiates the anatomical fractions. Furthermore, the results indicate that direct measurement of NMR relaxation times can be used to characterize corn stover biomass water adsorption, data relevant to processing and handling considerations.

09 BIOMASS FUELS↗

Techno-Economic Case Study: Low-Temperature Conversion Performance Based on Isolated Anatomical Fractions of Corn Stover

This report summarizes analysis conducted to support a case study under the Feedstock Conversion Interface Consortium (FCIC) focused on techno-economic analysis (TEA) modeling to quantify the process yield and resulting process cost impacts for processing isolated anatomical fractions of corn stover through a low-temperature conversion (biochemical) pathway. It is hypothesized that different individual anatomical fractions of corn stover vary in both composition and recalcitrance, giving biorefineries options in whether and how to deal with fractionated or whole biomass feedstock. By quantifying the techno-economic impacts of this variability, we provide actionable information for end users to understand tradeoffs in conversion system yields and economics in considering feedstock processing decisions at the biorefinery gate. For this study, we worked with FCIC researchers to obtain data on the compositional analysis and conversion performance of whole corn stover alongside three individual anatomical fractions (cobs, husks, and stalks) across key steps of the biorefinery conversion process within FCIC’s research scope—pretreatment and enzymatic hydrolysis. This TEA screening assessment highlighted biorefinery economic trade-offs observed through this approach. Namely, relative to processing whole stover biomass, two of the three anatomical fractions for which composition/conversion data were available (cobs and husks) demonstrated the ability to achieve higher fuel yields and lower minimum fuel selling prices (MFSPs), while the third fraction (stalks) led to the opposite result, as a composite reflection of compositional differences and process convertibility.

cost impacts↗

Distribution of Bound and Free Water in Anatomical Fractions of Pine Residues and Corn Stover as a Function of Biological Degradation

Biomass quality is influenced by water’s abundance, distribution, and status in relation to other chemical species within the polymer matrix. Water interacts with polymers that make up the cell walls, and these interactions govern the physical and chemical changes that occur during the storage and preprocessing of biomass feedstocks. Time-domain nuclear magnetic resonance (TD-NMR) was employed to explore variations in the physical constraints of water within the lignocellulosic microstructure in distinct anatomical fractions of biomass and as a function of biological degradation. The Carr–Purcell–Meiboom–Gill sequence, when combined with knowledge of the chemical composition and physical structure of pine residues and corn stover anatomical fractions, gives an accurate measurement of the bound and free water. In this work, the impacts of storage and biological degradation were investigated to elucidate changes in the status and distribution of water within distinct plant tissues. We also investigate how degradation during storage affects water interactions in different pine residues (e.g., bark, branch, and needle) and corn stover (e.g., cob, leaf, and stalk) anatomical fractions using transverse relaxation times (T2). As demonstrated herein, TD-NMR provides quantitative data on lignocellulosic biomass–water interactions within anatomical fractions, which can further aid in the investigation of preprocessing effects on feedstock quality. Our findings suggest that biological heating enhances biomass–water interactions at the cellular and macromolecular scale. In addition, analysis of three-dimensional scanning electron microscopy reconstructions indicates that surface roughness wavelengths align with microscale roughness, suggesting that pine forestry residue and corn stover particles have primarily hydrophobic exterior surfaces. Furthermore, this study offers multiscale insights into understanding the microstructure, wettability, and chemical environment that dictate diffusion, enzyme access, and recalcitrance of lignocellulosic biomass.

09 BIOMASS FUELS↗

Techno-Economic Case Study: Low-Temperature Conversion Performance Based on Isolated Anatomical Fractions of Corn Stover

This report summarizes analysis conducted to support a case study under the Feedstock-Conversion Interface Consortium (FCIC) focused on techno-economic analysis (TEA) modeling to quantify the yield and cost ramifications for processing isolated anatomical fractions of corn stover through a low-temperature conversion (biochemical pathway) biorefinery. It is hypothesized that different individual anatomical fractions of corn stover vary in composition and recalcitrance, such that processing each fraction on its own e.g. through dedicated campaigns may enable economic benefits relative to processing the whole stover material. To investigate this concept, we worked with FCIC researchers to obtain data on compositional analysis, as well as processing conditions and yields, for conversion of whole corn stover plus three individual anatomical fractions (cobs, husks, and stalks) across key steps of the biorefinery conversion process within FCIC research scope, namely pretreatment and enzymatic hydrolysis. After running the data through the TEA models, fractionated cobs and husks achieved higher fuel yields and lower minimum fuel selling prices than whole corn stover, but stalks fared worse than whole stover on both metrics. The most direct takeaway from this assessment is that a biorefinery would stand to benefit economically from maximizing the use of cob and husk fractions while avoiding or minimizing the use of stalks, though recognizing practical constraints with this approach in maintaining an equivalent processing capacity (fixed at 2,000 dry metric tonne per day in all cases).

09 BIOMASS FUELS↗

Effect of particle size and moisture on flow performance of loblolly pine anatomical fractions: Experimental findings and model predictions

The rising energy demand has highlighted biomass as a promising next-generation energy source. However, commercializing biomass-derived energy faces challenges, particularly in handling biomass feedstock. Factors like particle size, shape, moisture content, and surface roughness significantly impact biomass flowability. This study addresses a crucial knowledge gap by examining the effects of particle size and moisture content on the flow behavior and shear properties of different anatomical fractions of loblolly pine (Pinus taeda). The bulk shear behavior was examined using a Schulze ring shear tester, while flow performance was tested through gravity-driven flow experiments in a variable wedge-shape hopper. Results were incorporated into empirical and machine learning-based flow prediction models to evaluate their accuracy and limitations. The study found that samples with higher moisture content show higher unconfined yield strength. The critical arching distance increased with particle size, e.g., from approximately 13 and 33 mm for 2- and 6-mm whole chips, respectively at a 32-degree inclination angle. Conversely, the flow rate decreased for a given hopper opening as particle size increased. For instance, at a 60-mm hopper opening and a 32-degree inclination angle, the mass flow rates for 2- and 6-mm whole chips were 7.83 and 6.42 tonne/h, respectively. The empirical model consistently overpredicted the mass flow rate for all anatomical fractions, while the machine learning model more accurately predicted the central tendency of flow rate but was insensitive to varying tissue proportions. These novel findings provide comprehensive characterization of anatomical fractions, reveal significant combined effects of particle size and moisture content on biomass flow behavior, and demonstrate a better predictive accuracy of a machine learning model, all of which are useful for optimizing material handling strategies and biomass utilization technologies in the industry.

09 - BIOMASS FUELS↗

Let’s Stick Together: Interplay of Moisture, Particle Size, and Anatomical Fraction in the Flowability of Corn Stover Crumbles

Handling of agricultural waste biomass feedstocks (such as corn stover) is a persistent challenge in the production of biofuels and chemicals at integrated biorefineries. Inconsistent flowability and high feedstock variability creates equipment downtime and processing challenges. This work investigates the influence of anatomical fractionation and moisture content on the bulk solids handling behavior of corn stover crumbles. A combination of rotational shear testing, tribological measurements, and surface and sorption characterization techniques (inverse gas chromatography (IGC), dynamic vapor sorption (DVS), and electron microscopy) were used to evaluate the contributions of particle composition, size, and surface properties to flow behavior. Shear and frictional testing revealed that moisture content has the greatest effect on flowability, significantly increasing unconfined yield strength (ƒ c ) and reducing the flow function coefficient (F F C), regardless of anatomical fraction. While differences in surface energy were observed between fractions, particularly in polar contributions (γ AB ), these did not correspond to meaningful differences in flow behavior. Coarser 6 mm particles exhibited poorer flow performance than 4 mm crumbles, likely due to broader particle size distributions and increased particle interlocking. Taken together, these results suggest that anatomical fractionation provides minimal benefit from a bulk handling perspective. Moisture content and particle size heterogeneity dominate handling behavior, reinforcing the utility of unfractionated corn stover in processing environments. These insights can inform the design of more efficient and reliable feedstock processing systems for agricultural biomass in integrated biorefineries.

09 BIOMASS FUELS↗

Feedstock Variability: Differences Among Biomass Anatomical Fractions and Tissues

Corn stover is a versatile feedstock for producing biofuels and other sustainable products. However, its diverse chemical and physical attributes can hinder the processes that convert it into these compounds. The composition of corn stover varies according to factors including corn plant variety, cultivation conditions and maturity at harvest. In essence, corn stover consists of the polymers cellulose, hemicellulose and lignin. The structural core of plant cell walls consists of elongated chains of glucose molecules arranged in bundles of cellulose. Additionally, lower concentrations of hemicellulose, a complex carbohydrate composed of various sugars, form part of the matrix surrounding cellulose bundles. Lignin is a complex aromatic polymer that reinforces plant cell walls. Corn stover generally comprises 40%-50% cellulose, 20%-30% hemicellulose, and 20%-30% lignin. The ratios of these components vary based on the specific type of corn plant and the growth conditions. For example, corn plants cultivated in drought conditions exhibit higher lignin levels than those grown under optimal conditions. The compositional diversity resulting from growth conditions is most pronounced among the different anatomical fractions of the corn plant. Understanding and accommodating the variation among the anatomical fractions of corn stover can enhance the effective utilization of this resource.

09 BIOMASS FUELS↗

Influence of loblolly pine anatomical fractions and tree age on oil yield and composition during fast pyrolysis

Fast pyrolysis of woody materials is a technology pathway for producing renewable fuels and chemicals. This is a presentation of isolating needles, bark, and stemwood from a single tree as well as isolating stemwood and whole tree samples from the same species of tree with different ages and pyrolyzing each individually as well as in mixtures. This gives insight into the role of tree anatomical fractions on the resulting intermediate oil product as well as into interactions between these components. The highest carbon content oil (45.1 wt% as received) was produced from a one-to-one mixture of stemwood and needles, followed by the pure stemwood (43.4–43.8 wt% as received), while the lowest oil carbon content was from a one-to-one blend of bark and needles (26.7 wt% as received). The pyrolysis oil yield (combining oil and aqueous where separation occurred) varied from 54 wt% as received (needles) to 72.3 wt% as received (stemwood). When comparing trees of different ages, we find the change in the ratio of the anatomical fractions is a dominant factor in the product composition and yields, while the product composition and yields vary slightly with tree age when only the stemwood is pyrolyzed. Here, in this study, we present the bench-scale pyrolysis, yields, and product characterization of loblolly pine feedstocks (13- vs. 23 year-old, residues, air-classified residues, whole tree, needles, bark, and stemwood).

09 BIOMASS FUELS↗

Rheological effects of moisture content on the anatomical fractions of loblolly pine (Pinus taeda)

Here, this study focused on assessing the influence of moisture content on the rheological properties of different anatomical fractions of pine residue using the FT4 powder rheometer. Moisture content exhibited some influence on the 2 mm bark and needle fractions, increasing their cohesion, angle of internal friction, unconfined yield strength, and major principal stress. Stem and whole, on the other hand, presented minimal changes upon moisture introduction. All 4 mm fractions did not show many changes in their rheological properties with moisture introduction, which can be due to less particle-particle interactions and consequently reducing any liquid bridging the particles might undergo; however, they were shown to have a more unpredictable behavior compared to the 2 mm analogues (i.e., higher standard deviation) which can be due to a higher degree of particle-interlocking. Out of the three fractions, needle presented the poorest rheological properties for flowability in addition to being susceptible by moisture, unlike other fractions.

36 MATERIALS SCIENCE↗

Low Field NMR Relaxometry Characterization of Water Adsorption in Corn Stover Anatomical Fractions

Low magnetic field 2 MHz NMR relaxometry is applied to measure water adsorption processes of intact corn stover anatomical fractions. Comparison with high magnetic field 250 MHz relaxometry of milled corn stover fractions as a function of water activity, i.e., relative humidity, provides insight into the microstructural changes of the biomass and varying water molecular dynamics during adsorption. As a result, the data presented establish a basis for low field portable NMR of biomass in situ in field and processing environments.

09 BIOMASS FUELS↗

Impact of Tree Age and Anatomical Fraction on Forest Residue Pyrolysis and Hydrotreating

Utilization of cost-advantaged biomass and waste resources to produce clean, domestic biofuels will be a key factor in decarbonizing transportation in the United States. This study investigates how the distribution of anatomical fractions (stem wood, bark, needles, branches) from pine forest residues of different ages impacts pyrolysis and hydrotreating processes, including product composition, carbon efficiency, economics, and overall sustainability. Commercially sourced 13- and 23-year-old loblolly pine residues were chosen to represent available resources; whole tree thinnings, and tops and branches from merchantable timber, respectively. Detailed characterization of the residue samples, product distributions, bio-oil, char, and gas characterization data are presented for 13 experiments, including the individual fractions, blends, and air-classified samples to reduce ash content. Pyrolysis mass balances averaged 97 +/- 3%. As expected, bio-oil yields were lower for the bark, needles, and blends with high proportions of these (53-56% dry basis), and highest for the debarked stem wood (67-71% dry basis). Lower yields were attributed to the high ash content of the needles, but also to the high lignin content in the bark (>50%), which is hypothesized to have led to increased char formation during pyrolysis. Higher-oil yield was generally correlated with total volatiles, hydrogen, oxygen, glucan, and mannan; somewhat correlated with xylan and acetyl content; and negatively correlated with total carbon, fixed carbon, nitrogen, sulfur, and extractives. Air classification of the residues was effective in reducing ash content (1.5% to 0.64%), extractives (~7% to 2%), and sulfur (0.04% to 0.02%), resulting in a small increase in yield, a significant increase in the GC-detectable proportion of oil (27% to 34%) and a net economic benefit. These experimental results were used to conduct technoeconomic and life cycle analyses, which are also summarized here.

biofuels↗

Impact of anatomical fractionation of corn stover on hammer mill throughput and energy consumption

The goal of this Case Study was to quantify the impacts of variable moisture and ash on hammer mill throughput and energy consumption and on loss of very wet stover that causes failures in the first stage grinder and that are not able to be fed to conversion, as compared to a status quo Base Case system. Also considered was convertible carbohydrate content (minimum total carbohydrate specification) and maximum ash content and the delivered feedstock cost impacts of not being able to feed stover not meeting the total carbohydrate specification to the conversion reactor. Laboratory data on the impacts of moisture content and tissue fraction on throughput and energy consumption in a stage 2 hammer mill were received from FCIC Subtask 5.1. Additional air classifier throughput, energy consumption and separation efficiency data were obtained from FCIC Subtask 5.1 for the new air classifier, which has three exit streams (lights, middle and heavies). These data were utilized to develop the necessary response surface equations to perform throughput analysis using discrete event simulation. Because the ash contents and particle sizes had not been analyzed in the laboratory at the time of the model runs, we assumed that the ash distributed proportionally with total mass into the lights and heavies in an air classifier having two exit streams (lights and heavies) and that the lights fraction from the air classifier was not removed. Key takeaways from this Case Study are that due to lower energy consumption, it is more cost effective to hammer mill fractionated corn stover tissues than whole stover. Reduction of grinding energy was significant and may possibly be connected to particle-particle interactions in the grinder that lead to increased residence time of leaves and husks, resulting in decreased throughput and higher generation of fines when milling whole stover. While we did not see significant impacts to throughput, this was due to moisture failures of the first stage grinder in each system dominating failures and downtime. The operating cost savings of reduced grinding energy savings in the second stage hammer mills alone was high enough to offset the added capital cost of the air classifier and extra grinding line.

09 BIOMASS FUELS↗

Mechanical separations of corn stover anatomical fractions in an integrated feedstock preprocessing system: An experimental and data-driven modeling study

High variabilities of material attributes in lignocellulosic biomass present risks for biofuel and biochemical productions and must be mitigated via preprocessing. Since almost no mechanical device is originally designed for processing biomass, how to operate existing apparatuses with efficient performance has not been investigated extensively. This work presents a study on an integrated screening and air classification to separate cobs and stalks from husks and leaves in corn stover. Prototype machine learning models were developed to assess the feasibility of predicting the process outcome based on the measurable parameters. The models trained upon limited experimental data rendered decent predictive accuracy of yield and purity. The experimental data and modeling results collectively suggest decreasing throughput leads to a higher purity. To the contrary, if throughput increases, a lower purity is likely. A possible trade-off between yield and purity of the separated streams indicates the need for optimal combinations of feedstock size, moisture, and throughput to achieve optimized separations. The results of this study also suggest the need to further improve model predictability by developing more accurate formulations for physics governing the integrated unit operations. To accomplish this, additional experimental data needs to be generated for model training.

09 - BIOMASS FUELS↗

Anatomical Fraction segmentation in the biomass bales

The U.S. Department of Energy Bioenergy Technologies Office (BETO) is committed to the development of sustainable, nationwide, commercial biofuel production to displace petroleum-derived fuels, increase domestic energy production, and encourage the creation of a domestic bioenergy and bioproducts industry. Operating a commercial-scale bioenergy operation requires significant technological advancements for determining biomass feedstock quality during the preprocessing stage. Usage of non-food feedstocks- e.g., corn-stover, pine residue, and forest residue - at the biorefineries reduces strain on the food supply chain. But the non-food feedstock heterogeneity- physical size, shape, and chemical composition-poses a significant challenge during milling, conveyance, feeding, and biofuel conversion processes. 3D X-Ray imaging (CT) is capable of distinguishing material features by detecting density and compositional differences. But the inherent complexity introduced during harvesting and bailing makes the reconstruction and interpretation of baled biomass materials from x-ray data time consuming, laborious, and expensive. Feedstocks are low-density materials that produce small contrast differences in the x-ray images. This paper focuses on using the shape and texture properties, using 3D image processing techniques like 3D skeletonization, directional statistics to characterize and extract volumetric content of the different tissue samples in the biomass bales.

09 BIOMASS FUELS↗

Impact of Anatomical Fractionation of Corn Stover on Hammer Mill Throughput and Energy Consumption

The goal of this Case Study was to quantify the impacts of variable moisture and ash on hammer mill throughput and energy consumption and on loss of very wet stover that causes failures in the first stage grinder and that are not able to be fed to conversion, as compared to a status quo Base Case system. Also considered was convertible carbohydrate content (minimum total carbohydrate specification), maximum ash content and the delivered feedstock cost impacts of not being able to feed stover that did not meet the total carbohydrate specification to the conversion reactor. Laboratory data on the impacts of moisture content and tissue fraction on throughput and energy consumption in a stage 2 hammer mill were received from FCIC Subtask 5.1: Preprocessing, Corn Stover Preprocessing (Neal Yancey and Sergio Hernandez, INL). Additional air classifier throughput, energy consumption and separation efficiency data were obtained from FCIC Subtask 5.1 (Neal Yancey, INL) for the new air classifier, which has three exit streams (lights, middle and heavies). These data were utilized to develop the necessary response surface equations to perform throughput analysis using discrete event simulation. Because the ash contents and particle sizes had not been analyzed in the laboratory at the time of the model runs, we assumed that the ash distributed proportionally with total mass into the lights and heavies in an air classifier having two exit streams (lights and heavies) and that the lights fraction from the air classifier was not removed.

ash content↗

Discrete element modeling of irregular-shaped soft pine particle flow in an FT4 powder rheometer

Pine residues are a commonly used biomass feedstock that consists of different anatomical fractions, each with distinct particle characteristics. Here, in this work, an experiment-informed discrete element model is developed to investigate the flowability of pine residues in an FT4 rheometer. Multi-sphere particles with distinct particle attributes are created to model each anatomical fraction type. A systematic analysis of specimens with varying particle characteristics (e.g., anatomical fraction type, particle shape, and size) is conducted to elucidate the relationship between particle attributes and flowability. The results show that stems recorded the highest axial force and torque and, correspondingly, the highest flow energy, which is attributed to their high stiffness and interlocking effect. Increasing their percentage in the mixture increases the flow energy while increasing needles tends to decrease flow energy. Knowledge gained in this study on the flow of anatomical fractions is important for the efficient and robust processing of pine residues.

09 BIOMASS FUELS↗

Impacts of Biologically Induced Degradation on Surface Energy, Wettability, and Cohesion of Corn Stover

The impacts of biological degradation on surface area, surface energy, wettability, and cohesion of anatomically fractionated (i.e., leaf, stalk, and cob) and bulk corn stover are presented in this study. The physical, thermal and chemical properties of corn stover are critical material attributes that not only influence the mechanical processing and chemical conversion of corn stover, but also the bulk solids handling and transport. The measured surface areas were observed to be dependent on the degree of biological degradation (mild vs. moderate vs. severe) and on the anatomical fraction. The surface area of the bulk corn stover samples increased with the degree of biological degradation. The leaf fraction was the most sensitive to biological degradation, resulting in an increase in surface area from 0.5 m 2 /g (mildly degraded) to 1.2 m 2 /g (severely degraded). In contrast, the surface area of the cob fraction remained relatively unaffected by the degree of biological degradation (i.e., mildly degraded–0.55 m 2 /g, severely degraded–0.40 m 2 /g. All biologically degraded samples resulted in significant changes to the surface chemistry (evidenced by an increase in surface energy. As a general trend, the surface energy of bulk corn stover increased with the degree of biological degradation—the same trend was observed for the leaf and stalk anatomical fractions; however, the surface energy for the cob fraction remained unchanged. Wettability, calculated from surface energy, for bulk corn stover samples did not reveal any discernable trend with the degree of biological degradation. However, trends in wettability were observed for the anatomical fractions, with wettability increasing for the stalk and leaf fractions, and decreasing for the cob fraction. Excluding the cob fraction, the work of cohesion increased with the degree of biological degradation. Understanding the impacts of biological degradation on the physical, chemical and thermal properties of corn stover offers insights to improve the overall operational reliability, efficiency and economics of integrated biorefineries.

09 BIOMASS FUELS↗