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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Predictive CRISPR-mediated gene downregulation for enhanced production of sustainable aviation fuel precursor in Pseudomonas putida

CRISPR interference (CRISPRi) has emerged as a valuable tool for redirecting metabolic flux to enhance bioproduction. However, its application is often constrained by two challenges: (i) rationally identifying effective gene targets for downregulation and (ii) efficiently constructing multiplexed CRISPRi systems. In this study, we address both challenges by integrating a computational prioritization tool with a versatile assembly method for building multiplexed CRISPRi systems. FluxRETAP (Flux-Reaction Target Prioritization) accurately identified gene targets whose knockdown led to substantial increase of isoprenol titers in Pseudomonas putida KT2440, outperforming a conventional non-computational, pathway-guided target selection. The highest isoprenol titer of nearly 1.5 g/L was achieved by knocking down PP_4118 (a gene encoding α-ketoglutarate dehydrogenase). The use of VAMMPIRE (Versatile Assembly Method for MultiPlexing CRISPRi-mediated downREgulation) enabled accurate assembly of CRISPRi constructs containing up to five sgRNA arrays, reducing context dependency and achieving uniform, position-independent gene downregulation. The integration of FluxRETAP and VAMMPIRE has the potential to advance metabolic engineering by rapidly identifying CRISPRi-mediated knockdowns and knockdown combinations that enhance bioproduction titers, with potential applicability to other microbial systems.

CRISPR interference↗
DOE OSTI2025

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↗
DOE OSTI2022

Conversion of syngas into light olefins in one step for process-intensified production of sustainable aviation fuels

Here, we report on a preliminary investigation for direct conversion of syngas into olefins. This technology combines alcohol(s) production and olefin(s) production into a single unit operation to improve process efficiencies due to the overcoming of equilibrium limitations and also to offer capital savings relative to current synthesis approaches including Fischer-Tropsch synthesis, methanol-to-olefins followed by olefins to gasoline/distillate process and alcohol-to-jet process.

10 SYNTHETIC FUELS↗
DOE OSTI2023

Mixed Oxygenate Conversion to Sustainable Aviation Fuel via Ketones Intermediate

This report describes our effort in developing Pd based bimetallic catalysts during Tandem ketone condensation-hydrogenation reaction. We have synthesized a series of bimetallic catalysts containing equimolar amount of Pd with various other 3d, 4d and 5d transition and coinage metals. The activity of theses bimetallic catalysts towards C=C and C=O hydrogenation was evaluated using mesityl oxide and 2-heptanone as model compounds. All these catalysts show much higher activity towards C=C hydrogenation compared to C=O hydrogenation at a given temperature and at different H2 pressure, indicated the higher intrinsic activity of Pd based bimetallic catalysts towards C=C hydrogenation. Alloy catalysts with Pd and other 4d and 5d metals such as PdRu, PdRh, PdPt and PdIr shows higher activity towards both C=C and C=O hydrogenation compared to baseline Pd catalyst as well as alloy catalysts containing Pd and 3d transition metals. Among the different Pd-3d metal alloy catalysts, the activity of the bimetallic catalysts depends on alloying transition metals. Although, PdRu, PdRh, PdPt and PdIr catalysts shows very high activity towards C=O hydrogenation of 2-heptanone, the same catalysts didn’t show any C=O hydrogenation when ?,?-unsaturated carbonyl compound such as mesityl oxide was used as the model substrate. Based on these results, it is evident that Pd based bimetallic catalysts are very selective to the C=C hydrogenation and their activity could be tuned by the judicious choice of the alloying elements. Although alloying with Ru, Rh and Pt shows significant rate enhancement in case of C=C hydrogenation reaction, higher cost of those metals prevents their usage in industry as it significantly increases the cost of the catalyst. Considering all the factors, we have identified PdZn as one of promising alternative of Pd catalyst as it shows comparable activity towards C=C hydrogenation and reduces the activity for C=O hydrogenation. Based on the electrochemical CO stripping, we unambiguously established the weaker bonding CO on the PdZn surface compared to pristine Pd and highlight the benefits of its usage due to higher CO tolerance.

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

Computationally evaluating high-yield metabolites for sustainable aviation fuel (SAF) using machine learning

The computational tool described in this report helps identify promising biological pathways that produce SAF platform molecules (either a drop-in SAF, or a precursor that can be easily converted to a drop-in SAF). The workflow the computational tool follows first identifies possible biological pathways from a user-defined metabolite. These pathways may, or may not lead to a SAF platform molecule, thus the second step involves insilico testing of the end product of each pathway to assess whether it is, or is not, a SAF platform molecule. The identification of biological pathways performed in the first step is facilitated by linking the metabolite to a biological reaction database. Pathways are found by identifying pathways in the reaction database that include the metabolite. The computational tool includes an alternative way to find pathways. The alternative way develops a Flux Balanced Analysis (FBA), and modifying the FBA to include reactions that transform the metabolite. These modifications serve as a basis for understanding, in a semi-quantitative way, if there is an increase in the flux to desirable products. The second step, in silico testing of the end-products, is accomplished by estimating key physical properties relevant to SAF. When good models are available, we have integrated those models into the computational tool. In a few instances, we have developed our own models. In all instances, we have validated the models against available measured data. Finally, we have evaluated the effectiveness of our computational tool by genetically engineering Rhodosporidium toruloides. Validation occurred without the use of a FBA, and further validation is required.

09 BIOMASS FUELS↗