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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Thermal and orbital analysis of Earth monitoring Sun-synchronous space experiments

The fundamentals of an Earth monitoring Sun-synchronous orbit are presented. A Sun-synchronous Orbit Analysis Program (SOAP) was developed to calculate orbital parameters for an entire year. The output from this program provides the required input data for the TRASYS thermal radiation computer code, which in turn computes the infrared, solar and Earth albedo heat fluxes incident on a space experiment. Direct incident heat fluxes can be used as input to a generalized thermal analyzer program to size radiators and predict instrument operating temperatures. The SOAP computer code and its application to the thermal analysis methodology presented, should prove useful to the thermal engineer during the design phases of Earth monitoring Sun-synchronous space experiments.

Killough, Brian D.↗
NASA NTRS2000

Gravity Effects in Diffusive Coarsening of Bubble Lattices: von Neumann's Law

von Neumann modelled the evolution of two-dimensional soap froths as a purely diffusive phenomenon; the area growth of a given cell was found to depend only on the geometry of the bubble lattice. In the model, hexagons are stable, pentagons shrink and heptagons grow. The simplest equivalent to the area growth law is / approximately t(sub beta). The result depends on assuming (1) an incompressible gas; (2) bubble walls which meet at 120 deg and (3) constant wall thickness and curvature. Each assumption is borne out in experiments except the last one: bubble wall thickness between connecting cells varies in unit gravity because of gravity drainage. The bottom part of the soap membrane is thickened, the top part is thinned, such that gas diffusion across the membrane shows a complex dependence on gravity. As a result, experimental tests of von Neumann's law have been influenced by effects of gravity; fluid behavior along cell borders can give non-uniform wall thicknesses and thus alter the effective area and gas diffusion rates between adjacent bubbles. For area plotted as a function of time, Glazier (J.A. Glazier, S.P. Gross, and I. Stavans, Phys. Rev. A. 36, 306 (1987); J. Stavans, J.A, Glazier, Phys. Rev. Lett. 62, 1318 (1989).) suggest that in some cases their failure to observe von Neumann's predicted growth exponent ((sup beta)theor(sup =1; beta)exp(sup =0.70 + 0.10)) may have been the result of such "fluid drainage onto the lower glass plate". Additional experiments which varied plate spacing gave different beta exponents in a fashion consistent with this suggestion. During preliminary long duration experiments (approximately 100 h) aboard Spacelab-J, a low-gravity test of froth coarsening has examined (1) power law scaling of von Neumann's law (beta values) in the appropriate diffusive limits; (2) new bubble lattice dynamics such as greater fluid wetting behavior on froth membranes in low gravity; and (3) explicit relations for the gravity dependence of the second moment (or disorder parameter) governing the geometric spread in cell-sidedness around the mean of perfect hexagonal filling. By reducing the gravity-induced distortion in lattice wall thickness, the diffusion-limited regime of bubble coarsening becomes available for performing critical tests of network dynamics.

Noever, David A.↗
NASA NTRS2002

Tribological Performance of Some Pennzane(Registered Trademark) Based Greases for Vacuum Applications

Commercial greases for space applications usually fulfill the requirements imposed by the severe conditions of use. The main requirement is their ability to create an EHL film, boundary film, or both under speed, load and temperature conditions that the mechanisms will operate. Three greases, all based on a multiply alkylated cyclopentane (Pennzan(R)) base oil, were studied. The thickeners were an n-octadecylterephthalamate soap, a lithium soap, and a urea derivative. A Four-Ball Tribometer and a Spiral Orbit Tribometer were employed to evaluate the greases under ultrahigh vacuum. Results indicated that all three greases yielded very low wear rates and extended lifetimes. In addition, routine physical property data is reported for each grease.

Marchetti, Mario↗
NASA NTRS2008

NASA Tech Briefs, October 2008

Topics covered include: Control Architecture for Robotic Agent Command and Sensing; Algorithm for Wavefront Sensing Using an Extended Scene; CO2 Sensors Based on Nanocrystalline SnO2 Doped with CuO; Improved Airborne System for Sensing Wildfires; VHF Wide-Band, Dual-Polarization Microstrip-Patch Antenna; Onboard Data Processor for Change-Detection Radar Imaging; Using LDPC Code Constraints to Aid Recovery of Symbol Timing; System for Measuring Flexing of a Large Spaceborne Structure; Integrated Formation Optical Communication and Estimation System; Making Superconducting Welds between Superconducting Wires; Method for Thermal Spraying of Coatings Using Resonant-Pulsed Combustion; Coating Reduces Ice Adhesion; Hybrid Multifoil Aerogel Thermal Insulation; SHINE Virtual Machine Model for In-flight Updates of Critical Mission Software; Mars Image Collection Mosaic Builder; Providing Internet Access to High-Resolution Mars Images; Providing Internet Access to High-Resolution Lunar Images; Expressions Module for the Satellite Orbit Analysis Program Virtual Satellite; Small-Body Extensions for the Satellite Orbit Analysis Program (SOAP); Scripting Module for the Satellite Orbit Analysis Program (SOAP); XML-Based SHINE Knowledge Base Interchange Language; Core Technical Capability Laboratory Management System; MRO SOW Daily Script; Tool for Inspecting Alignment of Twinaxial Connectors; An ATP System for Deep-Space Optical Communication; Polar Traverse Rover Instrument; Expert System Control of Plant Growth in an Enclosed Space; Detecting Phycocyanin-Pigmented Microbes in Reflected Light; DMAC and NMP as Electrolyte Additives for Li-Ion Cells; Mass Spectrometer Containing Multiple Fixed Collectors; Waveguide Harmonic Generator for the SIM; Whispering Gallery Mode Resonator with Orthogonally Reconfigurable Filter Function; Stable Calibration of Raman Lidar Water-Vapor Measurements; Bimaterial Thermal Compensators for WGM Resonators; Root Source Analysis/ValuStream[Trade Mark] - A Methodology for Identifying and Managing Risks; Ensemble: an Architecture for Mission-Operations Software; Object Recognition Using Feature-and Color-Based Methods; On-Orbit Multi-Field Wavefront Control with a Kalman Filter; and The Interplanetary Overlay Networking Protocol Accelerator.

Source record↗
DOE OSTI2020

A mass spectrometry-based high-throughput screening method for engineering fatty acid synthases with improved production of medium-chain fatty acids

Microbial cell factories have been extensively engineered to produce free fatty acids (FFAs), key components of crucial nutrients, soaps, industrial chemicals, and fuels. Yet, our ability to control the specificity of microbially synthesized FFAs is still limited for medium-chain fatty acids (MCFAs), which is mainly due to lack of high-throughput approaches for FFA analysis. Here we report a mass spectrometry (MS)-based method for rapid profiling of MCFAs in Saccharomyces cerevisiae by using membrane lipids as a proxy. Specially, matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) MS was used to detect shorter acyl chain phosphatidylcholines from membrane lipids and the m/z peak ratio at 730 and 758 was used as an index for improved MCFA production. This yeast colony-based method can be performed at a rate of ~2 second per sample, which is much faster than the gold standard gas chromatography (GC)-MS (typically > 30 min per sample). To demonstrate the power of this method, we performed site-saturation mutagenesis of the yeast fatty acid synthase and identified 9 mutants that resulted in improved MCFA production relative to the wild-type strain. This colony-based MALDI-ToF MS screening method offers an alternative way for engineering microbial fatty acid compositions in a high-throughput manner.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Ice Phase Classification Made Easy with Score-Based Denoising

Accurate identification of ice phases is essential for understanding various physicochemical phenomena. However, such classification for structures simulated with molecular dynamics is complicated by the complex symmetries of ice polymorphs and thermal fluctuations. For this purpose, both traditional order parameters and data-driven machine learning approaches have been employed, but they often rely on expert intuition, specific geometric information, or large training data sets. In this work, we present an unsupervised phase classification framework that combines a score-based denoiser model with a subsequent model-free classification method to accurately identify ice phases. Further, the denoiser model is trained on perturbed synthetic data of ideal reference structures, eliminating the need for large data sets and labeling efforts. The classification step utilizes the smooth overlap of atomic position (SOAP) descriptors as the atomic fingerprint, ensuring Euclidean symmetries and transferability to various structural systems. Our approach achieves a remarkable 100% accuracy in distinguishing ice phases of test trajectories using only seven ideal reference structures of ice phases as model inputs. This demonstrates the generalizability of the score-based denoiser model in facilitating phase identification for complex molecular systems. The proposed classification strategy can be broadly applied to investigate structural evolution and phase identification for a wide range of materials, offering new insights into the fundamental understanding of water and other complex systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications

Molecular Dynamics (MD) simulations are used to understand the effects of corrosion on metallic materials in salt brine. Reactive force fields in classical MD enable accurate modeling of bond formation and breakage in the aqueous medium and at the metal-electrolyte interface, while also facilitating dynamic partial charge equilibration. However, MD simulations are computationally intensive and unsuitable for modeling the long time scales characteristic of corrosive phenomena. To address this, we develop reduced-order machine learning models that provide accurate and efficient predictions of charge density in corrosive environments. Specifically, we use Long Short-Term Memory (LSTM) networks to forecast charge density evolution based on atomic environments represented by Smooth Overlap of Atomic Positions (SOAP) descriptors. A physics-informed loss function enforces charge neutrality and electronegativity equivalence. The atomic charges predicted by the deep learning model trained on this work were obtained two orders of magnitude faster than those from molecular dynamics (MD) simulations, with an error of less than 3% compared to the MD-obtained charges, even in extrapolative scenarios, while adhering to physical constraints. This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.

Atomistic models↗
DOE OSTI2024

Unlocking saponin biosynthesis in soapwort

Abstract Soapwort ( Saponaria officinalis ) is a flowering plant from the Caryophyllaceae family with a long history of human use as a traditional source of soap. Its detergent properties are because of the production of polar compounds (saponins), of which the oleanane-based triterpenoid saponins, saponariosides A and B, are the major components. Soapwort saponins have anticancer properties and are also of interest as endosomal escape enhancers for targeted tumor therapies. Intriguingly, these saponins share common structural features with the vaccine adjuvant QS-21 and, thus, represent a potential alternative supply of saponin adjuvant precursors. Here, we sequence the S . officinalis genome and, through genome mining and combinatorial expression, identify 14 enzymes that complete the biosynthetic pathway to saponarioside B. These enzymes include a noncanonical cytosolic GH1 (glycoside hydrolase family 1) transglycosidase required for the addition of d- quinovose. Our results open avenues for accessing and engineering natural and new-to-nature pharmaceuticals, drug delivery agents and potential immunostimulants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Flexible polyurethanes, renewable fuels, and flavorings from a microalgae oil waste stream

Renewable polymers have become an important focus in next-generation materials, and algae biomass offers an environmentally low-impact feedstock that can serve multiple uses. This study aims to develop a scalable methodology for production of microalgae-based polyols for polyurethane synthesis from waste oils derived from algae biomass. Following separation of omega-3 fatty acids from algae oil, residual oils can offer valuable building blocks for petrochemical replacements. However, unlike vegetable oils, algae oils contain organic contaminants, including photosynthetic pigments and hydrophobic cofactors that can complicate preparative methodologies. Here we convert and purify waste streams from omega-3 depleted Nannochloropsis salina algae oil, with major components consisting of palmitic and palmitoleic acid, into azelaic acid (AA) as a building block for flexible polyurethanes, with a simultaneous production of heptanoic acid (HA) as a flavor and fragrance precursor. Conversion of free fatty acid mixtures into a soft soap allows extraction of organic contaminants, and urea complexation provides isolated palmitoleic acid, which is subsequently ozonolyzed to produce AA and HA. Bio-based polyester diols are prepared from AA via esterification to provide a polyol monomer for flexible polyurethane foam preparation. The HA co-product is modified to produce the flavoring agent methyl heptanoate and also decarboxylated to produce hexane as a renewable solvent. This scalable process can be performed on oils from multiple algal species, offering valuable monomers from a highly sustainable source.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Bonding similarities and differences between Y–Sb–Te and Sc–Sb–Te phase-change memory materials

The scandium (Sc) – alloyed Sb 2 Te 3 phase-change alloy has recently been found to enable ultrafast crystal nucleation due to the formation of Sc-stabilized octahedral motifs in the amorphous phase, rendering cache-type phase-change memory feasible. When yttrium (Y) is added, however, non-octahedral bonding patterns form in the amorphous Sb 2 Te 3 -based network even though Y has a valence electron configuration similar to that of Sc and also forms perfect octahedral bonding environments with tellurium in the YTe crystal. Here we elucidate the origin of this difference between Sc and Y, by carrying out thorough ab initio simulations and orbital-based bonding analyses on amorphous Y–Sb–Te and Sc–Sb–Te compounds. We also demonstrate how the smooth overlap of atomic positions (SOAP) similarity kernel can be used to quantify the structural similarity of local motifs in the amorphous phase with respect to various crystalline yttrium and scandium tellurides, both in the nearest-neighbor shell and beyond. We discover that the bonding contrast of Y- and Sc-centered structural motifs in amorphous Sb 2 Te 3 stems from their parent crystals at high Te concentrations. The larger atomic radius of Y and the weaker charge transfer when bonded with Te is found to allow more Te neighbors and cause a more open bonding environment, leading to higher coordination numbers and non-octahedral environments. We discuss the implications of the different local environments for practical applications in memory devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Excess Density as a Descriptor for Electrolyte Solvent Design

Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes to achieve desired properties, such as viscosity, dielectric constant, boiling point, and melting point. Conventionally, multi-component electrolyte properties are approximated with linear mixing, but in practice, significant deviations are observed. Excess quantities can provide insights into the molecular behavior of the mixture and could form the basis for designing high-performance electrolytes. Here we investigate the excess density of commonly used Li-ion battery solvents such as cyclic carbonates, linear carbonates, ethers, and nitriles with molecular dynamics simulations. We additionally investigate electrolytes consisting of these solvents and a salt. The results smoothly vary with mole percent and are fit to permutation-invariant Redlich-Kister polynomials. Mixtures of similar solvents, such as cyclic-cyclic carbonate mixtures, tend to have excess properties that are lower in magnitude compared to mixtures of dissimilar substances, such as carbonate-nitrile mixtures. We perform experimental testing using our automated test stand, Clio, to provide validation to the observed simulation trends. We quantify the structure similarity using SOAP fingerprints to create a descriptor for excess density, enabling the design of electrolyte properties. To a first approximation, this will allow us to estimate the deviation of a mixture from ideal behavior based solely upon the structural dissimilarity of the components.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

COVID-19 global pandemic planning: Performance and electret charge of N95 respirators after recommended decontamination methods

Shortages of N95 respirators for use by medical personnel have driven consideration of novel conservation strategies, including decontamination for reuse and extended use. Decontamination methods listed as promising by the Centers for Disease Control and Prevention (CDC) (vaporous hydrogen peroxide (VHP), wet heat, ultraviolet irradiation (UVI)) and several methods considered for low resource environments (bleach, isopropyl alcohol and detergent/soap) were studied for two commonly used surgical N95 respirators (3M™ 1860 and 1870+ Aura™). Although N95 filtration performance depends on the electrostatically charged electret filtration layer, the impact of decontamination on this layer is largely unexplored. As such, respirator performance following decontamination was assessed based on the fit, filtration efficiency, and pressure drop, along with the relationship between (1) surface charge of the electret layer, and (2) elastic properties of the straps. Decontamination with VHP, wet heat, UVI, and bleach did not degrade fit and filtration performance or electret charge. Isopropyl alcohol and soap significantly degraded fit, filtration performance, and electret charge. Pressure drop across the respirators was unchanged. Modest degradation of N95 strap elasticity was observed in mechanical fatigue testing, a model for repeated donnings and doffings. CDC recommended decontamination methods including VHP, wet heat, and UV light did not degrade N95 respirator fit or filtration performance in these tests. Extended use of N95 respirators may degrade strap elasticity, but a loss of face seal integrity should be apparent during user seal checks. NIOSH recommends performing user seal checks after every donning to detect loss of appropriate fit. Decontamination methods which degrade electret charge such as alcohols or detergents should not be used on N95 respirators. The loss of N95 performance due to electret degradation would not be apparent to a respirator user or evident during a negative pressure user seal check.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Data from A Mass Spectrometry-Based High-Throughput Screening Method for Engineering Fatty Acid Synthases with Improved Production of Medium Chain Fatty Acids

Microbial cell factories have been extensively engineered to produce free fatty acids (FFAs) as key components of crucial nutrients, soaps, industrial chemicals, and fuels. However, our ability to control the composition of microbially synthesized FFAs is still limited, particularly, for producing medium‐chain fatty acids (MCFAs). This is mainly due to the lack of high‐throughput approaches for FFA analysis to engineer enzymes with desirable product specificity. Here we report a mass spectrometry (MS)‐based method for rapid profiling of MCFAs in Saccharomyces cerevisiae by using membrane lipids as a proxy. In particular, matrix‐assisted laser desorption/ionization time‐of‐flight (MALDI‐ToF) MS was used to detect shorter acyl chain phosphatidylcholines from membrane lipids and a higher m/z peak ratio at 730 and 758 was used as an indication for improved MCFA production. This colony‐based method can be performed at a rate of ~2 s per sample, representing a substantial improvement over gas chromatography‐MS (typically >30 min per sample) as the gold standard method for FFA detection. To demonstrate the power of this method, we performed site‐saturation mutagenesis of the yeast fatty acid synthase and identified nine missense mutations that resulted in improved MCFA production relative to the wild‐type strain. Colony‐based MALDI‐ToF MS screening provides an effective approach for engineering microbial fatty acid compositions in a high‐throughput manner.

Conversion↗
DOE OSTI2023

Machine Learning for Prediction of Thermodynamic Descriptors

Our objective is to apply machine learning (ML) algorithms for the prediction of molecular catalysis descriptors from geometric properties derived from experimental crystallographic databases. Catalysis is often considered a “low-data” discipline that is poorly suited for ML methods. An exception is the extensive structural information that is available for molecular catalysts through the Cambridge Structural Database (CSD), which contains atomically precise molecular structures from X-ray diffraction analysis for >600K metal complexes. As a proof-of-principle, we targeted the prediction of hydricity, a thermodynamic property that provides understanding and control of catalytic hydride transfer. We built a training set composed of ~100 molecular complexes with a known hydricity and structural information from the CSD. This data set was converted into a machine-readable format using the smooth overlap of atomic positions (SOAP) representation and further labeled with simple electronic descriptors for the metal centers. Multiple different neural networks were trained on this data set, and the accuracy of the hydricity predictions ranged from < 2 kcal/mol to 20 kcal/mol. The accuracy of each model was highly sensitive to which compounds were in the train versus test set, underscoring the challenges associated with small and chemically diverse data sets. Finally, to further augment the data set, we attempted to experimentally measure several new hydricity values, however these experiments were unsuccessful due to undesired chemical reactivity of the selected complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Characterization of Oil and Gas Drill Cuttings for Critical Mineral Recovery and Reuse Potential as Soil Supplements

Expansion of unconventional oil and natural gas production over the last decade in the United States has resulted in record production of natural gas and oil in 2024. Millions of tons of drill cuttings generated from shale gas development are currently disposed of in landfills. Converting these cuttings into value product(s) such as critical minerals (CMs) and soil supplements, has the potential of reducing environmental impact of fossil fuel exploration. In this study we characterize the CM distribution and extractability from collected drill cuttings and core samples from major U.S. shale formations. A four-step sequential extraction, consisting of a sonicated soap step, sonicated EDTA step , mildly reducing agent, and a oxidizing agent, was developed to simultaneously extract CMs and convert the drill cuttings into soil supplements. Viability of converted drill cuttings as soil supplement was determined with a seedling growth experiment. Results show high concentrations of vanadium (V) (up to 1575 ppm, barite (up to 5 wt. %), and rare earth elements (REE) concentrations (up to 253 ppm). High extractability of selected critical minerals such as REE (19-50%) and Ba (10-58%) show promising results. Preliminary results show seedling growth in a mixture of converted drill cuttings with soil. These results show the potential for recovery of CMs from drill cuttings as an alternative domestic and the reduction of the environmental impact of fossil fuel production.

Barczok, Maximilian↗
DOE OSTI2024

Field Validation of a Pilot-scale Black Liquor Membrane for Water Removal at Ahlstrom-Munksjö Paper Mill in Mosinee, WI

Project Background: The Industrial Technology Validation (ITV) program aims to identify and demonstrate the performance of new, emerging, and underutilized technologies in the industrial sector to help inform decisions towards accelerating commercialization and deployment. Pulp and paper is considered one of the most energy-intensive industries in the manufacturing sector. There are several methodologies for converting wood into pulp in the paper-making industry. The kraft process is a chemical method for producing wood pulp. The kraft process generates black liquor as a byproduct of pulp production. Traditionally, water is evaporated from the liquor by a set of multi-effect evaporators (MEEs), which concentrate weak black liquor (WBL) into strong black liquor (SBL) to support efficient combustion in a recovery boiler. Concentrating black liquor is an energy-intensive step in recovering pulping chemicals and generating high-pressure steam from dissolved wood solids. About 7% of pulp and paper energy usage, or nearly 164 trillion Btu, is used to remove water from black liquor in U.S. kraft pulp mills per year. The U.S. DOE’s IEDO is interested in the black liquor membrane technology evaluated in this report because it offers the potential for a more energy-efficient and less carbon-intensive kraft pulping process across 99 kraft pulp mills in 24 states (Agenda 2020 Technology Alliance 2016). This ITV project validates an innovative black liquor membrane technology for kraft pulp mills to understand its impact and benefits. Via Separations is a technology vendor that developed a graphene oxide membrane system to remove water from WBL before entering the evaporator set. High-pressure positive displacement (HPR) pumps move the black liquor through membranes that separate water and create a more concentrated black liquor. The vendor claims their pre-commercial technology reduces evaporator steam consumption by dewatering WBL before entering the evaporators. They also claim their technology has non-energy benefits such as enhanced soap collection and improved pulp throughput. This evaluation focuses on validating the energy and carbon dioxide (CO 2 e) emissions benefits associated with the membrane system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

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↗