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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unveiling Feedstock Variability: Insights into Corn Stover Conversion - Part I: Physicochemical Properties and Self-Degradation

Transforming agricultural waste into biofuels and bioproducts is crucial to advancing a low-carbon bioeconomy. However, the inherent variability in the composition and quality introduces uncertainties in the conversion efficiency and poses challenges in process development. Through integrating a high-throughput conversion system, material characterization techniques, and advanced data analysis tools, this study investigates the variability of corn stover and its subsequent impacts on carbohydrate conversion. The findings reveal that indoor storage substantially reduces the moisture and ash content and soil contamination, while other properties remain largely unchanged. Self-degradation due to microbial activity during storage decreases the carbohydrate content of corn stover but enhances glucose and xylose yields. A negative correlation is observed between sugar yields and lignin content across samples with varying ash and moisture content. The inhibitory effect of lignin diminishes in self-degraded samples likely due to the disrupted cell wall structure. Although self-degradation slightly increases cellulose crystallinity, no strong correlation was observed between the crystallinity and sugar yield. Hot water pretreatment under mild conditions effectively mitigates inherent variability, consistently improving the sugar yield from corn stover by up to 50%. By elucidating the feedstock variability and its impact on convertibility, these findings offer valuable insights into appropriate feedstock handling and management, highlighting potential strategies to address variability challenges.

09 BIOMASS FUELS↗
DOE OSTI2022

Process-based modeling of soil nitrous oxide emissions from United States corn fields under different management and climate scenarios coupled with evaluation using regional estimates

Direct emissions of soil nitrous oxide during a growing season (N 2 O gs ) can be quantified with process-based models considering interactions between management, climate, and soil moisture when key data are available. We used an adapted “parameterized CENTURY/DAYCENT-model” ( p CENTURY) calibrated with crop growth and soil organic matter decay coefficients at the county-level for the estimation of N 2 O gs in the United States Corn Belt. Model estimated N 2 O-emissions from corn-based biofuels scenarios considering crop rotation, fertilizer inputs, tillage, and weather were compared against meta-summary of field observations from 55 studies. Both model and meta-summary ranked N 2 O gs -emissions to be corn > wheat > soybean phase while model likely underestimated cover crop N 2 O gs -emissions. The N 2 O gs -emissions and the associated emission factors (EFs) were modeled and summarized to be greater after anhydrous ammonia than urea application and from conventional tilled than non-tilled fields. Modeled and observed N 2 O gs -emissions after organic and inorganic fertilizer amendment did not differ due to high variability associated with the treatments. However, the organic fertilizer associated EFs were greater according to meta-summary data because of N input rates. Regionalized weather scenarios indicate hotspots for N 2 O gs -emissions can occur where crop N uptake is limited during dry years and in eastern states also during normal or wet seasons. The p CENTURY-derived N 2 O gs EFs (0.91 ± 0.19%) for counties investigated were only slightly lower than literature (1.07 ± 0.57%) or Tier-1 (1%) values. Our preliminary evaluation of regional soil moisture estimates showed reasonable agreement between monthly soil moisture estimates and the North American Soil Moisture Dataset during the growing season, but overestimation of soil moisture in winter-spring can influence the estimates of annual N 2 O emissions so future work is needed to calibrate soil moisture-associated model parameters. Our work provided scenario-based estimates of climate and management impacts on soil N 2 O gs -emissions together with valuable spatial insights into EFs that will be improved by more accurate information of fertilizer inputs and more temporally refined model evaluation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Techno‐economic assessment of single‐stream feedstock logistics supply chain for corn stover and grain

Abstract The state‐of‐technology for corn stover harvest is a multi‐pass system that collects the stover after grain harvest. An alternative is a single‐stream system where the grain and stover are harvested as a bulk material co‐stored and preserved by anerobic fermentation, and finally, co‐transported to a biorefinery. In the present work, four single‐pass whole‐plant bulk systems were compared with a conventional multi‐pass bale system. The single‐stream systems consisted of the harvest of corn grain and a portion of the stover fraction. Four machine configurations were simulated. This work predicted that a multi‐pass bale system would result in a material cost of 111.80 $2021 Mg –1 stover DM delivered to the biorefinery gate. Alternatively, the lowest cost single‐stream system was the self‐propelled forage harvester (SPFH) configured with the whole‐plant header, which delivered feedstock for 74.76 $2021 Mg stover DM –1 . In addition to machine configuration, a sensitivity analysis was performed to understand important drivers of feedstock cost. These analyses revealed that feedstock cost increased with moisture content, fertilizer price, and biorefinery size, and decreased with harvest season length, crop yield, and grower participation. This work demonstrated that single‐stream systems could reduce corn stover feedstock costs in comparison with state‐of‐technology systems. © 2022 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2025

Understanding the Effects of Ash Content on Various Pretreatment Technologies for the Bioconversion of Corn Stover

Here, the study aimed to examine the effects of adding biomass ash on the biochemical processes involved in fermentable sugar production. Corn stover was pretreated using several methods—hot water, dilute acid, alkaline, γ-valerolactone, and ionic liquid methods, each examined with ash loadings of 7.18% and 21.07%. The findings demonstrated that increased ash content adversely affected both pretreatment and enzymatic hydrolysis. Specifically, the total sugar yield was 3 to 16% lower at the higher ash content across all pretreatment methods, and up to 4.01% lower during enzymatic hydrolysis. For acidic pretreatment, the sugar yield decreased as ash content increased. In contrast, ash content had a lesser impact on alkaline pretreatment compared to acidic pretreatment. For example, using corn stover with an ash content as high as 22.65% resulted in only a 2.90% decrease in total sugar yield compared to corn stover without added ash. Further, the primary reasons for the reduced sugar yield in higher ash biomass during acidic pretreatments were likely the neutralizing effect of the ash and decreased acid access to the substrates. During enzymatic hydrolysis, ash reduced the sugar yield by limiting enzyme access to cellulose.

09 BIOMASS FUELS↗
DOE OSTI2021

New strategy for liquefying corn stover pellets

The movement of solid material into and between unit operations within a biorefinery is a bottleneck in reaching design capacity, with formation of biomass slurries needed to introduce feedstock. Corn stover slurries have been achieved from dilute acid, pretreated materials resulting in slurry concentrations of up to about 150 g/L, above which flowability is compromised. We report a new strategy to liquefy corn stover at higher solids concentration (300 g/L) by initially cooking it with the enzyme mimetic maleic acid at 40 mM and 150°C. This is followed by 6 h of enzymatic modification at 1 FPU (2.2 mg protein)/g solids, resulting in a yield stress of 171 Pa after 6 h and 58 Pa in 48 h compared to 6806 Pa for untreated stover. Mimetic treatment of corn stover pellets minimizes the inhibitory effect of xylo-oligomers on hydrolytic enzymes. Furthermore, this strategy allows for the delivery of solid lignocellulosic slurry into a pretreatment reactor by pumping, improving operability of a biorefinery.

09 BIOMASS FUELS↗
DOE OSTI2020

Production of levulinic acid and biocarbon electrode material from corn stover through an integrated biorefinery process

To overcome the inefficient biomass conversion, waste generation, and lack of co-production in biorefineries, an integrated process was proposed for the conversion of corn stover into levulinic acid and biocarbon electrode material. Corn stover was pretreated through hydrothermal process using 0.45 wt% K 2 CO 3 which removed 76 wt% lignin and 85 wt% xylan while preserving 83 wt% glucan. This was followed by acid hydrolysis to produce levulinic acid at varying H 2 SO 4 concentrations and reaction time in a batch reactor at 190 °C. At a reaction time of 5 min in 2 wt% H 2 SO 4 , 35.8 wt% and 30 wt% glucan in raw and pretreated corn stover was converted to levulinic acid, respectively. The residue from acid hydrolysis was converted into biocarbon for supercapacitor electrodes via a two-step thermal activation process which showed a specific capacitance of 120 F g -1 . The proposed integrated biorefinery concept provides multiple value-added products for a greater financial and environmental sustainability.

09 BIOMASS FUELS↗
DOE OSTI2021

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↗
DOE OSTI2022

Image Analysis for Rapid Assessment and Quality-Based Sorting of Corn Stover

Imaging in the visible spectrum is a low-cost tool that can be readily deployed for in-field or over-belt monitoring of biomass quality for bio-refining operations. Rapid image analysis coupled with innovative preprocessing may reduce the impacts of feedstock variability through identification of contaminants or other material attributes to guide selective sorting and quality management. Image analysis was employed to evaluate the quality of corn stover in red-green-blue (RGB) chromatic space. This study used controlled, bench-scale imaging as a proof-of-concept for rapid quality assessment of corn stover based on variations in material attributes, including chemical and physical attributes, that relate to biological degradation and soil contamination. Additionally, logistic regression-based classification algorithms were used to develop a method for biomass screening as a function of biological degradation or soil contamination. This study demonstrated the use of image analysis to extract features from RGB color space to investigate variations in critical material attributes from chemical composition of corn stover. Fourier transform infrared (FT-IR) suggested a correlation between red band intensity and biological degradation, while detailed surface texture analysis was found to distinguish among variations in ash. These insights offer promise for development of a rapid screening tool that could be deployed by farmers for in-field assessment of biomass quality or biorefinery operators for in-line sorting and process optimization.

09 BIOMASS FUELS↗
DOE OSTI2018

Ethanol Production from Corn Fiber Separated after Liquefaction in the Dry Grind Process

Conversion of corn fiber to ethanol in the dry grind process can increase ethanol yields, improve coproduct quality and contribute to process sustainability. This work investigates the use of two physio-chemical pretreatments on corn fiber and effect of cellulase enzyme dosage to improve ethanol yields. Fiber separated after liquefaction of corn was pretreated using (I) hot water pretreatment (160 °C for 5, 10 or 20 min) and (II) wet disk milling and converted to ethanol. The conversion efficiencies of hot water pretreated fiber were higher than untreated fiber, with highest increase in conversion (10.4%) achieved for 5 min residence time at 160 °C. Disk milling was not effective in increasing conversion compared to other treatments. Hydrolysis and fermentation of untreated fiber with excess cellulase enzymes resulted in 33.3% higher conversion compared to untreated fiber.

09 BIOMASS FUELS↗
NASA NTRS2017

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

evapotranspiration↗
NASA NTRS2020

Adaptation in U.S. Corn Belt Increases Resistance to Soil Carbon Loss With Climate Change

Increasing the amount of soil organic carbon (SOC) has agronomic benefits and the potential to mitigate climate change. Previous regional predictions of SOC trends under climate change often ignore or do not explicitly consider the effect of crop adaptation (i.e., changing planting dates and varieties). We used the DayCent biogeochemical model to examine the effect of adaptation on SOC for corn and soybean production in the U.S. Corn Belt using climate data from three models. Without adaptation, yields of both corn and soybean tended to decrease and the decomposition of SOC tended to increase leading to a loss of SOC with climate change compared to a baseline scenario with no climate change. With adaptation, the model predicted a substantially higher crop yield. The increase in yields and associated carbon input to the SOC pool counteracted the increased decomposition in the adaptation scenarios, leading to similar SOC stocks under different climate change scenarios. Consequently, we found that crop management adaptation to changing climatic conditions strengthen agroecosystem resistance to SOC loss. However, there are differences spatially in SOC trends. The northern part of the region is likely to gain SOC while the southern part of the region is predicted to lose SOC.

Soil Organic Carbon (SOC)↗
DOE OSTI2022

Corn Stover Fractions from Different Harvest Conditions

There is a lot of variability in biomass. This variability can make it difficult to process the biomass into a consistent format for handling and conversion. As a result, bioenergy feedstocks are often under- or over-converted. Corn stover in particular can be harvested in different ways, baled in different ways, and has significant intrinsic variability due to its very different anatomies. These factors could cause variability in the fractions of corn stover. The fractions of corn stover are leaf, husk, cob, and stalk.

09 BIOMASS FUELS↗
DOE OSTI2023

A global meta‐analysis of cover crop response on soil carbon storage within a corn production system

Abstract By influencing soil organic carbon (SOC), cover crops play a key role in shaping soil health and hence the system's long‐term sustainability. However, the magnitude by which cover crops impacts SOC depends on multiple factors, including soil type, climate, crop rotation, tillage type, cover crop growth, and years under management. To elucidate how these multiple factors influence the relative impact of cover crops on SOC, we conducted a meta‐analysis on the impacts of cover crops within rotations that included corn ( Zea mays L.) on SOC accumulation. Information on climatic conditions, soil characteristics, management, and cover crop performance was extracted, resulting in 198 paired comparisons from 61 peer‐reviewed studies. Over the course of each study, cover crops on average increased SOC by 7.3% (95% CI, 4.9%–9.6%). Furthermore, the impact of cover crop–induced increases in percent change SOC was evaluated across soil textures, cover crop types, crop rotations, biomass amounts, cover crop durations, tillage practices, and climatic zones. Our results suggest that current cover crop–based corn production systems are sequestering 5.5 million Mg of SOC per year in the United States and have the potential to sequester 175 million Mg SOC per year globally. These findings can be used to improve carbon footprint calculations and develop science‐based policy recommendations. Taken altogether, cover cropping is a promising strategy to sequester atmospheric C and hence make corn production systems more resilient to changing climates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Using waste CO 2 from corn ethanol biorefineries for additional ethanol production: life‐cycle analysis

Abstract Corn ethanol plants generate high‐purity carbon dioxide (CO 2 ) while producing ethanol. If that CO 2 could be converted into ethanol by carbon capture and utilization technologies it would be possible to increase ethanol production more than 37% without additional corn grain inputs. Gas fermentation processes use microbes to convert carbon‐containing gases into ethanol and so have the potential to be used with the CO 2 from biorefineries for this purpose. However, as CO 2 utilization technologies for converting thermodynamically stable CO 2 are typically energy intensive, it is necessary to evaluate the related life‐cycle greenhouse gas (GHG) emissions (carbon intensities or CIs) to see whether there are actual emission reduction benefits. In this study, we evaluate the CIs of ethanol produced from high‐purity CO 2 in corn ethanol plants by gas fermentation plus electrochemical reduction. Our analysis shows that the sources of electricity and hydrogen are key drivers of CO 2 ‐based ethanol's GHG emissions. With wind electricity, the design cases show the potential of near‐zero CI ethanol (1.1 g CO 2 e/MJ), but that can increase to up to 331–531 g CO 2 e/MJ when today's U.S. Midwest electricity mix is used. To avoid the renewable electricity intermittency issue, we considered a power purchase agreement option using wind electricity 40% of the time and using the regional mix for the rest, which provides a 42% GHG emission reduction from the CI of gasoline. © 2020 The Authors and UChicago Argonne, LLC, Operator of Argonne National Laboratory. Biofuels, Bioproducts and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.

09 BIOMASS FUELS↗
DOE OSTI2018

Physicochemical, Antimicrobial and Cytotoxic Characteristics of Corn Starch Film Containing Propolis for Wound Dressing

Modern dressings increase the rate of wound healing rather than just covering them. Dressing can protect the injured skin and keep it appropriately moist to speed up the healing process. In this study, the ethanolic extract of propolis loaded with corn starch was successfully prepared using solvent casting. Characterizations of the samples performed in respect to their mechanical properties were examined by scanning electron microscopy, contact angle, and attenuated total reflectance—fourier transform infrared spectroscopy, as well as antimicrobial capacities. The MTT assay using fibroblast cells showed the cell viability of corn starch in the ethanolic extract of propolis wound dressing. The results showed that by increasing the amount of ethanolic propolis extract from 0.25 to 1%, the tensile strength and the Young’s modulus of the samples were decreased, the elongation at the break increased about 15% as compared to the control films, and the contact angle properties were detected by a slightly hydrophobic character of the films in the antibacterial activity against Escherichia coli and Staphylococcus aureus even at low ethanolic extract of propolis concentrations (1%), mainly due to its phenolic compounds. Therefore, ethanolic extract of propolis loaded with corn starch film will be a potential candidate for wound dressing and skin tissue engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗
DOE OSTI2021

An adaptive adversarial domain adaptation approach for corn yield prediction

Recently, statistical machine learning and deep learning methods have been widely explored for corn yield prediction. Though successful, machine learning models generated within a specific spatial domain often lose their validity when directly applied to new regions. To address this issue, we designed an unsupervised adaptive domain adversarial neural network (ADANN). Specifically, through domain adversarial training, the ADANN model reduced the impact of domain shift by projecting data from different domains into the same subspace. Also, the ADANN model was designed to be trained in an adaptive way, which guaranteed the model can learn the domain-invariant features and perform accurate yield prediction simultaneously. Informative variables including time-series vegetation indices and sequential weather observations were first collected from multiple data sources and aggregated to the county level. Then, we trained the ADANN model with the extracted features and corresponding reported county-level corn yield from the U.S. Department of Agriculture (USDA). Finally, the trained model was evaluated in four testing years 2016–2019. The U.S. corn belt was used as the study area and counties under study were grouped into two diverse ecological regions. Overall, the experimental results showed that the developed ADANN model had better performance than three other state-of-the-art machine learning models in both local experiments (train and test in the same region) and transfer experiments (train and test in different regions). As the first study using adversarial learning for crop yield prediction, this research demonstrates a novel solution for improving model transferability on crop yield prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Microwave-assisted co-gasification of mixed plastics and corn stover: A synergistic approach to produce clean hydrogen

Co-gasification of waste plastic and corn stover into hydrogen is an effective way of reducing hydrogen cost and carbon footprint. However, current gasification technologies are energy intensive and cannot accommodate flexible feedstock. Microwave gasification offers several advantages including higher H 2 yield and enhanced selectivity to syngas over tars. Herein this work presents parametric optimization study of microwave co-gasification of mixed plastics and corn stover for hydrogen-rich syngas. High hydrogen yields of 30.5 mmol H2 /g feed at 700 °C were obtained using a microwave reactor, as opposed to 0.9 mmolH 2 /g feed at 700-950 °C with conventional heating. Hydrogen yields are >98% of the theoretical extractable hydrogen from feedstock. Microwaves enhanced plastic and corn stover synergy and reduced tar yields. H-poor carbon formation resulting from the dehydrogenation of tar and coke, and light olefins decomposition, triggered by the external microwave electric fields, allowed further cracking of intermediate hydrocarbons to produce additional H 2 .

30 DIRECT ENERGY CONVERSION↗