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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantitative Determination of Biomass-derived Renewable Carbon in Fuels from Coprocessing of Bio-oils in Refinery Using a Stable Carbon Isotopic Approach

Increasing renewable carbon incorporation into conventional fuels through coprocessing with vacuum gas oil (VGO, a petroleum refining feedstock) is a critical step in biofuels development, scaling-up, adoption and associated GHG reduction. Optimization of the co-processing parameters maximizes incorporation of the renewable carbon in the fuel products. Quantitative determination of the renewable carbon content in the co-processed products provides direct evaluation of the parameters. The co-processing bio-oil with VGO through hydrocracking (HC) or fluid catalytic cracking (FCC) system resulted in carbon isotopic fractionation that prevented the direct use of the isotope mixing model for quantifying the renewable carbon. Here, we report an algorithm of using a stable carbon isotope approach to quantify the renewable carbon content in co-processing biofuel products through high-precision ?13C analysis. A controlled experiment carried out by blending a fossil diesel (-29.013‰) with a bio-diesel (-30.099‰) at various blending levels up to 98.0/2.0 wt% is presented and has demonstrated the applicability of this approach. The carbon isotope fractionation factors for the bio-oil co-processing were obtained by using a 14C-derived isotope-mixing model. The ?13C method was tested by co-processing 13C-labeled bio-crude and natural woody biomass-derived fast pyrolysis (FP) and catalytic fast pyrolysis (CFP) bio-oils with VGO. The results were verified by 14C accelerator mass spectrometry (AMS) method (ASTM-D6866) and compared with the yield mass balance (YMB) method. Strong agreement between d13C and 14C AMS methods demonstrated the applicability of the ?13C method to quantify renewable carbon content in co-processing fuel products and guide the co-processing optimization

Li, Zhenghua↗
DOE OSTI2026

Cost and Carbon Intensity Implications of Coprocessing Sustainable Aviation Fuel at Petroleum Refineries

Sustainable aviation fuel (SAF) will play a critical role in decarbonizing the aviation industry. Among SAF production pathways, alcohol-to-jet (ATJ) stands out for its scalability, supported by abundant feedstock availability and a well-established bioethanol industry. However, significant reductions in SAF carbon intensity (CI) require the use of future feedstocks (e.g., cellulosic) whose adoption is hindered by high capital costs for feedstock processing and ethanol upgrading. Here, we evaluate the financial viability and environmental implications of integrating an ATJ SAF biorefinery within a petroleum refinery, utilizing miscanthus and switchgrass as example feedstocks. Three scenarios are evaluated: standalone (benchmark), colocated, and repurposing (coprocessing SAF within the petroleum refinery). Results show repurposing reduces baseline capital costs by 36% and SAF minimum selling price (MSP) by 12% to 8.14 USD·gal −1 ; the superior performance of repurposing is consistent across both feedstocks. Integration has a limited effect on SAF CI, which remains stable across scenarios, whereas using cellulosic feedstocks reduces CI by over 70% relative to corn, with baseline values of 17.01 g CO 2 e· MJ −1 for miscanthus and 12.23 g CO 2 e·MJ −1 for switchgrass. Global sensitivity analysis reveals MSP declines with greater coprocessing levels.

09 BIOMASS FUELS↗
DOE OSTI2021

Online Biogenic Carbon Analysis Enables Refineries to Reduce Carbon Footprint during Coprocessing Biomass- and Petroleum-Derived Liquids

To mitigate green-house gas (GHG) emissions, governments around the world are enacting legislation to reduce carbon intensity in transportation fuels. Coprocessing biomass and petroleum-derived liquids in existing refineries is a near-term, cost-effective approach for introducing renewable carbon in fuels and enabling refineries to meet regulatory mandates. However, coprocessing biomass-derived liquids in refineries results in variable degrees of biogenic carbon incorporation, necessitating accurate quantification to verify compliance with mandates. Existing refinery control and instrumentation systems lack the means to measure renewable carbon accurately, reliably, and quickly. Furthermore, accurate measurement of biogenic carbon is key to ensuring refineries meet regulatory mandates. In this Perspective, we present existing methods for measuring biogenic carbon, point out their challenges, and discuss the need for new online analytical capabilities to measure biogenic carbon in fuel intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Machine Learning Model for Predicting Composition of Catalytic Coprocessing Products from Molecular Beam Mass Spectra

Demand for the development of an automated and integrated refining process for biofuels has increased in recent years due to the lack of generalized process inspection tools. In bio-oil upgrading processes, all process variables are maintained based on the offline specification of intermediates and products. A lack of real-time product specifications in batch-wise monitoring can cause process failure and wasted resources. Therefore, there is a need for a fast and accurate intermediates/product specification tool that can be used for real-time specification to reduce waste and mitigate the risk of process failure. Here, to address this gap, we developed a machine learning (ML) model for predicting speciated bio-oil composition, including paraffin, iso-paraffins, olefins, naphthene, and aromatics. The model is trained using the mass spectra from upgraded products collected in the vapor phase before condensation and predicts the composition of the condensed product. Training ML models using raw mass spectra is challenging due to numerous overlapped peaks originating from different parent compounds. With this in mind, we propose a protocol that (i) transforms raw mass spectra to chemistry-inspired predefined features and (ii) trains decision tree-based models using these features. Our results show that the random forest model was robust against overfitting and had the highest accuracy compared to other models. Moreover, a stochastic ablation method determined the eight most significant features while maximizing the accuracy. Our protocol facilitates real-time compositional analysis of upgraded bio-oils and thus real-time process monitoring. Additionally, this protocol enables the rational design of efficient catalysts and the determination of optimal process conditions.

09 BIOMASS FUELS↗
DOE OSTI2022

Coprocessing Biomass Fast Pyrolysis and Catalytic Fast Pyrolysis Oils with Vacuum Gas Oil in Refinery Hydroprocessing

Fast pyrolysis and catalytic fast pyrolysis (CFP) have been considered to be promising approaches for converting lignocellulosic biomass into liquid bio-oils followed by upgrading to produce fuel-range hydrocarbon products. Co-processing fast pyrolysis and CFP bio-oils with petroleum feedstocks leverages the existing petroleum refining infrastructure, which reduces Capex for the overall conversion technologies for biomass to fuel and enables fast adoption of the technologies and biofuels. Here, we reported the co-processing of different woody fast pyrolysis and CFP bio-oils with petroleum vacuum gas oil (VGO) at 5-25% bio-oil blending levels over a NiMo sulfide catalyst for mild hydrocracking. The catalyst activities over ~300 hours time on stream, the product yield and properties, and the biogenic carbon content in products are provided. Co-processing of the raw fast pyrolysis bio-oil in our configuration was not successful because the instability of the bio-oil resulted in reactor plugging and bio-oil stabilization by hydrogenation enabled their stable co-processing with VGO, whereas the CFP bio-oil can be co-processed without pretreatment. Simultaneous hydrodesulfurization, hydrodeoxygenation, and hydrocracking reactions occurred during co-processing and no obvious decrease in hydrodesulfurization and hydrocracking conversion of VGO was observed, suggesting the minimal impact of co-processed bio-oils on the reaction of VGO and also the simultaneous conversion of bio-oil and VGO to produce fuel products with much-reduced S and O content. Biogenic carbon content in co-processed products calculated by yield mass balance, together with results from isotopic measurements, indicates high biogenic carbon incorporation into liquid hydrocarbon products. In conclusion, higher biogenic carbon incorporation into fuel products was observed when co-processing CFP bio-oils than the fast pyrolysis bio-oils and over 90% of carbon in CFP bio-oil was incorporated into liquid hydrocarbon products.

09 BIOMASS FUELS↗
DOE OSTI2023

Demonstration of a quantum-classical coprocessing protocol for simulating nuclear reactions

Quantum computers hold great promise for exact simulations of nuclear dynamical processes (e.g., scattering and reactions), which are paramount to the study of nuclear matter at the limit of stability and in the formation of chemical elements in stars. However, quantum simulations of the unitary (real) time dynamics of fermionic many-body systems require a currently prohibitive number of reliable and long-lived qubits. Here we propose a co-processing algorithm for the simulation of real-time dynamics in which the time evolution of the spatial coordinates is carried out on a classical processor, while the evolution of the spin degrees of freedom is carried out on quantum hardware. We demonstrate this hybrid scheme with the simulation of two neutrons scattering at the Lawrence Berkeley National Laboratory's Advanced Quantum Testbed. After implementing error mitigation strategies to improve the accuracy of the algorithm in addition to a combination of circuit compression techniques and tomography as methods to elucidate the onset of decoherence, our results validate the principle of the proposed co-processing scheme. A generalization of this present scheme will open the way for (real-time) path integral simulations of nuclear scattering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Data for Coprocessing Corn Germ Meal for Oil Recovery and Ethanol Production, a Process Model for Lipid-Producing Energy Crops

Efforts to engineer high-productivity crops to accumulate oils in their vegetative tissue present the possibility of expanding biodiesel production. However, processing the new crops for lipid recovery and ethanol production from cell wall saccharides is challenging and expensive. In a previous study using corn germ meal as a model substrate, we reported that liquid hot water (LHW) pretreatment enriched the lipid concentration by 2.2 to 4.2 fold. This study investigated combining oil recovery with ethanol production by extracting oil following LHW and simultaneous saccharification and co-fermentation (SSCF) of the biomass. Corn germ meal was again used to model the oil-bearing energy crops. Pretreated germ meal hydrolysate or solids (160 °C and 180 °C for 10 minutes) were fermented, and lipids were extracted from both the spent fermentation whole broth and fermentation solids, which were recovered by centrifugation and convective drying. Lipid contents in spent fermentation solids increased 3.7 to 5.7 fold compared to the beginning germ meal. The highest lipid yield achieved after fermentation was 36.0 mg lipid g−1 raw biomass; the maximum relative amount of triacylglycerol (TAG) was 50.9% of extracted oil. Although the fermentation step increased the lipid concentration of the recovered solids, it did not improve the lipid yields of pretreated biomass and detrimentally affected oil compositions by increasing the relative concentrations of free fatty acids.

Conversion↗
DOE OSTI2022

Coprocessing Corn Germ Meal for Oil Recovery and Ethanol Production: A Process Model for Lipid-Producing Energy Crops

Efforts to engineer high-productivity crops to accumulate oils in their vegetative tissue present the possibility of expanding biodiesel production. However, processing the new crops for lipid recovery and ethanol production from cell wall saccharides is challenging and expensive. In a previous study using corn germ meal as a model substrate, we reported that liquid hot water (LHW) pretreatment enriched the lipid concentration by 2.2 to 4.2 fold. This study investigated combining oil recovery with ethanol production by extracting oil following LHW and simultaneous saccharification and co-fermentation (SSCF) of the biomass. Corn germ meal was again used to model the oil-bearing energy crops. Pretreated germ meal hydrolysate or solids (160 and 180 °C for 10 min) were fermented, and lipids were extracted from both the spent fermentation whole broth and fermentation solids, which were recovered by centrifugation and convective drying. Lipid contents in spent fermentation solids increased 3.7 to 5.7 fold compared to the beginning germ meal. The highest lipid yield achieved after fermentation was 36.0 mg lipid g−1 raw biomass; the maximum relative amount of triacylglycerol (TAG) was 50.9% of extracted oil. Although the fermentation step increased the lipid concentration of the recovered solids, it did not improve the lipid yields of pretreated biomass and detrimentally affected oil compositions by increasing the relative concentrations of free fatty acids.

09 BIOMASS FUELS↗