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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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New perspective on glycoside hydrolase binding to lignin from pretreated corn stover
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Comprehensive characterization of non-cellulosic recalcitrant cell wall carbohydrates in unhydrolyzed solids from AFEX-pretreated corn stover
Inefficient carbohydrate conversion has been an unsolved problem for various lignocellulosic biomass pretreatment technologies, including AFEX, dilute acid, and ionic liquid pretreatments. Previous work has shown 22% of total carbohydrates are typically unconverted, remaining as soluble or insoluble oligomers after hydrolysis (72 h) with excess commercial enzyme loading (20 mg enzymes/g biomass). Nearly one third (7 out of 22%) of these total unconverted carbohydrates are present in unhydrolyzed solid (UHS) residues. The presence of these unconverted carbohydrates leads to a considerable sugar yield loss, which negatively impacts the overall economics of the biorefinery. Current commercial enzyme cocktails are not effective to digest specific cross-linkages in plant cell wall glycans, especially some of those present in hemicelluloses and pectins. Thus, obtaining information about the most recalcitrant non-cellulosic glycan cross-linkages becomes a key study to rationally improve commercial enzyme cocktails, by supplementing the required enzyme activities for hydrolyzing those unconverted glycans.
Propionic acid production from corn stover hydrolysate by Propionibacterium acidipropionici
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Soil Microbe Sequence Data: Influence of Shrub Willow Buffers Strategically Integrated in an Illinois Corn-Soybean Field on Soil Health and Microbial Community Composition
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Improving Biomass and Ethanol Yield by Intercropping a Winter Cereal with Corn
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Leveraging 2-D GC-MS and Machine Learning to Explore the Corn Metabolome [Slides]
Abstract not provided.
U.S. Average Corn Ethanol Production Baseline for 45Q Life Cycle Analysis Version 1.0 (2018-2022)
U.S. Average Benchmark life cycle inventory documentation for ethanol production for calendar years 2018 - 2022. The documentation includes a technical report describing data sources and statistical methods used and an Excel file showing calculations. The calculations performed are used in the 45Q benchmark json-ld dataset, compatible with the NETL CO2U LCA Guidance Toolkit. Summary impact results will be included in the NETL CO2U LCA Documentation Spreadsheet within the Toolkit. To access the model referenced in the report, please visit https://www.netl.doe.gov/energy-analysis/details?id=55ab21f1-9238-4b63-9a7a-ae1a4cfa7b05.
CORN (Crop Optimization Realized through Neuralnets)
Traditional models of predicting plant traits are limited because they often rely on linear assumptions that do not fully capture the complexity of biological interactions and DNA-based markers which are static across environments. This project generated a set of RNA-based data from large multi-environment field trials and combined it with advanced machine learning techniques to account for these complex interactions and improve the accuracy of predictions.
Life Cycle Inventory Data for the Anaerobic Digestion of Corn Stover and Stillage to produce Renewable Natural Gas
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Ensiled Wet Storage Accelerates Pretreatment for Bioconversion of Corn Stover
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Effects of Storage Moisture Content on Corn Stover Biomass Stability, Composition, and Conversion Efficacy
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Wet Corn Stover Storage: Correlating Fiber Reactivity With Storage Acids Over a Wide Moisture Range
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Characterization and Deconstruction of Oligosaccharides in Black Liquor From Deacetylation Process of Corn Stover
The National Renewable Energy Laboratory (NREL) developed low severity Deacetylation and Mechanical Refining (DMR) process under atmospheric pressure, generates highly fermentable, low toxicity sugar syrups and highly reactive lignin streams. The dilute alkali deacetylation step saponifies acetyl groups from the hemicellulosic fraction of biomass into a black liquor waste stream that also contains solubilized acetic, ferulic, p-coumaric acids, lignin-carbohydrate complexes (LCCs), oligosaccharides, and solubilized lignin. Valorization of the soluble components in the deacetylation black liquor waste stream requires characterization of the black liquor. Our analyses show that glucan, xylan, and lignin were three main components in black liquor and the oligosaccharides in the black liquor were mainly dimers and trimers with arabinofuranose branch groups mainly on the xylooligomers. GPC chromatograms showed that the black liquor also contained oligomeric lignin moieties with molecular weights ranging between 1,800 and ~10,000 Da. Enzymatic saccharification of the black liquor was conducted based on the compositional and structural information. Incorporation of commercial cellulase and hemicellulase enzyme preparations with various accessary enzymes showed up to 57% hydrolysis of the xylooligosaccharides in the black liquor to monomeric sugars, which could be used to improve biorefinery carbon utilization in biological fermentations to improve end product fuel or bioproduct volumes per metric ton of biomass processed. This is so far the first study about characterizing DMR black liquor and exploring breaking down the oligosaccharides in black liquor for potential use.
Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain
Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meet conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions.
Estimation of Corn Latent Heat Flux from High Resolution Thermal Imagery
Crop evapotranspiration (ET), which is directly related to latent heat flux, is also a key indicator in determining the water status of crops. In order to estimate the latent heat flux, two-source energy balance (TSEB) models have been developed for thermal imagery from satellite platforms. However, because of the coarse resolution of thermal sensors on the satellite, distinguishing soil and vegetation is difficult which complicates the calculation process and introduces errors in latent heat estimates. In this research, high-resolution thermal datasets (0.05 m) and corresponding RGB datasets (0.03 m) were used for calculating crop latent heat flux using an adapted TSEB model. The RGB datasets were used for supervised classification of soil and vegetation, and the classification results were then used to filter the thermal mosaics to separate vegetation and soil temperatures. The vegetation temperature is used for calculating latent heat flux and the results are validated against the ground reference measurements of latent heat using a handheld porometer. The objective of this research is to introduce a workflow including an adapted TSEB model which is customized for high resolution thermal images from unmanned aircraft systems (UAS) to estimate the latent heat flux of row crops in agricultural fields. Nine dates of data collection in 2018 and 2020 have been evaluated and the root mean square error (RMSE) varies between 16 to 106 W/m2 depending on the days after planting (DAP) and the time of measurement for each day. The results indicate that the workflow introduced here is able to provide estimates of instantaneous latent heat flux (evapotranspiration) measurements for row crops in agricultural fields which will enable people to make reliable decisions related to irrigation scheduling.