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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Catalysis and biocatalysis program

The annual report presents the fiscal year (FY) 1990 research activities and accomplishments for the Catalysis and Biocatalysis Program of the Advanced Industrial Concepts Division (AICD), Office of Industrial Technologies of the Department of Energy (DOE). The mission of the AICD is to create a balanced program of high risk, long term, directed interdisciplinary research and development that will improve energy efficiency and enhance fuel flexibility in the industrial sector. The Catalysis and Biocatalysis Program's technical activities were organized into five work elements: the Molecular Modeling and Catalysis by Design element; the Applied Microbiology and Genetics element; the Bioprocess Engineering element; the Separations and Novel Chemical Processes element; and the Process Design and Analysis element.

Source record↗
NASA NTRS2012

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Zaychik, Kirill B.↗
DOE OSTI2020

NREL's Capabilities in Algae-Based Chemicals, Polymers, and Fuels

NREL is advancing research and development (R&D) to maximize photosynthetic carbon capture into biomass for conversion to a broad portfolio of valuable products. Areas of focus include: (1) Carbon capture improvement through photosynthesis engineering; (2) Biotechnology and genetic toolbox development for broad species portfolio; (3) Conversion and fractionation of algal biomass to create high-value products and fuels; (4) Biological seaweed conversion to volatile fatty acids as fuel and product feedstocks; (5) Novel polyurethane production synthesis from fully renewable algae-based feedstocks; (6) Advanced analytical characterization of biomass feedstocks; and (7) Process techno-economic and life cycle modeling.

algae↗
DOE OSTI2021

Overexpression of NblA decreases phycobilisome content and enhances photosynthetic growth of the cyanobacterium Synechococcus elongatus PCC 7942

Many research groups have considered whether decreasing photosynthetic antenna content in cyanobacteria can improve photosynthetic oxygen evolution and biomass accumulation. In this work, we describe a genetic strategy for truncating light harvesting antennae based on engineered alterations in the expression of NblA, a native protein naturally used by cyanobacteria to disassemble phycobilisomes antennae in response to environmental changes. We show that if enforced overexpression is fine-tuned, it is possible to realize gains in photosynthesis in a model cyanobacterium Synechococcus elongatus PCC 7942. We also show that antennae truncation helps protect cells from photodamage and that a strain overexpressing NblA can outcompete wild type in a mixed population. We propose approaches for future applications of these findings.

09 BIOMASS FUELS↗
DOE OSTI2020

Varroa destructor mites vector and transmit pathogenic honey bee viruses acquired from an artificial diet

The ectoparasitic mite Varroa destructor is one of the most destructive pests of the honey bee (Apis mellifera) and the primary biotic cause of colony collapse in many regions of the world. These mites inflict physical injury on their honey bee hosts from feeding on host hemolymph and fat body cells/cellular components, and serve as the vector for deadly honey bee viruses, including Deformed wing virus (DWV) and the related Varroa destructor virus-1 (VDV-1) (i.e., DWV-like viruses). Studies focused on elucidating the dynamics of Varroa-mediated vectoring and transmission of DWV-like viruses may be confounded by viruses present in ingested host tissues or the mites themselves. Here we describe a system that includes an artificial diet free of insect tissue-derived components for maintaining Varroa mites for in vitro experimentation. Using this system, together with the novel engineered cDNA clone-derived genetically tagged VDV-1 and wild-type DWV, we demonstrated for the first time that Varroa mites provided an artificial diet supplemented with engineered viruses for 36 hours could acquire and transmit sufficient numbers of virus particles to establish an infection in virus-naïve hosts. While the in vitro system described herein provides for only up to five days of mite survival, precluding study of the long-term impacts of viruses on mite health, the system allows for extensive insights into the dynamics of Varroa-mediated vectoring and transmission of honey bee viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Acetaminophen production in the edible, filamentous cyanobacterium Arthrospira platensis

Abstract Spirulina is the common name for the edible, nonheterocystous, filamentous cyanobacteriumArthrospira platensisthat is grown industrially as a food supplement, animal feedstock, and pigment source. Although there are many applications for engineering this organism, until recently no genetic tools or reproducible transformation methods have been published. While recent work showed the production of a diversity of proteins inA. platensis, including single‐domain antibodies for oral delivery, there remains a need for a modular, characterized genetic toolkit. Here, we independently establish a reproducible method for the transformation ofA. platensisand engineer this bacterium to produce acetaminophen as proof‐of‐concept for small molecule production in an edible host. This work opensA. platensisto the wider scientific community for future engineering as a functional food for nutritional enhancement, modification of organoleptic traits, and production of pharmaceuticals for oral delivery.

Biotechnology & Applied Microbiology↗
DOE OSTI2021

Progress Towards a New Model Chemolithoautotrophic Host (CRADA Final Report)

Some of the largest scale chemical processes for the production of important commodity chemicals and fuels involve an H 2 -containing gas mixture as an intermediate [e.g. ammonia, urea, methanol, Fischer-Tropsch (F-T) diesel, and hydrotreatment of crude petroleum to refined fuels]. The successful development of a model H 2 -oxidizing chemoautotrophic host could expand the range of fuels and chemicals produced from H 2 and CO 2 intermediates in the chemical, oil, and gas sectors in the near term, as well as from renewable and waste-derived sources of these gases that are expected to greatly expand in coming years. Among non-photosynthetic bacteria that can utilize H 2 and CO 2 , Cupriavidus necator (C. necator, formerly Ralstonia eutropha), is the best studied. C. necator is an excellent microbial host for the production of a variety of chemicals because it grows extremely quickly to very high cell densities autotrophically on H 2 and CO 2 , is genetically tractable, and has the ability to accumulate polymers, such as polyhydroxybutyrate, at industrial levels. Despite having great potential as a platform bioproduction host, genetic tools are limited, making metabolic engineering of this organism slow and laborious. In this CRADA project, we developed a number of genetic tools for C. necator: 1) Improvement of C. necator genetic transformation efficiency 2) Integration of heterologous genes into the C. necator chromosome and development of promoter library 3) Development of graded RBSs to control heterologous protein expression 4) Use of RBSs to demonstrate fatty alcohol production in C. necator 5) Demonstration of CRISPR-Cas9 gene editing in C. necator

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design optimization

In recent years, the use of machine learning-based surrogate models for computational fluid dynamics (CFD) simulations has emerged as a promising technique for reducing the computational cost associated with engine design optimization. However, such methods still suffer from drawbacks. One main disadvantage is that the default machine learning (ML) hyperparameters are often severely suboptimal for a given problem. This has often been addressed by manually trying out different hyperparameter settings, but this solution is ineffective in case of a high-dimensional hyperparameter space. Besides this problem, the amount of data needed for training is also not known a priori. In response to these issues that need to be addressed, the present work describes and validates an automated active learning approach, AutoML-GA, for surrogate-based optimization of internal combustion engines. In this approach, a Bayesian optimization technique is used to find the best machine learning hyperparameters based on an initial dataset obtained from a small number of CFD simulations. Subsequently, a genetic algorithm is employed to locate the design optimum on the ML surrogate surface. In the vicinity of the design optimum, the solution is refined by repeatedly running CFD simulations at the projected optima and adding the newly obtained data to the training dataset. It is demonstrated that AutoML-GA leads to a better optimum with a lower number of CFD simulations, compared to the use of default hyperparameters. The proposed framework offers the advantage of being a more hands-off approach that can be readily utilized by researchers and engineers in industry who do not have extensive machine learning expertise.

Owoyele, Opeoluwa↗
DOE OSTI2025

Xylanolytic metabolism is regulated by coordination of transcription factors XynR and XylR in extremely thermophilic Caldicellulosiruptorales

ABSTRACT Global transcription factors (TFs) control metabolic processes in bacteria to efficiently utilize available carbon. The orderCaldicellulosiruptoraleshas drawn interest due to the ability of its members to degrade components of lignocellulosic biomass. Regulatory reconstruction ofAnaerocellum (f. Caldicellulosiruptor) besciiidentified two major global transcription factors for xylan utilization, XynR and XylR, and the corresponding putative transcription factor binding sites. Recombinant versions of XynR (LacI family) and XylR (ROK family) were subjected to fluorescence polarization (FP) and biolayer interferometry (BLI) analysis to confirm the predicted binding sites. Four XynR sites and two XylR sites were validated, accounting for 20 of 26 genes regulated by XynR and six of seven genes regulated by XylR. Bioinformatic analysis of the individual genes controlled by the two regulators showed an inter-dependent scheme for xylan conversion; the transport of xylooligosaccharides (XOS) is dependent on XylR, while enzymes responsible for hydrolysis are controlled by both regulators. For xylose catabolism by the xylose isomerase-xylulose kinase pathway, regulation is also split, with XylR controlling xylose isomerase and XynR controlling xylokinase. The XynR/XylR regulator pair withinA. besciiis conserved in all sequenced species ofCaldicellulosiruptorales, suggesting similarities in regulating linear xylan conversion. In other xylanolytic thermophiles, XylR homologs control xylan degradation, compared to just 6 out of 26 genes forA. bescii. These results show that two separate regulatory schemes (dual repression) are coordinated byA. besciito effectively regulate the hemicellulose inventory and xylan catabolism. IMPORTANCE To take full advantage of extreme thermophiles as platform metabolic engineering microorganisms, the tools for genetic manipulation must be further developed, and strategies that exploit a better understanding of metabolic regulation need to be discerned.Anaerocellum bescii, the most studied of the extremely thermophilic fermentative anaerobic bacteria that can utilize microcrystalline cellulose, can degrade microcrystalline cellulose and hemicellulose and has been metabolically engineered to convert the resulting sugars to products such as ethanol and acetone. For xylan, in particular, two major global transcription factors (TFs), XynR and XylR, play a role in sugar metabolism, although their predicted regulatory interdependence from bioinformatics analysis has not been elucidated experimentally. Here, fluorescence polarization (FP) and biolayer interferometry (BLI) were used to explore this issue to support metabolic engineering efforts aimed at improving carbohydrate processing to industrial chemicals.

Biotechnology & Applied Microbiology↗
DOE OSTI2026

Data for Multisite Field Evaluation of Oil Accumulation and Agronomic Performance in Grain and Sweet Sorghums Engineered for Lipid Hyperaccumulation

Oil sorghum (OS) has been developed by engineering grain (TX430) and sweet (Ramada) genetic backgrounds to accumulate triacylglycerols (TAG) in vegetative tissues as an energy-dense feedstock for sustainable aviation fuel (SAF) and other biofuels. This study evaluated two TX430 OS lines (TxHO-2, TxHO-3) and two Ramada OS lines (RmHO-1, RmHO-2) alongside wild-type (WT) lines in NE and IL over 2 years (2023–2024) to quantify genotype × environment effects on agronomic performance and TAG accumulation. Across four environments, TX430 OS lines showed average TAG concentrations of 15.0 g kg−1 in leaves and 12.8 g kg−1 in stems, approximately 19-fold higher than WT. Ramada OS lines accumulated 26.1 g kg−1 in leaves and 12.3 g kg−1 in stems, approximately 25-fold and 13-fold increases over WT, respectively. OS lines in TX430 exhibited an 18% reduction in biomass (8.4 vs. 9.9 Mg ha−1 for WT), while Ramada OS lines had similar WT biomass (18.3 vs. 19.9 Mg ha−1 for WT). Among TX430 OS lines, TxHO-2 achieved the highest TAG yield (190 kg ha−1), while RmHO-1 led the Ramada lines (335 kg ha−1) due to higher biomass and similar TAG concentration. Enhanced TAG accumulation increased N, P, and K removal in TX430 lines but not in Ramada lines. Structural carbohydrate and ash concentration were unaffected. Overall, results confirm vegetative lipid accumulation as a viable strategy for high-biomass sorghum, supporting its potential as a dual-purpose feedstock for SAF. Future work should focus on minimizing biomass yield penalties and improving nutrient use efficiency in oil sorghum systems.

Agronomy↗
NASA NTRS1999

A Single-Lap Joint Adhesive Bonding Optimization Method Using Gradient and Genetic Algorithms

A natural process for any engineer, scientist, educator, etc. is to seek the most efficient method for accomplishing a given task. In the case of structural design, an area that has a significant impact on the structural efficiency is joint design. Unless the structure is machined from a solid block of material, the individual components which compose the overall structure must be joined together. The method for joining a structure varies depending on the applied loads, material, assembly and disassembly requirements, service life, environment, etc. Using both metallic and fiber reinforced plastic materials limits the user to two methods or a combination of these methods for joining the components into one structure. The first is mechanical fastening and the second is adhesive bonding. Mechanical fastening is by far the most popular joining technique; however, in terms of structural efficiency, adhesive bonding provides a superior joint since the load is distributed uniformly across the joint. The purpose of this paper is to develop a method for optimizing single-lap joint adhesive bonded structures using both gradient and genetic algorithms and comparing the solution process for each method. The goal of the single-lap joint optimization is to find the most efficient structure that meets the imposed requirements while still remaining as lightweight, economical, and reliable as possible. For the single-lap joint, an optimum joint is determined by minimizing the weight of the overall joint based on constraints from adhesive strengths as well as empirically derived rules. The analytical solution of the sin-le-lap joint is determined using the classical Goland-Reissner technique for case 2 type adhesive joints. Joint weight minimization is achieved using a commercially available routine, Design Optimization Tool (DOT), for the gradient solution while an author developed method is used for the genetic algorithm solution. Results illustrate the critical design variables as a function of adhesive properties and convergences of different joints based on the two optimization methods.

Smeltzer, Stanley S., III↗
DOE OSTI2022

Ancestral archaea expanded the genetic code with pyrrolysine

The pyrrolysyl-tRNA synthetase (PylRS) facilitates the cotranslational installation of the 22nd amino acid pyrrolysine. Owing to its tolerance for diverse amino acid substrates, and its orthogonality in multiple organisms, PylRS has emerged as a major route to install noncanonical amino acids into proteins in living cells. Recently, a novel class of PylRS enzymes was identified in a subset of methanogenic archaea. Enzymes within this class (ΔPylSn) lack the N-terminal tRNA-binding domain that is widely conserved amongst PylRS enzymes, yet remain active and orthogonal in bacteria and eukaryotes. In this study, we use biochemical and in vivo UAG-readthrough assays to characterize the aminoacylation efficiency and substrate spectrum of a ΔPylSn class PylRS from the archaeon Candidatus Methanomethylophilus alvus. We show that, compared with the full-length enzyme from Methanosarcina mazei, the Ca. M. alvus PylRS displays reduced aminoacylation efficiency but an expanded amino acid substrate spectrum. To gain insight into the evolution of ΔPylSn enzymes, we performed molecular phylogeny using 156 PylRS and 105 pyrrolysine tRNA (tRNA Pyl ) sequences from diverse archaea and bacteria. This analysis suggests that the PylRS•tRNA Pyl pair diverged before the evolution of the three domains of life, placing an early limit on the evolution of the Pyl-decoding trait. Furthermore, our results document the coevolutionary history of PylRS and tRNA Pyl and reveal the emergence of tRNA Pyl sequences with unique A73 and U73 discriminator bases. The orthogonality of these tRNA Pyl species with the more common G73-containing tRNA Pyl will enable future efforts to engineer PylRS systems for further genetic code expansion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A Catabolic Powerhouse for Biorefineries: Characterization and Engineering Erwinia spp. Strain LJJL01 to Produce Bioproducts

Nonmodel microbial hosts can efficiently biotransform unconventional organic feedstocks into advanced bioproducts, leveraging their superior metabolic capabilities and resilience to process-relevant physicochemical conditions. In this study, we domesticated Erwinia spp. strain. LJJL01 (Er LJJL01) as a potent microbial chassis to advance the emerging biorefinery strategy for the valorization of lignin-rich biomass and plastic, thereby enabling the circular economy. The strain exhibits remarkable chemical tolerance and can biofunnel various substrates, including sugars, acids, polyols, and aromatics, in minimal salt media to produce native fine chemicals such as acetoin, 2,3-butanediol, and lactic acid. As a proof of concept, engineering this strain with advanced genetic tools enables the production of tailored high-value chemicals, such as cis,cis-muconate from plastic-derived terephthalate and polyhydroxybutyrate from lignocellulosic hydrolysate. We established Er LJJL01 as a potent microbial chassis for the green synthesis of bioproducts from unconventional organic feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2020

Metabolic and evolutionary responses of Clostridium thermocellum to genetic interventions aimed at improving ethanol production

Engineering efforts targeted at increasing ethanol by modifying the central fermentative metabolism of Clostridium thermocellum have been variably successful. Here, we aim to understand this variation by a multifaceted approach including genomic and transcriptomic analysis combined with chemostat cultivation and high solids cellulose fermentation. Three strain lineages comprising 16 strains total were examined. Two strain lineages in which genes involved in pathways leading to organic acids and/or sporulation had been knocked out resulted in four end-strains after adaptive laboratory evolution (ALE). A third strain lineage recapitulated mutations involving adhE that occurred spontaneously in some of the engineered strains.

Biotechnology & Applied Microbiology↗
DOE OSTI2023

Systems Engineering of Rhodococcus opacus to Enable Production of Drop-in Fuels from Lignocellulose

Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.

09 BIOMASS FUELS↗
DOE OSTI2021

Biodiesel from oil produced in vegetative tissues of biomass – A review

Biodiesel is a green, renewable alternative to petroleum-derived diesel. However, using vegetable oil for bio- diesel production significantly challenges the food security. Progress in metabolic engineering, understanding of lipid biosynthesis and storage have enabled engineering of vegetative tissues of plants such as sugarcane, sor- ghum, and tobacco for lipid production. Such sources could be cultivated on land resources, which are currently not suitable for row crops. Besides achieving significant lipid accumulation, it is imperative to maintain the fatty acid and lipid profile ideal for biodiesel production and engine performance. In this study, genetic modifications used to induce lipid accumulation in transgenic crops and the proposed strategies for efficient recovery of oil from these crops have been presented. Here, this paper highlights that lipids sourced from vegetative biomass in their native form would pose significant challenges in biodiesel production. Therefore, different strategies have been presented for improving feedstock quality to achieve high-quality biodiesel production.

09 BIOMASS FUELS↗
DOE OSTI2020

Optogenetics and biosensors set the stage for metabolic cybergenetics

We report cybergenetic systems use computer interfaces to enable feed-back controls over biological processes in real time. The complex and dynamic nature of cellular metabolism makes cybergenetics attractive for controlling engineered metabolic pathways in microbial fermentations. Cybergenetics would not only create new avenues of research into cellular metabolism, it would also enable unprecedented strategies for pathway optimization and bioreactor operation and automation. Implementation of metabolic cybergenetics, however, will require new capabilities from actuators, biosensors, and control algorithms. The recent application of optogenetics in metabolic engineering, the expanding role of genetically encoded biosensors in strain development, and continued progress in control algorithms for biological processes suggest that this technology will become available in the not so distant future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Redefining fundamental concepts of transcription initiation in bacteria

Despite enormous progress in understanding the fundamentals of bacterial gene regulation, our knowledge remains limited when compared with the number of bacterial genomes and regulatory systems to be discovered. Derived from a small number of initial studies, classic definitions for concepts of gene regulation have evolved as the number of characterized promoters has increased. Together with discoveries made using new technologies, this knowledge has led to revised generalizations and principles. In this Expert Recommendation, we suggest precise, updated definitions that support a logical, consistent conceptual framework of bacterial gene regulation, focusing on transcription initiation. The resulting concepts can be formalized by ontologies for computational modelling, laying the foundation for improved bioinformatics tools, knowledge-based resources and scientific communication. Furthermore, this work will help researchers construct better predictive models, with different formalisms, that will be useful in engineering, synthetic biology, microbiology and genetics.

59 BASIC BIOLOGICAL SCIENCES↗