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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Long-Term Corrosion Studies of Pine Derived Bio-Oil and Blends with Heavy Fuel Oil

Biomass derived liquid fuels offer a means to reduce greenhouse gas emissions compared to those produced by combustion of petroleum derived liquid fuels. However, the corrosivity of bio-oils toward the less expensive structural materials creates a material selection problem for designers of storage tanks and combustion systems. Samples of candidate structural materials are being exposed for thousands of hours in multiple fast pyrolysis bio-oils and conditions to evaluate the corrosion resistance of these materials. One method to mitigate the corrosivity of bio-oils and speed their adoption, while also decreasing the pollution issues associated with low quality petroleum derived fuels, is to utilize blends of bio-oil and heavy fuel oil in engines currently solely burning a petroleum-based fuel. In addition to the corrosion studies conducted in 100% bio-oil, studies were also conducted with blends of the fast pyrolysis bio-oil produced from pine tree components with a heavy fuel oil that is used in ocean-going ships. This bio-oil had a very high carboxylic acid content which made it very corrosive to carbon and 2¼ Cr-1 Mo steel and even 409 stainless steel. The heavy fuel oil was not corrosive to carbon steel, but its sulfur content makes it a significant pollution producer and particularly undesirable for use near coastlines. Corrosion tests were conducted with the individual components and with various blends of the two liquid fuels. Studies showed a significantly lower corrosivity of the blends than would be projected assuming linear mixing behavior. Adoption of such blends holds the potential to reduce production of sulfur-containing exhaust gases as well as carbon dioxide from non-renewable fuels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Engineering the cellulolytic extreme thermophile Caldicellulosiruptor bescii to reduce carboxylic acids to alcohols using plant biomass as the energy source

Abstract Caldicellulosiruptor bescii is the most thermophilic cellulolytic organism yet identified (Topt 78 °C). It grows on untreated plant biomass and has an established genetic system thereby making it a promising microbial platform for lignocellulose conversion to bio-products. Here, we investigated the ability of engineered C. bescii to generate alcohols from carboxylic acids. Expression of aldehyde ferredoxin oxidoreductase (aor from Pyrococcus furiosus) and alcohol dehydrogenase (adhA from Thermoanaerobacter sp. X514) enabled C. bescii to generate ethanol from crystalline cellulose and from biomass by reducing the acetate produced by fermentation. Deletion of lactate dehydrogenase in a strain expressing the AOR–Adh pathway increased ethanol production. Engineered strains also converted exogenously supplied organic acids (isobutyrate and n-caproate) to the corresponding alcohol (isobutanol and hexanol) using both crystalline cellulose and switchgrass as sources of reductant for alcohol production. This is the first instance of an acid to alcohol conversion pathway in a cellulolytic microbe.

Biotechnology & Applied Microbiology↗
DOE OSTI2019

Synthesis and analysis of separation processes for extracellular chemicals generated from microbial conversions

Recent advances in metabolic engineering have enabled the production of chemicals via bio-conversion using microbes. However, downstream separation accounts for 60–80% of the total production cost in many cases. Previous work on microbial production of extracellular chemicals has been mainly restricted to microbiology, biochemistry, metabolomics, or techno-economic analysis for specific product examples such as succinic acid, xanthan gum, lycopene, etc. In these studies, microbial production and separation technologies were selected apriori without considering any competing alternatives. However, technology selection in downstream separation and purification processes can have a major impact on the overall costs, product recovery, and purity. To this end, we apply a superstructure optimization based framework that enables the identification of critical technologies and their associated parameters in the synthesis and analysis of separation processes for extracellular chemicals generated from microbial conversions. We divide extracellular chemicals into three categories based on their physical properties, such as water solubility, physical state, relative density, volatility, etc. We analyze three major extracellular product categories (insoluble light, insoluble heavy and soluble) in detail and provide suggestions for additional product categories through extension of our analysis framework. The proposed analysis and results provide significant insights for technology selection and enable streamlined decision making when faced with any microbial product that is released extracellularly. The parameter variability analysis for the product as well as the associated technologies and comparison with novel alternatives is a key feature which forms the basis for designing better bioseparation strategies that have potential for commercial scalability and can compete with traditional chemical production methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Machine learning framework for assessment of microbial factory performance

Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other hand, machine learning, complementary to metabolic modeling necessitates large amounts of data. Building such a database for metabolic engineering designs requires significant manpower and is prone to human errors and bias. We propose an approach to integrate data-driven methods with genome scale metabolic model for assessment of microbial bio-production (yield, titer and rate). Using engineered E. coli as an example, we manually extracted and curated a data set comprising about 1200 experimentally realized cell factories from ~100 papers. We furthermore augmented the key design features (e.g., genetic modifications and bioprocess variables) extracted from literature with additional features derived from running the genome-scale metabolic model iML1515 simulations with constraints that match the experimental data. Then, data augmentation and ensemble learning (e.g., support vector machines, gradient boosted trees, and neural networks in a stacked regressor model) are employed to alleviate the challenges of sparse, non-standardized, and incomplete data sets, while multiple correspondence analysis/principal component analysis are used to rank influential factors on bio-production. The hybrid framework demonstrates a reasonably high cross-validation accuracy for prediction of E.coli factory performance metrics under presumed bioprocess and pathway conditions (Pearson correlation coefficients between 0.8 and 0.93 on new data not seen by the model).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A superstructure-based framework for bio-separation network synthesis

Modern biotechnologies enable the production of chemicals using engineered microorganisms. However, the cost of downstream recovery and purification steps is high, which means that the feasibility of bio-based chemicals production depends heavily on the synthesis of cost-effective separation networks. To this end, we develop a superstructure-based framework for bio-separation network synthesis. Based on general separation principles and insights obtained from industrial processes for specific products, we first identify four separation stages: cell treatment, product phase isolation, concentration and purification, and refinement. For each stage, we systematically implement a set of connectivity rules to develop stage-superstructures, all of which are then integrated to generate a general superstructure that accounts for all types of chemicals that can be produced using microorganisms. Here we further develop a superstructure reduction method to solve specific instances, based on product attributes, technology availability, case-specific considerations, and final product stream specifications. A general optimization model, including short-cut models for all technologies, is formulated. The proposed framework enables preliminary synthesis and analysis of bio-separation networks, and thus estimation of separation costs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Genome Stability in Engineered Strains of the Extremely Thermophilic Lignocellulose-Degrading Bacterium Caldicellulosiruptor bescii

Caldicellulosiruptor bescii is the most thermophilic cellulose degrader known and is of great interest because of its ability to degrade nonpretreated plant biomass. For biotechnological applications, an efficient genetic system is required to engineer it to convert plant biomass into desired products. To date, two different genetically tractable lineages of C. bescii strains have been generated. The first (JWCB005) is based on a random deletion within the pyrimidine biosynthesis genes pyrFA , and the second (MACB1018) is based on the targeted deletion of pyrE , making use of a kanamycin resistance marker. Importantly, an active insertion element, IS Cbe4 , was discovered in C. bescii when it disrupted the gene for lactate dehydrogenase ( ldh ) in strain JWCB018, constructed in the JWCB005 background. Additional instances of IS Cbe4 movement in other strains of this lineage are presented herein. These observations raise concerns about the genetic stability of such strains and their use as metabolic engineering platforms. In order to investigate genome stability in engineered strains of C. bescii from the two lineages, genome sequencing and Southern blot analyses were performed. The evidence presented shows a dramatic increase in the number of single nucleotide polymorphisms, insertions/deletions, and IS Cbe4 elements within the genome of JWCB005, leading to massive genome rearrangements in its daughter strain, JWCB018. Such dramatic effects were not evident in the newer MACB1018 lineage, indicating that JWCB005 and its daughter strains are not suitable for metabolic engineering purposes in C. bescii . Furthermore, a facile approach for assessing genomic stability in C. bescii has been established. Caldicellulosiruptor bescii is a cellulolytic extremely thermophilic bacterium of great interest for metabolic engineering efforts geared toward lignocellulosic biofuel and bio-based chemical production. Genetic technology in C. bescii has led to the development of two uracil auxotrophic genetic background strains for metabolic engineering. We show that strains derived from the genetic background containing a random deletion in uracil biosynthesis genes ( pyrFA ) have a dramatic increase in the number of single nucleotide polymorphisms, insertions/deletions, and IS Cbe4 insertion elements in their genomes compared to the wild type. At least one daughter strain of this lineage also contains large-scale genome rearrangements that are flanked by these IS Cbe4 elements. Finally, in contrast, strains developed from the second background strain developed using a targeted deletion strategy of the uracil biosynthetic gene pyrE have a stable genome structure, making them preferable for future metabolic engineering studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Techno-Economic Analysis and Life Cycle Assessment of Alternative Fuels for Locomotives in the U.S. Freight Rail Sector

Freight rail is more energy-efficient than truck transport over long-haul distances, offering a low-energy and emissions-intensive option for transporting freight. This study evaluates techno-economic analysis and life cycle assessment of seven alternative unblended fuels for freight locomotive engines─biodiesel, renewable diesel (RD), bio-oils, methanol, dimethyl ether (DME), ethanol, and ammonia─across 16 fuel pathways utilizing soybean, corn, woody biomass, renewable hydrogen, and waste sources, e.g., sludge, manure, and industrial CO 2 , and compares these to conventional diesel. The minimum fuel selling price (MFSP) ranged from $\$2.05$ to $\$8.27$ per diesel gallon equivalent (2020 US dollars), with biocrude and RDs produced from hydrothermal liquefaction (HTL) of sludge having the lowest MFSPs due to coproduct credits and avoided waste treatment cost. Life cycle GHG emissions ranged from −41 to 53 g of CO 2 e/MJ. RD from waste via HTL achieves negative emissions by diverting sludge/manure from GHG-intensive conventional management. Few pathways such as biocrude, methanol, and DME require additional control for SO X emissions in the refinery, while ethanol, FT-diesel, and bio-oil require additional control for particulate matter emissions. Bio-oil and RD from sludge have lower marginal abatement cost or MAC (–$\$38$/tonne CO 2 lowest) while methanol and ammonia with renewable hydrogen have higher MAC ($\$490$/tonne CO 2 maximum).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Topological Engineering of Interfacial Optical Tamm States for Highly Sensitive Near-Singular-Phase Optical Detection

Here, we developed planar multilayered photonic-plasmonic structures, which support topologically protected optical states on the interface between metal and dielectric materials, known as optical Tamm states. Coupling of incident light to the Tamm states can result in perfect absorption within one of several narrow frequency bands, which is accompanied by a singular behavior of the phase of electromagnetic field. In the case of near-perfect absorptance, very fast local variation of the phase can still be engineered. In this research, we theoretically and experimentally demonstrate how these drastic phase changes can improve sensitivity of optical sensors. A planar Tamm absorber was fabricated and used to demonstrate remote near-singular-phase temperature sensing with an over an order of magnitude improvement in sensor sensitivity and over two orders of magnitude improvement in the figure of merit over the standard approach of measuring shifts of resonant features in the reflectance spectra of the same absorber. Our experimentally demonstrated phase-to-amplitude detection sensitivity improvement nearly doubles that of state-of-the-art nano-patterned plasmonic singular-phase detectors, with further improvements possible via more precise fabrication. Tamm perfect absorbers form the basis for robust planar sensing platforms with tunable spectral characteristics, which do not rely on low-throughput nano-patterning techniques.

42 ENGINEERING↗
DOE OSTI2021

Maturation of Rhodobacter capsulatus Multicopper Oxidase CutO Depends on the CopA Copper Efflux Pathway and Requires the cutF Product (Final Report)

The goal is to achieve a comprehensive understanding of the nature, mechanism of function and biogenesis of c-type cytochromes and their oligomeric complexes. These cytochrome are ubiquitous heme proteins that are required for cellular bioenergetics, including photosynthesis (Ps) and respiration (Res), which are central to chemical energy (ATP) production by oxidative- and photophosphorylation. We contribute to the molecular characterization of individual and membrane-integral cytochromes as parts of Ps and Res electron transport (ET) pathways, using the facultative phototrophic bacteria of as excellent models for multidisciplinary investigations. Supported by this grant we discovered novel membrane-bound cytochromes and cyts c complexes that are important for Ps- and Res-ET. We worked out their biogenesis including maturation (covalent heme addition) and assembly of mature subunits into complexes. These involve fundamental process found virtually in all organisms and are fundamental processes with major significance to the “Photosynthetic Systems” program of DOE-BES, because the cytochromes are integral components of natural energy production systems. Elucidation of basic principles, and the knowledge gained by their study greatly impact on our ability to design, engineer, and create new natural, bio-hybrid, bio-inspired and artificial systems to better capture light, transduce and store its energy with improved efficacy and are of broad significance.

14 SOLAR ENERGY↗
DOE OSTI2016

Photosynthetic conversion of CO2 to farnesyl diphosphate-derived phytochemicals (amorpha-4,11-diene and squalene) by engineered cyanobacteria

Background: Metabolic engineering of cyanobacteria has enabled photosynthetic conversion of CO2 to value added chemicals as bio-solar cell factories. However, the production levels of isoprenoids in engineered cyanobacteria were quite low, compared to other microbial hosts. Therefore, modular optimization of multiple gene expressions for metabolic engineering of cyanobacteria is required for the production of farnesyl diphosphate-derived isoprenoids from CO2. Results: Here, we engineered Synechococcus elongatus PCC 7942 with modular metabolic pathways consisting of the methylerythritol phosphate pathway enzymes and the amorphadiene synthase for production of amorpha-4,11-diene, resulting in significantly increased levels (23-fold) of amorpha-4,11-diene (19.8 mg/L) in the best strain relative to a parental strain. Replacing amorphadiene synthase with squalene synthase led to the synthesis of a high amount of squalene (4.98 mg/L/OD730). Overexpression of farnesyl diphosphate synthase is the most critical factor for the significant production, whereas overexpression of 1-deoxy-d-xylulose 5-phosphate reductase is detrimental to the cell growth and the production. Additionally, the cyanobacterial growth inhibition was alleviated by expressing a terpene synthase in S. elongatus PCC 7942 strain with the optimized MEP pathway only (SeHL33). Conclusions: This is the first demonstration of photosynthetic production of amorpha-4,11-diene from CO2 in cyanobacteria and production of squalene in S. elongatus PCC 7942. Our optimized modular Over MEP strain (SeHL33) with either co-expression of ADS or SQS demonstrated the highest production levels of amorpha-4,11-diene and squalene, which could expand the list of farnesyl diphosphate-derived isoprenoids from CO2 as bio-solar cell factories.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Tailored Bioblendstocks With Low Environmental Impact To Optimize MCCI Engines

The prohect goal is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel.

09 BIOMASS FUELS↗
DOE OSTI2016

Enhancing digestibility and ethanol yield of Populus wood via expression of an engineered monolignol 4-O-methyltransferase

Producing cellulosic biofuels and bio-based chemicals from woody biomass is impeded by the presence of lignin polymer in the plant cell wall. Manipulating the monolignol biosynthetic pathway offers a promising approach to improved processability, but often impairs plant growth and development. Here, we show that expressing an engineered 4-O-methyltransferase that chemically modifies the phenolic moiety of lignin monomeric precursors, thus preventing their incorporation into the lignin polymer, substantially alters hybrid aspens’ lignin content and structure. Woody biomass derived from the transgenic aspens shows a 62% increase in the release of simple sugars and up to a 49% increase in the yield of ethanol when the woody biomass is subjected to enzymatic digestion and yeast-mediated fermentation. Furthermore, the cell wall structural changes do not affect growth and biomass production of the trees. Our study provides a useful strategy for tailoring woody biomass for bio-based applications.

09 BIOMASS FUELS↗
DOE OSTI2021

Investigation of grid-based vorticity-velocity large eddy simulation off-body solvers for application to overset CFD

Accurately predicting unsteady wakes and vortex-dominated flows is essential to a wide range of engineering applications, including aircraft, rotorcraft, shipboard operations, bio-inspired unsteady flight and propulsion, wind turbines, and urban flows. While current CFD software can model the complete flow field and wake system, the computational costs incurred in high Reynolds number unsteady turbulent flow simulations often remain prohibitive for routine engineering use, particularly for applications involving moving components. Prior work has demonstrated that by adopting a vorticity-velocity formulation in a grid-based off-body flow solver (VorTran-M and VorTran-M2) one can lower these costs by several orders of magnitude when compared to conventional approaches. This paper describes the extensions made to VorTran-M2 to support turbulent flows, and associated benchmarking activity to assess its performance for problems involving strong stretching and diffusion processes, whose competing contributions to the vorticity field are core drivers of turbulent flow evolution. Predictions are presented for: (i) the Kida-Pelz problem whose inviscid form is of mathematical interest due to its apparent formation of singular flow in finite time; and (ii) the Taylor Green vortex arrangement, which has been extensively studied as a fundamental simulation challenge in the turbulent modeling community. Here, the results are used to evaluate the overall predictive ability and performance of two sub-grid scale models incorporated into VorTran-M2. Results indicate that the computational cost savings seen previously for inviscid and convection dominated problems extend to turbulent flow simulations supporting the viability of VorTran-M2 as a low cost means for accurately modeling the far-field and background flow, particularly when long duration vorticity evolution is of interest.

42 ENGINEERING↗
DOE OSTI2025

Predicting Fuel Properties and Emissions for Advanced Biofuels for Diesel Engines (CRADA Final Report)

The project will investigate variations in biofuel composition and optimize performance in combustion for conventional and future compression ignition engines. It will evaluate a variety of bio-derived molecules in the diesel range that can be produced using technology in ExxonMobil’s portfolio as well as fuels that cover the range of potential molecular structures for robust model development. Changes in fuel/air premixing and stratification in advanced engines could alter the relationship between fuel properties and performance in comparison to current generation spray combustion approaches. NREL experience in fuel and combustion modeling will enable development of general rules for predicting performance of a wide range of biofuel options.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

The Promise of Emergent Nanobiotechnologies for In Vivo Applications and Implications for Safety and Security

Nanotechnology, the multi-disciplinary field based on the exploitation of the unique physicochemical properties of nanoparticles (NPs) and nanoscale materials, has opened a new realm of possibilities for biological research and biomedical applications. The development and deployment of mRNA-NP vaccines for COVID-19, for example, may revolutionize vaccines and therapeutics. However, regulatory and ethical frameworks that protect the health and safety of the global community and environment are lagging, particularly for nanotechnology geared towards biological applications (i.e., bio-nanotechnology). Considering this, the following review, while not comprehensive, attempts to illustrate the breadth and promise of bionanotechnology developments, and how they may present future safety and security challenges. Specifically, we address current advancements to streamline the development of engineered NPs for in vivo applications and provide discussion on nano-bio interactions, NP in vivo delivery, nano-enhancement of human performance, nanomedicine, and the impacts of NPs on human health and the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Enhancing control of cell-free metabolism through pH modulation

Engineering metabolism for the synthesis of bio-based products in non-model organisms can be challenging. One specific challenge is that biosynthetic pathways are often built from enzyme candidates sourced from diverse organisms, which can prove difficult to implement in recombinant hosts due to differences in their cellular environments (e.g. pH, cofactor balance). To address this problem, in this work we report a cell-free synthetic biology approach for understanding metabolism in a range of environmental conditions, specifically under varied pH. The key idea is to control the pH of Escherichia coli-based cell-free systems for assessing pathway performance using enzymes sourced from organisms other than E. coli. As a model, we apply this approach to study the impact of pH on the n-butanol biosynthesis pathway derived from clostridia in E. coli lysates. Specifically, we exploit the open, cell-free reaction environment to explore pH outside the habitable range of E. coli, revealing insights into how chemical context impacts the interaction between native metabolism and heterologous enzymes. We find that the pH optimum for butanol production from acetyl-CoA is substantially lower than the optimal pH of glycolysis in E. coli-based crude lysates. In addition, pH is an essential factor to consider when activating metabolic pathways in the cell-free environment due to its effect on reaction yield or enzyme activity, the latter of which is demonstrated in this work for alcohol dehydrogenases from a range of extremophiles. Ultimately, altering metabolism through pH control will allow cell-free systems to be used in studying the metabolic state of organisms and identify suitable enzymes for pathway engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

TAILORED BIOBLENDSTOCKS WITH LOW ENVIRONMENTAL IMPACT TO OPTIMIZE MCCI ENGINES

The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. Specific objectives include: (1) development of a new framework for both LCA and TEA that explicitly considers temporal variation in productivity and the frequency of crop loss; (2) determination of how fuel compounds that can be produced from the algal biomass can be ‘bio-tailored’ based on the species composition and biological production process, and subsequent processing via HTL to biocrude, and upgrading of the biocrude; (3) execution of a feedback loop (algae production  biocrude refining  combustion optimization  feedback to refining stage), for optimization of fuels for MCCI combustion; (4) optimization of MCCI combustion and emissions performance, accounting first for the biological processes that dictate the chemical composition of biocrude oil, and second for the subsequent chemical processes that comprise mixing controlled compression ignition combustion; (6) simulation of MCCI engine combustion processes to demonstrate the incorporation of relevant fuel chemistry that captures the specific impacts of optimized algal fuels.

09 BIOMASS FUELS↗