Tracking renewable carbon in bio-oil/crude co-processing with VGO through 13C/12C ratio analysis
Not Available
Li, Zheng-Hua (ORCID:000000030946500X)↗
SEARCH · Engineering Papers
Results for “Feedstock Analysis”
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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Analysis of the Solid Products from the OSCAR and the AOWG Trash Processing Systems
Two trash conversion systems that process space logistical trash for conversion into gases and liquids have minor solid product formation consisting of primarily high carbon ash, inorganic salts, and aluminum metal flakes. These solid products necessarily comprise part of the system output because the thermal degradation processes intentionally operate at temperatures below aluminum vaporization and do not convert all solid inorganics or carbon-based compounds into gaseous compounds (i.e., CO 2 or CH 4 ). The two systems included the Orbital Syngas/Commodity Augmentation Reactor (OSCAR) combustion system funded by the NASA Space Technology Mission Directorate (STMD) located at NASA’s Kennedy Space Center, and the Advanced Organic Waste Gasifier (AOWG) steam reforming system developed by Pioneer Astronautics in Lakewood, Colorado, and funded by the NASA Small Business Innovation Research (SBIR) Exploration Systems Development Mission Directorate (ESDMD). OSCAR residual solids were collected from suborbital flight and ground-based laboratory testing, while all AOWG samples were collected from ground testing. This report discusses the solid product characterization, including elemental analyses performed with scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDS), and a surface chemistry performed with x-ray photoelectron spectroscopy (XPS). A particle size analysis was performed with sieves, followed by SEM analyses. These analyses were performed to elucidate what high value products can be extracted or utilized from the solid products for follow on infusion into chemical feedstocks, manufacturing additives, or in-situ construction-based material needs.
OSCAR↗
A Study of Particle Size Metrics Using Non-Spherical Feedstock for Metal Additive Manufacturing
The goal of this work was to determine which standard particle size metric derived from optical analysis most closely approximates the sieved weight percent of irregularly shaped powder intended to be used for directed energy deposition. In this investigation, equivalent circle diameter, maximum diameter, minimum diameter, and perimeter are used as metrics to “virtually sieve” the particles in samples of irregularly shaped powder into the following particle size bins: <45 µm, 45 µm - 150 µm, and >150 µm. The percentage in the 45 µm - 150 µm bin is then compared to the weight percent of the powder mechanically sieved into this size range. The absolute difference between the virtually sieved percentage and the mechanically sieved percentage was assessed for 81 samples of mechanically-generated stainless steel 316L powder all produced under different processing conditions in an oscillation ball mill. This difference was found to be on average, the least with the minimum diameter assessed as an area percentage, followed by the equivalent diameter assessed as an area percentage, and then the maximum diameter assessed as a percentage of the total number of particles ranked third. These findings may be used by powder production process engineers and quality assurance personnel to assist in process control as more diverse additive manufacturing feedstocks become utilized.
Marcus Jackson↗
Techno-economic uncertainty analysis of wet waste-to-biocrude via hydrothermal liquefaction
Not Available
Li, Shuyun↗
Near-infrared spectroscopy as a green analytical tool for sustainable biomass characterization for biofuels and bioproducts: An overview
Biomass, a widely used renewable energy source, requires characterization to optimize biofuel and bioproduct processes, customize feedstocks, and ensure economic and environmental sustainability. Conventional wet-chemistry methods for biomass analysis are slow, expensive, and require significant reagents and skilled personnel. In contrast, near-infrared (NIR) spectroscopy, a faster, cost-effective, and reagent-free green technology, enables non-destructive biomass analysis with minimal sample preparation. This study provides an overview of the fundamentals of NIR spectroscopy and explores its recent applications for analyzing various biomass properties important to the biofuel and bioproduct industry. The study also critically evaluates the challenges and opportunities of using NIR spectroscopy for biomass analysis. This review aims to guide future research for rapid and high throughput characterization of biomass in the biomass industry, supporting the United Nations’ sustainable development goal (SDG) 7: producing affordable and sustainable energy.
Biofuels↗
Data and Code for 'GHG Mitigation and Land Use Change Implications of Sustainable Aviation Fuel in the United States'
BEPAM, Biofuel and Environmental Policy Analysis Model, models the agricultural sector and determines economically optimal land-use and feedstock mix at the US scale by maximizing the sum of agricultural sector consumers’ and producers’ surplus subject to various resource balances, land availability, and technological constraints under a range of biomass prices, from zero to $140 Mg-1 over the 2016-2030 period. Here BEPAM is used to model SAF production using energy crops and crop residues. BEPAM uses the GAMS format and uses yield and GHG balance projections from the biogeochemical model, DayCent.
09 BIOMASS FUELS↗
Processing Municipal Solid Waste for Conversion to Jet Fuel (Final Technical Report)
This final report describes the successful demonstration of AI‑assisted waste sorting and a novel pressurized solids feed system to enable conversion of non‑recyclable municipal solid waste to jet fuel under DOE Award DE‑EE0009265. Results include improved feedstock purity and variability reduction, lab‑scale testing, and technoeconomic and life‑cycle assessments.
09 BIOMASS FUELS↗
Economic perspective of ethanol and biodiesel coproduction from industrial hemp
Herein, the economics of producing biofuels from an industrial hemp (Cannabis sativa) genotype e 19m96136 was investigated. A lignocellulosic biofuel plant, hourly consuming 85 metric tons of hemp biomass was modeled in SuperPro Designer®. The integrated bioenergy plant produced hemp biodiesel and bioethanol from lipids and carbohydrates, respectively. The structural composition of the industrial hemp plant was analyzed in a previous study. The data obtained was used to simulate feedstock composition in SuperPro Designer®. The simulation results indicated that Hemp containing 2% lipids can yield up to 3.95 million gallons of biodiesel annually. On improving biomass lipid content to 5 and 10%, biodiesel production increased to 9.88 and 19.91 million gallons, respectively. The breakeven unit production cost of hemp biodiesel with 2, 5, and 10% lipid containing hemp was $18.49, $7.87, and $4.13/gallon, respectively. The biodiesel unit production cost when utilizing 10% lipid-containing hemp was comparable to soybean biodiesel at $4.13/ gallon. Furthermore, sensitivity analysis revealed the possibility of a 7.80% reduction in unit production cost upon a 10% reduction in hemp feedstock cost. Furthermore, industrial hemp was capable of pro- ducing between 307.80 and 325.82 gallons of total biofuels per hectare of agricultural land than soybean.
09 BIOMASS FUELS↗
Analysis as a Key Guiding Tool for Waste Carbon Utilization
Over a billion metric tons of waste and biomass are projected to be available in a future mature market in the United States. These resources represent an opportunity to decouple chemical and polymer production from conventional fossil fuel feedstocks, but such a broad solution space can also make for challenging decision-making. This talk will provide researchers with an introduction to key analysis techniques such as techno-economic analysis, life cycle assessment, and material flow analysis: how they are conducted and how they can be used to benchmark the costs, environmental impacts, and circularity of new innovations as well as to identify opportunities for prioritization and optimization. Using a series of examples related to plastic recycling and chemical manufacturing, we will explore how analysis can guide where and how to leverage waste carbon in supply chains towards a future circular economy.
chemical↗
Machine learning for surrogate process models of bioproduction pathways
Technoeconomic analysis and life-cycle assessment are critical to guiding and prioritizing bench-scale experiments and to evaluating economic and environmental performance of biofuel or biochemical production processes at scale. Traditionally, commercial process simulation tools have been used to develop detailed models for these purposes. However, developing and running such models can be costly and computationally intensive, which limits the degree to which they can be shared and reproduced in the broader research community. This study evaluates the potential of an automated machine learning approach to develop surrogate models based on conventional process simulation models. The analysis focuses on several high-value biofuels and bioproducts for which pathways of production from biomass feedstocks have been well-established. The results demonstrate that surrogate models can be an accurate and effective tool for approximating the cost, mass and energy balance outputs of more complex process simulations at a fraction of the computational expense.
09 BIOMASS FUELS↗
Environmental and Economic Assessments and Uncertainties of Multiple Lignocellulosic Biomass Utilization for Bioenergy Products: Case Studies
Life-cycle assessment (LCA) and techno-economic analysis (TEA) were applied to assess the economic feasibility and environmental benefits of utilizing multiple biomass feedstocks for bioenergy products under three different technological pathways with consideration of uncertainties. Three cases were studied for the production of pellets, biomass-based electricity, and pyrolysis bio-oil. A Monte Carlo simulation was used to examine the uncertainties of fossil energy consumption, bioenergy conversion efficiency, stochastic production rate, etc. The cradle-to-gate LCA results showed that pellet production had the lowest greenhouse gas (GHG) emissions, water and fossil fuels consumption (8.29 kg CO2 eq (equivalent), 0.46 kg, and 105.42 MJ, respectively). The conversion process presented a greater environmental impact for all three bioenergy products. When producing 46,929 Mg of pellets, 223,380 MWh of electricity, and 78,000 barrels of pyrolysis oil, the net present values (NPV) indicated that only pellet and electricity production were profitable with NPVs of $1.20 million for pellets, and $5.59 million for biopower. Uncertainty analysis indicated that pellet production showed the highest uncertainty in GHG emission, and bio-oil production had the least uncertainty in GHG emission but had risks producing greater-than-normal amounts of GHG. Biopower production had the highest probability to be a profitable investment with 85.23%.
09 BIOMASS FUELS↗
Autothermal Chemical Looping Oxidative Dehydrogenation of Ethane: Redox Catalyst Performance, Longevity, and Process Analysis
Energy-efficient upgrading of stranded ethane from shale gas to olefins holds the promise of increasing the supply of useful chemical feedstocks while reducing flaring-based CO 2 emissions. Previously, we reported a modular ethane-to-liquids (M-ETL) system based on a chemical looping oxidative dehydrogenation (CL-ODH) scheme. In this article, we present long-term (>1200 h) results of Li 2 CO 3 -promoted La 0.8 Sr 0.2 FeO 3 corresponding to ~4125 CL-ODH cycles in a large laboratory-scale packed bed reactor. Temperature monitoring along the bed length confirmed the exothermicity of both the oxidative dehydrogenation and regeneration steps, enabling an autothermal operation. Product gas analysis indicated that the redox catalyst maintains a high C 2+ selectivity (~90%) and ethane conversion (~67%) at 735 °C after continuous cycling of >1000 h. As a result, product distributions and heats of reactions were used to update our M-ETL process model for revised techno-economic analysis, demonstrating that the current system is economically viable with relatively low required selling prices across a wide range of operating scenarios.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Data from Economic Perspective of Ethanol and Biodiesel Coproduction from Industrial Hemp
In this study, the economics of producing biofuels from an industrial hemp (Cannabis sativa) genotype – 19m96136 was investigated. A lignocellulosic biofuel plant, hourly consuming 85 metric tons of hemp biomass was modeled in SuperPro Designer®. The integrated bioenergy plant produced hemp biodiesel and bioethanol from lipids and carbohydrates, respectively. The structural composition of the industrial hemp plant was analyzed in a previous study. The data obtained was used to simulate feedstock composition in SuperPro Designer®. The simulation results indicated that Hemp containing 2% lipids can yield up to 3.95 million gallons of biodiesel annually. On improving biomass lipid content to 5 and 10%, biodiesel production increased to 9.88 and 19.91 million gallons, respectively. The breakeven unit production cost of hemp biodiesel with 2, 5, and 10% lipid containing hemp was $18.49, $7.87, and $4.13/gallon, respectively. The biodiesel unit production cost when utilizing 10% lipid-containing hemp was comparable to soybean biodiesel at $4.13/gallon. Furthermore, sensitivity analysis revealed the possibility of a 7.80% reduction in unit production cost upon a 10% reduction in hemp feedstock cost. Furthermore, industrial hemp was capable of producing between 307.80 and 325.82 gallons of total biofuels per hectare of agricultural land than soybean.
Conversion↗
Integrating Experiments, Simulations, and Artificial Intelligence to Accelerate the Discovery of High-Performance Green Composites
The imperative for incorporating greener materials into the aerospace industry necessitates addressing significant challenges associated with the microstructural variability exhibited by recycled and sustainable feedstocks. In this study, we propose an integrated methodology that combines experimental investigations, finite element analysis, and artificial intelligence to develop sustainable composites with consistent properties. Our approach utilizes a pipeline comprising an automated mechanical tester, a finite element method simulator, and a convolutional neural network predictor to identify and optimize fabrication parameters for achieving desired mechanical characteristics in composites. By employing a nested-loop pipeline, our methodology improves sample efficiency, accuracy, and effectively bridges the gap between simulations and real-world performance. This unique methodology offers a promising avenue for facilitating the adoption of aerospace-appropriate green composites.
Athanasiou, Christos↗
Analysis of Using a Hybrid ZIRCEX Process to Generate High-Assay Low-Enriched Uranium (HALEU) - 20158
Idaho National Lab (INL) is investigating the feasibility of providing High-Assay Low Enriched Uranium (HALEU) by recovering Highly Enriched Uranium (HEU) from spent nuclear fuel (SNF) and downblending the HEU with natural, low-enriched, or depleted uranium (NU, LEU, or DU). That investigation identified that significant quantities of HALEU could be produced with a Hybrid ZIRCEX process to further advanced reactor research while reducing INL's environmental liability. Many new advanced reactor designs are being developed with improved safety, efficiency, and economics. Most require nuclear fuel with U-235 enrichment between 5% and 20%, which is defined as HALEU. Although technically feasible, there is no current domestic capability to make HALEU in the US. While it is anticipated that industry will provide HALEU through commercial enrichment once advanced reactors mature, until a market is established, an interim source of HALEU is needed to enable research and demonstration. An interim source of HALEU could be provided by recovering the HEU in some DOE-managed SNF and downblending it to between 5% and 20% using the Hybrid ZIRCEX Process. ZIRCEX is a dry head-end process to remove cladding (zirconium or aluminum) from SNF. Drying of the SNF is needed prior to introduction to ZIRCEX. After cladding removal, uranium and fission products in the bed material are oxidized and elutriated. In a Hybrid ZIRCEX process, the HEU process stream is sent to a very compact, modular solvent extraction process for uranium purification. The uranyl nitrate from solvent extraction is denitrated and calcined to produce a HALEU product ready for fuel fabrication. The long-lived fission products from solvent extraction are immobilized in glass using a small in-can melt. By removing the cladding before dissolution, the volume of glass waste is reduced by a factor of up to 300 times (when compared to not removing the cladding from the fuel). Other radioactive wastes from the process could be disposed of as Class A or Class B low-level waste. In addition to producing HALEU for advanced reactors, consumption of SNF would reduce DoE's environmental liability. Incorporating low-enriched spent fuel (versus exclusive use of LEU, DU, or NU) into the downblending scheme could reduce the SNF inventory even further. Several downblending and enrichment scenarios using INL fuels were investigated in this study. The results of this analysis show that the Hybrid ZIRCEX process could make a significant contribution to needed HALEU feedstock and reduce the environmental liability of managing SNF at INL. (authors)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
A simplified integrated framework for predicting the economic impacts of feedstock variations in a catalytic fast pyrolysis conversion process
Feedstock attributes of lignocellulosic biomass, such as particle size, compositional makeup, and moisture content, can vary substantially even within pre-processed materials and have a significant effect on conversion in fast pyrolysis-based processes. However, the economic impacts of these attributes are not well understood. To address this, biomass deconstruction phenomena captured with a versatile particle-scale simulation were linked to techno-economic impacts via reduced-order models. Parametric analysis of the particle-scale model, which was validated using literature data, was used in combination with multiple linear regression models to develop correlations between feedstock attributes and yields of pyrolysis oil, gas, and char. Yields were then correlated with the minimum fuel selling price (MFSP) using a techno-economic model, bridging the gap between physics-based biomass conversion simulations and predictions of MFSP for a catalytic fast-pyrolysis process. Empirical correlations derived from the literature regarding the impact of mineral matter (ash) on oil yield were also considered. The model correlations deployed in the integrated framework capture the impacts of variation in feedstock attributes on the MFSP. Variations in ash were shown to have the biggest impact, varying MFSP by -13%/+22% due to catalytic effects and lower relative amounts of convertible lignocellulosic material. It was also found that, if ash can be controlled to low levels, the increased extractives in forest residues can help compensate for some yield losses associated with increased ash. As a result, other inputs considered (particle size, moisture content, and reactor temperature) had relatively negligible effects on process economics within the ranges analyzed considering particle-scale effects alone.
BIOMASS FUELS↗
Using Separation-Enhanced Isotope Ratio Mass Spectrometry to Enable Increased Renewable Carbon Content in Transportation Fuels (CRADA 525)
Stable isotope ratio measurements of carbon atoms using isotope ratio mass spectrometry (IRMS) can be an effective tool for quantifying biogenic carbon in co-processed fuels, with results approaching the precision and accuracy of accelerator mass spectrometry (AMS). The lower cost of an IRMS may enable deployment to refineries, improving access and analysis turnaround times (≤2 hours), and, by extension, provide data that can allow process optimization to maximize renewable carbon in desired refinery products. This project explored the integration of chemical separation with IRMS analyses to enable highly detailed tracking of biogenic carbon into fuel product streams separated by boiling point range, chemical class, or specific compound. Forty-nine fuels and fuel components of fossil and biogenic origin, spanning gasoline and diesel boiling point ranges, were received from three refiners and were analyzed for their δ 13 C values via IRMS. Results spanned a 13 C range from ca. 10‰ to 44‰ and reflect materials derived from sustainable sources (e.g., C4 or C3 plants, animal-based pathways, syngas) or from fossil-derived fuels. Common ranges are approximately 18‰ to 9‰ and approximately 30‰ to 20‰ for C4 and C3 plants, respectively, and approximately 34‰ to 24‰ and approximately 70‰ to 33‰ for petroleum-derived fuels and methane, respectively. Fuel-like standards were developed and tested using direct-injection elemental analyzer (EA) IRMS for liquid fuels. This method was compared with the published methods, yielding statistically similar results. Four blend curve sets were produced ranging from 0% to 100% of a fuel containing biogenic carbon, focusing on 0% to 10% biogenic carbon. Linear fits were the most applicable for two of the four blend curve sets; however, two sets were found to exhibit slightly quadratic behavior, which was more pronounced in low biogenic blend samples, necessitating second-order fits. The origin of the slight quadratic behavior remains unclear; however, the discussion points to possible interpretations. CanmetENERGY thoroughly characterized a majority of the samples using one- and two-dimensional gas chromatography (GC and GC×GC, respectively) and other analyses. Selected samples were subjected to solid phase extraction (SPE) for saturate, olefin, aromatic, and polar (SOAP) analysis, and the resulting solvent-diluted fractions containing saturates and aromatics were returned to Pacific Northwest National Laboratory (PNNL), where the solvent was removed via evaporation or physical separation using GC techniques. Characterization and separations provided an understanding of saturate and aromatic content, as well as boiling point ranges for each sample and sample fraction. Samples resulting from SPE were examined using EA-IRMS and gas chromatography combustion IRMS (GC-C-IRMS) analyses. Both approaches suggest that the range in values between end-members can be increased by selecting the paraffinic or aromatic fraction of the end-member or by selecting among individual compounds resulting from GC separation of the paraffinic fractions. Considerable work remains to put these approaches into practice and statistically validate the benefit for using a fraction or individual compound over bulk analysis of a sample. However, initial results suggest that separations provide advantages for samples having blend ratios of less than 10% biogenic blendstocks. 13 C results showed statistically similar biofuel blend results to those obtained at PNNL, although additional work is needed to obtain better reproducibility. Select samples were sent to Los Alamos National Laboratory (LANL) for IRMS measurements and Beta Analytics for AMS measurements. This work suggests that IRMS and AMS yield closely comparable results and in some circumstances, IRMS could serve as a surrogate for AMS. While additional work is needed to better resolve statistical advantages for separations and better show the comparable nature of IRMS and AMS in both the biogenic carbon analysis of bulk chemical classes, initial results from this study suggest that these should be pursued in order to proliferate this approach for quantifying biogenic carbon in transportation fuels to the refinery level, thereby potentially enabling process optimization in co-processing scenarios.
09 BIOMASS FUELS↗
Techno-economic and life-cycle analysis of strategies for improving operability and biomass quality in catalytic fast pyrolysis of forest residues
Many of the challenges faced by the first commercial biorefineries were associated with feedstock handling, quality, and cost. Strategies are needed to enable further expansion of biorefineries and meet the growing demand for bio-based fuels and products. Here, we examine 2 key feedstock challenges and mitigation strategies in the context of a catalytic fast pyrolysis (CFP) biorefinery: (1) the operability of the feed system, which may be improved by modifying the minimum particle size fed to the reactor, and (2) the quality of the biomass, which may be improved by employing air classification to remove undesirable material and increase fuel yields. We conduct techno-economic analysis (TEA) and life-cycle analysis for these strategies, employing a discrete event simulation model for biomass preprocessing combined with a series of correlations developed from literature data and a rigorous CFP conversion model. Our results highlight the importance of balancing increased cost and material losses from preprocessing against improved operability and fuel yields. Economics and sustainability were optimized when operating at the lowest minimum particle size, emphasizing the importance of minimizing material losses while maintaining the operability of the process. Economically, additional costs and material losses from air classification could be acceptable due to improved biomass conversion, and an optimum air classification speed was identified; however, the fuel GHG emissions were minimized when air classification was not used. Valorizing material removed during preprocessing as a coproduct could improve economics and sustainability, decreasing the burden of material losses.
09 - BIOMASS FUELS↗