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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Mechanisms for high creep resistance in alumina forming austenitic (AFA) alloys

Castable alumina forming austenitic (AFA) alloys have demonstrated superior creep life and oxidation resistance at temperatures exceeding 800⁰C. Despite the success in the applicability of these alloys in extreme environments, there is a limited understanding of the deformation modes and the influence of each alloying element guiding the alloy design strategies that could further enhance the creep strength of these AFA alloys, particularly at temperatures at and above 900⁰C. In this study, we reveal the mechanism underpinning the superior creep performance of castable AFA alloys that involves suppressing primary carbide formation through minor compositional modification. This approach results in a three-fold increase in creep strength at 900⁰C and 50 MPa. Here, by employing integrated characterization techniques, we analyzed the microstructures of two AFA alloys, both before and after the creep process. We discovered that the suppression of primary carbides permits the in-situ clustering of now-available interstitial elements such as C, Si, and O during high-temperature creep. This improved solid solution strengthening and reduced stacking fault energy of the alloy. Moreover, it also enabled controlled secondary carbide formation during testing, further improving the creep resistance. These findings underline the important interplay between alloy composition, microstructure, and creep properties, and offer a promising design strategy for developing economical high-temperature Fe-based alloys suitable for advanced applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Physics-coupled data-driven design of high-temperature alloys

We present a materials design loop, which streamlines physics-coupled machine learning (ML) surrogate models to discover new alloy chemistries with improved properties. The efficacy is demonstrated by discovering a high-temperature alumina-forming austenitic (AFA) stainless steel with enhanced creep, followed by experimental validation. The ML models have been trained using a well-curated, highly consistent experimental dataset augmented with synthetic microstructural features from a computational thermodynamic approach. We have populated a large number of hypothetical AFA alloys to explore the high-dimensional composition space and have predicted their creep properties by providing the same synthetic input features obtained from the trained ML models. Uncertainties from the ML training were taken as thresholds for truncating predicted results to identify alloys with improved or deteriorated creep. Individual elemental compositions have been determined via probability density distribution analysis from the group of alloys at the top and bottom of the predicted creep values for further virtual and experimental validations. In conclusion, we anticipate that this workflow can be applied to screen desired conditions, such as chemistry and processing parameters, in high-dimensional space through physics-guided data analytics.

Alloy design↗
DOE OSTI2022

Small angle neutron scattering and lipidomic analysis of a native, trimeric PSI-SMALP from a thermophilic cyanobacteria

The use of styrene-maleic acid copolymers (SMAs) to produce membrane protein-containing nanodiscs without the initial detergent isolation has gained significant interest over the last decade. We have previously shown that a Photosystem I SMALP from the thermophilic cyanobacterium, Thermosynechococcus elongatus (PSI-SMALP), has much more rapid energy transfer and charge separation in vitro than detergent isolated PSI complexes. In this study, we have utilized small-angle neutron scattering (SANS) to better understand the geometry of these SMALPs. These techniques allow us to investigate the size and shape of these particles in their fully solvated state. Further, the particle's proteolipid core and detergent shell or copolymer belt can be interrogated separately using contrast variation, a capability unique to SANS. Here we report the dimensions of the Thermosynechococcus elongatus PSI-SMALP containing a PSI trimer. At ~1.5 MDa, PSI-SMALP is the largest SMALP to be isolated; our lipidomic analysis indicates it contains ~1300 lipids/per trimeric particle, >40-fold more than the PSI-DDM particle and > 100 fold more than identified in the 1JB0 crystal structure. Interestingly, the lipid composition to the PSI trimer in the PSI-SMALP differs significantly from bulk thylakoid composition, being enriched ~50 % in the anionic sulfolipid, SQDG. Finally, utilizing the contrast match point for the SMA 1440 copolymer, we also can observe the ~1 nm SMA copolymer belt surrounding this SMALP for the first time, consistent with most models of SMA organization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Co-processing catalytic fast pyrolysis oil in an FCC reactor

Here, studies of co-processing catalytic fast pyrolysis (CFP) oil with vacuum gas oil (VGO) are conducted in a Davison Circulating Riser (DCR). The CFP oil (CFPO) for this study was produced by upgrading fast-pyrolysis vapors from pine in an ex-situ fixed-bed reactor. CFPOs were co-processed at up to a volume fraction of 0.05 with VGO at 521 degrees C and 257 kPa. The yields of oil, aqueous phase, tail gas, and coke were measured. The amount of coke was determined from the carbon containing components in the regenerator flue gas. A compositional analysis was conducted with gas chromatography and elemental analyzers. The organic liquids were distilled into gasoline, jet-fuel, diesel, and resid fractions. A biocarbon analysis was conducted on the organic phase and its individual boiling-point fractions. The results show a small decrease in liquid yield and a generally increased gas yield when co-processing CFPO with VGO. The experiments showed that 75%-100% of biocarbon is incorporated into liquid fuels relative to fossil carbon, depending on catalyst and CFPO. The measurements indicate that cracked CFPO components are predominantly included in the jet-fuel and diesel fractions. A techno-economic analysis (TEA) estimated the minimum fuel selling price (MSFP) for fuel-range products derived from FCC co-processing of CFPO at 24 to 29 $\$$/GJ ($\$$2.90 to $\$$3.50 per gasoline-gallon equivalent; GGE) at a yield of 4.87-7.14 GJ/t(biomass) or 40-58 GGE/t.

09 BIOMASS FUELS↗
DOE OSTI2022

Feedstock and Catalyst Impact on Bio-Oil Production and FCC Co-Processing to Fuels

NREL's thermochemical biomass conversion research is focused on ex-situ upgrading of biomass fast-pyrolysis (FP) vapors as an efficient route to completely biogenic pyrolysis-based fuel precursors, fuels, and value-added chemicals depending on catalyst and process conditions. A near term pathway being developed uses these liquids for co-processing with petroleum feedstocks to assess biogenic carbon incorporation in hydrocarbon fuel feedstocks for potential refinery use. In this work, the impact of feedstock and catalyst on catalytic fast pyrolysis oil (CFPO) composition was determined with the oils then assessed for biogenic fuel production via FCC (fluidized catalytic cracking) co-processing. Biomass vapors were generated via fast pyrolysis with destabilizing vapor components (char, inorganics, tar aerosols) removed by hot gas filtration to produce clean vapors more responsive to catalytic upgrading. A Davison Circulating Riser (DCR), a petroleum industry standard for fluidized catalytic cracking (FCC) catalyst evaluation, was coupled to a custom pyrolyzer system designed to produce consistent-composition pyrolysis vapors as feed to the DCR. Pyrolysis vapors, derived from pure hardwood and softwood, were upgraded using commercially available modified zeolite-based catalysts to produce CFPOs. These upgraded oils were analyzed via 31P and 13C NMR spectroscopy, GCxGC-TOF/MS, carbonyl and ultimate analysis (CHNO), and simulated distillation (SIMDIS) to assess both oil chemistry and distillation behavior as they relate to catalyst and feedstock type for producing fungible hydrocarbon product liquids. These exploratory vapor-phase-upgrading results demonstrated the feasibility of producing refinery-compatible hydrocarbon fuel intermediates entirely from biomass-derived fast-pyrolysis vapors using an industry-accepted DCR system for catalytic upgrading. The FCC co-processing results demonstrated the feasibility of using CFPOs with VGO feeds in FCC refinery operations to produce biogenic carbon containing fuels.

biogenic carbon↗
DOE OSTI2020

An integrated methane dehydroaromatization and chemical looping process

Most of the natural gas co-produced in oil wells is flared due to the high transportation costs of bringing it to market. Onsite upgrading of natural gas to liquid products could address this issue but there are few processes for effective direct conversion of natural gas to liquid products. Methane dehydroaromatization (DHA) over Mo/HZSM- 5 offers a potential route to a value-added liquid product, however, DHA conversion is severely limited by thermodynamics at most industrially relevant temperatures. Here we propose an integrated process coupling methane DHA, chemical looping for selective hydrogen oxidation, and subsequent water removal to achieve higher yields of aromatic products limited by the thermodynamics in one-pass systems. Here, we validate this process via the construction and operation of a one-of-a-kind multibed recirculating reactor, and achieve a combined aromatics yield of 42%. Detailed technoeconomic analysis of the process for mobile applications show that such a process could be economically viable under certain circumstances.

03 NATURAL GAS↗
DOE OSTI2025

Sequential membrane- and protein-bound organelles compartmentalize genomes during phage infection

Many eukaryotic viruses require membrane-bound compartments for replication, but no such organelles are known to be formed by prokaryotic viruses. Bacteriophages of the Chimalliviridae family sequester their genomes within a phage-generated organelle, the phage nucleus, which is enclosed by a lattice of the viral protein ChmA. We show that inhibiting phage nucleus formation arrests infections at an early stage in which the injected phage genome is enclosed within a membrane-bound early phage infection (EPI) vesicle. Early phage genes are expressed from the EPI vesicle, demonstrating its functionality as a prokaryotic, transcriptionally active, membrane-bound organelle. We also show that the phage nucleus is essential, with genome replication beginning after the injected DNA is transferred from the EPI vesicle to the phage nucleus. Our results show that Chimalliviridae require two sophisticated subcellular compartments of distinct compositions and functions that facilitate successive stages of the viral life cycle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Review of low salinity waterflooding in carbonate rocks: mechanisms, investigation techniques, and future directions

This review analyses the fundamental thermodynamic theory of the crude oil-brine-rock (COBR) interface and the underlying rock-brine and oil-brine interactions. Next, the available data are reviewed to outline potential mechanisms responsible for increased oil recovery from low salinity waterflooding (LSWF). We propose an approach to studying LSWF and identify the key missing links that are needed to explain observations at multiple length scales. The synergistic effect of LSWFon other chemical enhanced oil recovery methods such as surfactant, alkaline, nanoparticle and polymer flooding are also outlined. We specifically highlight key uncertainties that must be overcome to fully implement the technique in the field.

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

Physics-informed latent neural operator for real-time predictions of time-dependent parametric PDEs

Deep operator network (DeepONet) has shown significant promise as surrogate models for systems governed by partial differential equations (PDEs), enabling accurate mappings between infinite-dimensional function spaces. However, when applied to systems with high-dimensional input-output mappings arising from large numbers of spatial and temporal collocation points, these models often require heavily overparameterized networks, leading to long training times. Latent DeepONet addresses some of these challenges by introducing a two-step approach: first learning a reduced latent space using a separate model, followed by operator learning within this latent space. While efficient, this method is inherently data-driven and lacks mechanisms for incorporating physical laws, limiting its robustness and generalizability in data-scarce settings. Here, in this work, we propose PI-Latent-NO, a physics-informed latent neural operator framework that integrates governing physics directly into the learning process. Our architecture features two coupled DeepONets trained end-to-end: a Latent-DeepONet that learns a low-dimensional representation of the solution, and a Reconstruction-DeepONet that maps this latent representation back to the physical space. By embedding PDE constraints into the training via automatic differentiation, our method eliminates the need for labeled training data and ensures physics-consistent predictions. The proposed framework is both memory and compute-efficient, exhibiting near-constant scaling with problem size and demonstrating significant speedups over traditional physics-informed operator models. We validate our approach on a range of parametric PDEs, showcasing its accuracy, scalability, and suitability for real-time prediction in complex physical systems.

Latent representations↗
DOE OSTI2024

Integrated multimodel analysis reveals achievable pathways toward reliable, 100% renewable electricity for Los Angeles

Climate change has prompted many communities to set targets for carbon-free power supplies, but they often lack data-driven strategies to achieve them. We present a comprehensive analysis of an entirely renewable electric power system that can maintain operating reliability and resource adequacy using detailed models of the city of Los Angeles power grid. In consultation with the operating utility, the Los Angeles Department of Water and Power (LADWP), and the local community, we develop four supply scenarios across three demand projections to analyze which types of infrastructure and operational changes would achieve reliable electricity at least cost. We find that a reliable, 100%-renewable power system yielding more than $1 billion annually in health and climate co-benefits is achievable. Solar can supply most future energy needs, while combustion turbines that use renewable, storable carbon-neutral fuels are key to maintaining reliability. This study provides a replicable methodology that other jurisdictions globally can follow.

14 SOLAR ENERGY↗
DOE OSTI2024

Integrating in situ environmental covariates in an American lobster catch model to improve impact assessment

The installation and operation of floating offshore wind power is an integral component of societal transition to renewable energy generation where fixed bottom offshore wind is not possible. However, it will cause unique ecosystem changes. To disentangle the effects of offshore wind installations from the concurrent effects of climate change and the fishing practices on commercially significant resources, we must develop detailed characterizations of the resources before development occurs. In the Gulf of Maine, American lobster is the most commercially and culturally important fishery. At the time of writing, this is the largest fishery by value in North America. Our understanding of baseline localized parameters (such as catch per trap at the spatial scale of individual turbines) should be informed by relationships to environmental, biological, and survey-specific functional drivers of catch. A more mechanistic understanding of catch will allow for strategic adjustments to Post- Deployment fishery responses and ultimately, the development of research- and commercial-scale floating offshore wind development. Here, we used survey data from the New England Aqua Ventus Pre-Construction Commercial Trapping Survey to develop Generalized Additive Models describing seasonal catch per trap for legal and sublegal lobsters. We found fall catch to be nearly twice that of spring. Bottom temperature dynamics could be used to predict catch, and the Fall survey was associated with a warmer temperature regime. By using analytical tools that incorporate environmental heterogeneity, we developed monitoring methods from preconstruction baseline data that will be applicable over the post-construction operating period of an offshore wind farm.

BACI↗