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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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This study developed machine learning models using a dataset consisting of 963 entries with 24 variables both numerical and categorical to predict H2 production of plastic waste and biomass gasification. The models were utilized to optimize feedstock and process conditions through genetic algorithm to maximize hydrogen production.
This study evaluates cover crops in Washington State (WA) as a renewable feedstock for hydrothermal liquefaction (HTL), supported by techno-economic (TEA) and life cycle (LCA) analysis. In the Pacific Northwest, fallow land is the common winter practice, generating no income for farmers. Over three years, field trials at two representative sites—Puyallup (cool, wet) and Othello (irrigated, no-till)tested triticale, hairy vetch, crimson clover, winter pea, and fava bean preceding cash crops. Biomass yields, composition, soil impacts, and net revenue were assessed across removal treatments. HTL conversion produced 32–37 wt% biocrude, lower than 48 wt% for sewage sludge, with modeled cradle-to-grave carbon intensities of 26–31 g CO 2 e/MJ and minimum fuel selling prices (MFSP) of $\$$6.75–$\$$7.18 per gallon gasoline equivalent (GGE), comparable to other lignocellulosic feedstocks. No significant changes were observed in soil carbon, nitrogen, or subsequent cash crop yields after cover crop removal. Farmer profitability was possible, particularly for triticale and hairy vetch at $\$$60 per dry ton. To address seasonal variability, blending with wastewater sludge was evaluated. All scenarios delivered >70 % carbon intensity reductions relative to fossil fuels, and with Renewable Identification Number (RIN) credits, MFSPs below $\$$2.5 GGE were achievable. These results demonstrate that cover crops can generate new revenue streams for farmers while serving as a flexible, low-carbon feedstock. Integrating cover crops with waste biomass offers a practical pathway to expand the bioeconomy and support year-round renewable fuel production.
This report integrates the results of a series of studies and workshops to address the question: Can a nuclear-assisted biofuels system enable liquid biofuels as the economic low-carbon replacement for all liquid fossil fuels and hydrocarbon feedstocks and simultaneously enable negative carbon emissions? “Economic” is defined as economically competitive relative to other low-carbon replacement options for crude oil. “All” refers to the capability to replace the 18 million barrels of oil per day used by the United States. “Nuclear-assisted” refers to the provision of massive quantities of low-carbon heat and hydrogen at the refinery to fully utilize the carbon content of the cellulosic biomass feedstocks for liquid hydrocarbon production. A system is proposed that decarbonizes about half of the U.S. economy while improving long-term soil productivity and sequestering carbon from the atmosphere. In the U.S. almost half the energy consumed by the final customer is in the form of liquid hydrocarbons produced from crude oil. Liquid hydrocarbons are used as (1) an energy source, (2) a method for daily-to-seasonal energy storage, (3) a chemical feedstock, (4) a chemical reducing agent, (5) a method to enhance high-temperature heat transfer in many furnaces and industrial processes and (6) other purposes. As a consequence, the U.S. consumes ~18 million barrels of crude oil per day to produce liquid hydrocarbons. While there are substitutes for liquid hydrocarbons for some applications, our assessment is that the costs and difficulty will dramatically increase if liquid hydrocarbon use goes much below the equivalent of 10 million barrels per day of crude oil. New uses of liquid hydrocarbons to partly replace coal and natural gas could increase demand beyond the equivalent of 10 million barrels of oil per day. One can produce and burn liquid hydrocarbons from biomass without any net addition of carbon dioxide to the atmosphere. Plants grow by removing carbon dioxide from the atmosphere; thus, burning biomass does not result in any net addition of carbon dioxide to the atmosphere. Biomass is typically 40% oxygen. To remove this oxygen to create hydrocarbon liquids, there are two options. The first option is to use biomass as (1) a feedstock, (2) an energy source to operate the process and (3) a supply of carbon to remove the biomass oxygen as carbon dioxide. The second option is to use external heat and hydrogen to remove the oxygen as water and produce liquid hydrocarbons. The use of massive quantities of external heat and hydrogen for hydrocarbon liquid fuels production reduces the biomass feedstock per unit of liquid hydrocarbon product by more than a factor of two reducing land use by more than a factor of two. Many cellulosic feedstocks unsuitable for liquid hydrocarbon production are viable feedstocks with external heat and hydrogen inputs. As a result, there is sufficient cellulosic feedstocks to meet U.S. and global liquid fuels hydrocarbon demand without significant impacts on food and fiber prices. The heat and hydrogen (heat plus electricity) are produced using base-load nuclear power plants—the most economic form of nuclear energy. If low-price natural gas, there is also the option of producing hydrogen from natural gas with sequestration of the carbon dioxide. The biomass is locally processed in depots to produce commodity feedstocks that can be shipped long distances to large biorefineries (250,000 barrels per day, oil equivalent) similar to existing refineries except modifications of front-end processes. The depot system enables local recycle of nutrients back to the soil. The biorefinery can produce variable quantities of liquid hydrocarbon fuels and carbon dioxide for sequestration enabling removal of carbon dioxide from the atmosphere. Preliminary estimates are that the liquid hydrocarbon costs are equivalent to crude oil at between $60 and $70 per barrel. The largest cost is for hydrogen with biomass feedstocks and refinery costs a smaller fraction of the total cost.
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Populus is a promising lignocellulosic feedstock for biofuels and bioproducts. However, the cell wall biopolymer lignin is a major barrier in conversion of biomass to biofuels. To investigate the variability and underlying genetic basis of the complex structure of lignin, a population of 409 three-year-old, naturally varying Populus trichocarpa genotypes were characterized by heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR). A subsequent genome-wide association study (GWAS) was conducted using approximately 8.3 million single nucleotide polymorphisms (SNPs), which identified 756 genes that were significantly associated (−log 10 ( p -value)>6) with at least one lignin phenotype. Several promising candidate genes were identified, many of which have not previously been reported to be associated with lignin or cell wall biosynthesis. These results provide a resource for gaining insights into the molecular mechanisms of lignin biosynthesis and new targets for future genetic improvement in poplar.
This work aims to understand the pelleting characteristics of 2-inch top-pine residue blended with switchgrass at high moisture content. The process variables tested are blend moisture content, length-to-diameter (L/D) ratio in the pellet die, and the blend ratio. A flat-die pellet mill was also used in this study. The pine and switchgrass blend ratios that were tested include (1) 25% 2-inch top pine residue with 75% switchgrass; (2) 50% 2-inch top pine residue with 50% switchgrass; and (3) 75% 2-inch top pine residue with 25% switchgrass. The pelleting process conditions tested included the L/D ratio in the pellet die (i.e., 1.5 to 2.6) and the blend moisture content (20 to 30%, w.b.). Analysis of experimental data indicated that blending 25% switchgrass with 75% 2-inch top pine residue and 50% switchgrass with 50% 2-inch top pine residue resulted in pellets with a bulk density of >550 kg/m3 and durability of >95. Optimization of the response surface models developed for process conditions in terms of product properties indicated that a higher L/D ratio of 2.6 and a lower blend-moisture content of 20% (w.b.) maximized bulk density and durability. Higher pine in the blends improved the pellet durability and reduced energy consumption. Tests were also conducted on blends of pine and switchgrass using a pilot scale pellet mill by varying the blend moisture content and compression ratio of the pellet die. Pelleting tests on pure pine and switchgrass and their blends in a pilot scale ring die pellet mill with a throughput of 1 ton/h has indicated pellets with durability >500 kg/m3 and durability in the range of >90 and >95 %. The demonstration of high moisture pelleting of blends of 2- and 6-inch top pine residues and switchgrass blends indicated that good quality pellets with durability >90 % and bulk density of >500 kg/m3 can be produced.
Carbon composites are attractive to a variety of high-impact applications, such as carbon fibers, batteries, and vehicle parts, due to their multifunctional properties. The properties of carbon are highly dependent on the allotrope the carbon takes and the functionality, impurities, and defects contained within the structure. The increase in demand for sustainable carbon sources in energy storage devices motivates interest in understanding synthesis parameters of lignin value-added products. Also, as the dependence on oil for fuel decreases, alternative sources for carbon in many applications will be needed. In this work, the thermochemical conversion of lignin powders from different feedstocks was evaluated via small and wide-angle X-ray scattering techniques to resolve the amorphous, disordered, and crystalline domains present in the lignin carbons. Scattering analyses indicated an evolution of hierarchical structures along with an increase in ordered domains as a function of carbonization temperature. Qualitative and quantitative methods were used to describe isotropic scattering intensity profiles at multiple length scales. The use of power law models in the mesoscopic region served as the basis to describe morphological changes related to structural features, for example, graphene stacking, degree of roughness, and surface fractals. Kraft softwood and switchgrass produced carbon powder with the most crystalline domains and the least surface roughness. Softwoods reached the highest degree of crystallinity followed by switchgrass samples and had less variability in particle sizes. These results suggest lignin carbons extracted from softwoods and switchgrass are viable substitutes for graphite. Interpretation of X-ray scattering data from lignin carbon powders elucidates feedstock- and processing-dependent morphological features across multiple length scales providing a straightforward framework to evaluate the feasibility of leveraging lignin carbons for producing tunable application-specific materials.
Metal powders are a fundamental starting point for fabricating many types of nuclear targets. Elemental powder properties can differ drastically between batches, even when using the same method. Therefore, the variation in morphology and the size of metal powders can cause variable quality and produce inconsistent results with what are otherwise proven target manufacturing techniques. Additive manufacturing has additional requirements for higher quality and more uniform feedstock. The production of spheroidized powders with uniform, reproducible properties and a narrow size distribution represents unexplored opportunities for experiments. These opportunities include experimenting with solid metals that can now flow like liquids, new options for powder handling and dispensing, and new target fabrication methods using additive manufacturing. The Stable Isotope Materials and Chemistry Group at Oak Ridge National Laboratory obtained an AMAZEMET rePowder ultrasonic metal atomization tool for creating limited batches of fully dense, free flowing, spherical powders with a narrow size distribution of extremely rare materials. Early results are presented with materials that were produced. The team explores the anticipated limits of this instrument with extremely rare materials (e.g., enriched stable isotopes) and highlights research into new fabrication techniques that provide additional options benefitting the international nuclear target community.
Offshore synthetic fuel production and marine carbon dioxide removal can be enabled by direct ocean capture, which extracts carbon dioxide from the ocean that then can be used as a feedstock for fuel production or sequestered underground. To maximize carbon capture, plants require a variety of low-carbon energy sources to operate, such as variable renewable energy. However, the impacts of variable power on direct ocean capture have not yet been thoroughly investigated. To facilitate future deployments, a generalizable model for electrodialysis-based direct ocean capture plants is created to evaluate plant performance and electricity costs under intermittent power availability. This open-source Python-based model captures key aspects of the electrochemistry, ocean chemistry, post-processing, and operation scenarios under various conditions. To incorporate realistic energy supply dynamics and cost estimates, the model is coupled with the National Renewable Energy Laboratory’s H2Integrate tool, which simulates hybrid energy system performance profiles and costs. This integrated framework is designed to provide system-level insights while maintaining computational efficiency and flexibility for scenario exploration. Initial evaluations show similar results to those predicted by the industry, and demonstrate how a given plant could function with variable power in different deployment locations, such as with wind energy off the coast of Texas and with wind and wave energy off the coast of Oregon. The results suggest that electrochemical systems with greater tolerances for power variability and low minimum power requirements may offer operational advantages in variable-energy contexts. However, further research is needed to quantify these benefits and evaluate their implications across different deployment scenarios.
Large-scale algae production has garnered interest due to its potential as a biofuel feedstock. Previous research assessing the profitability of algae products has been mostly based on values averaged over time, but algae production and resulting financial returns exhibit significant variability due to weather and fluctuations in selling prices for algae-based products. In other sectors, producers often reduce weather- and market price-related financial risk with financial instruments such as insurance, but little research has been performed on the design of insurance products to protect algae producers. Furthermore, this study develops a novel index-based insurance instrument that pays-out during unfavorable weather and market conditions, then explores the instrument's effectiveness, combined with a cash reserve, in reducing revenue stream variability for an algae producer. Results indicate that a biophysically based index-insurance product tailored to the specific financial risks in algae production can reduce variability in net revenues and can do so at a lower cost than relying solely on cash reserves, the most common financial risk management tool. Assessing the performance of index-insurance in algae production is particularly timely given the passage of the 2018 Farm Bill, which newly opens opportunities for the USDA to provide crop insurance to algae producers.
There has been growing interest in integrating bio-derived composites into Large-format additive manufacturing (LFAM) feedstocks to reduce the use of petroleum-derived materials and reduce the overall carbon footprint of LFAM. However, these materials present unique challenges during manufacturing due to their variability, which can lead to unintended deformations and failures attributable to suboptimal process conditions. While numerical modelling has been extensively employed to simulate numerous manufacturing processes, its application in LFAM with bio-derived composites remains limited. This study addresses this gap by systematically developing a numerical model to simulate the LFAM process using bio-based materials, specifically wood fiber-reinforced polylactic acid (PLA/WF). Experimental investigations were conducted to characterise the thermal and mechanical properties of additively manufactured PLA/WF specimens. Numerical simulations were performed to predict temperature profiles and deformations during LFAM. The effect of varying infill patterns, internal structures, and tool paths on the temperature distribution and deformation of printed parts was explored using the developed model. This article aims to advance the utilisation of bio-derived composites in LFAM systems and provide a comprehensive understanding of the LFAM process. The findings offer valuable insights for optimising process parameters and enhancing the performance of LFAM with bio-based composites.
Genome-wide association studies are powerful tools to elucidate the genome-to-phenome relationship. In order to explain most of the observed heritability of a phenotypic trait, a sufficient number of individuals and a large set of genetic variants must be examined. The development of high-throughput technologies and cost-efficient resequencing of complete genomes have enabled the genome-wide identification of genetic variation at large scale. As such, almost all existing genetic variation becomes available, and it is now possible to identify rare genetic variants in a population sample. Rare genetic variants that were usually filtered out in most genetic association studies are the most numerous genetic variations across genomes and hold great potential to explain a significant part of the missing heritability observed in association studies. Rare genetic variants must be identified with high confidence, as they can easily be confounded with sequencing errors. In this study, we used a pre-filtered data set of 1,014 pure Populus trichocarpa entire genomes to identify rare and common small genetic variants across individual genomes. We compared variant calls between Platypus and HaplotypeCaller pipelines, and we further applied strict quality filters for improved genetic variant identification. Finally, we only retained genetic variants that were identified by both variant callers increasing calling confidence. Based on these shared variants and after stringent quality filtering, we found high genomic diversity in P. trichocarpa germplasm, with 7.4 million small genetic variants. Importantly, 377k non-synonymous variants (5% of the total) were uncovered. We highlight the importance of genomic diversity and the potential of rare defective genetic variants in explaining a significant portion of P. trichocarpa's phenotypic variability in association genetics. The ultimate goal is to associate both rare and common alleles with poplar's wood quality traits to support selective breeding for an improved bioenergy feedstock.
The processing of used nuclear fuels and related materials is often complex and variable. The ability to quickly optimize conditions to the material being processed can aid in increasing efficiency and safety, but requires very quick determination of the conditions present in the feedstock, the process, and the product. Furthermore, accurate quantification of materials such as enriched uranium and plutonium aids in maintaining material accountancy and avoiding nuclear proliferation risks. Traditional analytical methods require process samples to be collected and analyzed in a laboratory, which often takes days to weeks. Online monitoring is suitable for collecting this information nearly instantaneously, enabling much faster optimization of the process or detection of material diversion. Online monitoring is also beneficial as it is typically based on robust and nondestructive analytical methods, so no material is removed as samples. This review examines online monitoring relevant to used nuclear fuel processing for the determination of both chemical and physical parameters. The chemical parameters include quantities such as concentration, isotopic composition, and speciation. These values are often well suited to spectroscopic or spectrometric measurements as they are fast, nondestructive, and easily implemented in an online manner. Physical quantities are often more varied and include temperature, pressure, tank fill levels, and others. Due to the specificity of these quantities, specialized instrumentation is often used. However, this instrumentation is often amendable to online monitoring.
Splat quenching as a high throughput rapid solidification screening tool is evaluated. Samples were made using known alloys (SS316, IN625, Ti-5553) to evaluate and establish the microstructures for a variety of alloy systems as well as the predicted cooling rates. The samples are inductively heated and levitated prior to being struck between two platens that produce a high contact pressure and a thin sample resulting in cooling rates on the order of 10 6 to 10 7 K/s. Process parameters were evaluated with analytical models in addition to numerical simulations to provide an effect of process variables such as substrate material, melt superheat, and platen velocity on the resulting solidification. The splat thickness was found to be controlled by platen velocity, melt superheat, as well as the feedstock volume. The sample thickness is the key controlling factor for varying the average cooling rate experienced by the splat quenched sample. The splat quenching techniques can reach regions of rapid solidification space that meet and exceed laser and electron beam techniques across the sample. In conclusion, the results of the study provide a useful foundation in understanding the splat quenching technique and its potential as a low effort tool to explore rapid solidification effects on alloys.
The flowability of biomass is an indicator of how amenable biomass is to handling. The flowability measurements are often determined with empirical or tertiary experiments. This status quo impedes employing engineering principles to advance the design and operation of biomass handling systems. It is imperative to establish an experimental protocol minimizing empirical aspects of flowability characterization to account for the variability of biomass. This study demonstrates the operational principles of the large chamber cubical triaxial tester and the procedure of triaxial tests to quantify bulk flow behaviors of two milled biomass feedstocks, namely corn stover 2 mm (CS) and Douglas fir 1 mm (DF). The Mohr-Coulomb (MC), Drucker-Prager (DP) and modified Cam Clay (mCC) models are calibrated for both biomasses. Analysis indicates that CS will exhibit a cohesive flow with a larger cohesion coefficient of MC (3.8 ± 3.5 kPa) than DF (0.42 ± 0.9 kPa) and a larger d value of DP (6.9 kPa) than DF (0.0 kPa), respectively. CS exhibits a higher spring-back index of mCC (0.39 ± 0.05) than DF (0.27 ± 0.05) also suggesting handling issues, which agrees with the experiences in the industry. This study demonstrates the capability of a CTT in a quantitative investigation of biomass handling characteristics.
Nanocellulose is a promising and sustainable feedstock for developing advanced and functional materials. However, the characteristics of nanocellulose, such as crystallinity, surface energy, and aspect ratio, can vary depending on biomass source and pretreatment methods, leading to variable performance of the nanocellu-lose-based materials. In this study, cellulose nanocrystals (CNCs) were isolated from hemp and poplar using totally chlorine free (TCF) peracetic acid and sodium chlorite delignification and bleaching pretreatments to probe the influences of biomass source and treatment methods on the isolation and characteristics of CNCs. Our results showed that hemp and poplar were almost completely delignified by peracetic acid treatment, whereas sodium chlorite treatment left 5%–6% lignin in the pulp. The yields of CNCs from raw hemp and poplar biomass ranged from 9.8% to 21.9% and 10.9% to 28.3%, respectively, depending on the treatment methods. The dimensions of CNCs from TCF-treated biomass generally maintained a larger width and aspect ratio than those from sodium chlorite-treated biomass. The poplar-derived CNCs exhibited slightly higher crystallinity of 53%–58% than hemp-derived CNCs of 49%–54%. The zeta potential of the CNCs, ranging from -20.1 mV to -31.1 mV, ensured a well-dispersed aqueous solution. The surface energy (dispersive energy of 40–80 mJ/m2 and specific energy of 2–10 mJ/m2), water interaction, and thermal stability of the CNCs were comparable, regardless of the biomass source and pretreatment methods. Our finding suggests that the TCF technique with peracetic acid treatment is a promising delignification and bleaching approach to obtain cellulose-rich pulps from herbaceous and hardwood biomass for nanocellulose isolation.
Modern automotive applications demand lightweight, multifunctional materials to reach mileage goals and natural fiber reinforced composites (NFRCs) are one of the classes of materials proposed as a solution. NFRCs exhibit good vibration damping properties and have low density, but are often limited by processing challenges, poor-fiber matrix compatibility and variable performance. Herein, we investigate non-woven wet-lay of comingled banana fiber (BF), recycled glass fiber (rGF), and polypropylene (PP) fibers to in situ sizing and preparation of composite feedstocks for compression molding. BF and rGF hybrids were prepared by stacking rGF layers during compression molding to produce composites with various fiber ratios. The effect of fiber content, in-situ sizing and ratio of BF to rGF on tensile, flexural and vibration damping performance are investigated. Key results are the significant increase in tensile strength by in situ sizing (40 % sized at 60 wt% BF) and in flexural modulus (+58 % sized at 60 wt% BF) and flexural strength (+41 % sized 60 wt% BF) compared to the unsized equivalent. For BF-rGF hybrid composites with40 wt% total fiber content, flexural strength and modulus were improved by 51 % and 231 % respectively for a 1:1 ratio BF:rGF compared to BF reinforced system. Lastly, identifying the cross-over point where damping and stiffness are optimized for a hybrid composite. These findings demonstrate that these composites can be used as alternative to synthetic fiber or mineral filled composites in automotive applications, particularly where weight reduction, vibration damping and stiffness are desired.
The release of leachates from intact coal ash impoundments is a concern due to the enrichment and mobilization of toxic elements such as arsenic (As) and selenium (Se). This study aims to explore the intrinsic properties of coal fly ash that correlate with the relative leachability of As and Se. We performed leaching experiments with 52 fly ash samples collected from 15 different U.S. power plants and representing coal feedstocks from the three major domestic regions. We assessed the mobilization potential of As and Se in fly ash based on standardized leaching protocols and performed multivariate and lasso regression analyses to explore correlations of leachable As and Se contents with characteristics such as major element contents, loss on ignition, and pH. The results of regression models indicated that major elements (Fe, Ca, and Al) for a wide range of fly ashes can serve as predictor variables for the leaching potential of As but not for Se. LOI and pH were not important predictive variables in the models. Both regression approaches resulted in relatively strong fits for leachable As (correlation coefficient R 2 = 0.78 for both models) compared to models for leachable Se (R 2 = 0.49). Overall, these results suggest that correlation models combined with on-site elemental analysis with portable analyzers may enable a screening method for leachable As in coal ash.