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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Water treatment based on atomically engineered materials: Atomic layer deposition and beyond

Global water stress and challenges for producing sufficient supplies of fit-for-purpose water are amplifying. Atomically engineered interfaces are emerging as a powerful tool in the fabrication of advanced water treatment materials. Atomic layer deposition (ALD) and recently developed related methods, such as sequential infiltration synthesis (SIS), offer a tremendously diverse library of chemistries for interface functionalization. Thickness, stoichiometry, and physicochemical properties can be manipulated with precision. We review their fundamental physical chemistry and processing factors. ALD/SIS engineering strategies, including direct deposition, growth with intermediate layers, and secondary treatment are presented with realization of efficient water treatment. We lay out a pathway to establishing an ALD/SIS-based universal functionalization platform for water treatment, including sensitization strategies, in situ regulation, secondary reactions, and simulation/machine learning. Furthermore, we also provide a perspective on ALD/SIS-based interface engineering via synergy with other widely used interface engineering techniques to develop facile, versatile, and energy-efficient strategies for tackling increasingly complex water challenges.

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

Investigation of post-injection strategies for diesel engine Catalyst Heating Operation using a vapor-liquid-equilibrium-based spray model

Most multidimensional engine simulations spend much time solving for non-equilibrium spray dynamics (atomization, collision, vaporization). However, their accuracy is limited by significant grid dependency, and the need for extensive calibration. This is critical for modeling cold-start diesel fuel post injections, which occur at low temperatures and pressures, far from typical model validation ranges. At the same time, resolving micron-scale spray phenomena would render full Eulerian multiphase calculations prohibitive. In this study, an improved phase equilibrium based approach was implemented and assessed for simulating diesel catalyst heating operation strategies. A phase equilibrium solver based on the model by Yue and Reitz [1] was implemented: a fully multiphase CFD solver is employed with an engineering-size engine grid, and fuel injection is modeled using the standard Lagrangian parcels approach. Mass and energy from the liquid parcels are released to the Eulerian multiphase mixture according to an equilibrium-based liquid jet model. An improved phase equilibrium solver was developed to handle large real-gas mixtures such as those from accurate chemical kinetics mechanisms. The liquid-jet model was improved such that momentum transfer to the Eulerian solver better reproduces the physical spray jet structure. Validation of liquid/vapor penetration predictions showed that the model yields accurate results with very limited tuning and low sensitivity to the few calibration constants. In-cylinder simulations of diesel catalyst heating operation strategies showed that capturing spray structure is paramount when short, transient injection pulses and low temperatures are present. Furthermore, the EP model provides improved predictions of post-injection spray structure and ignitability, while conventional spray modeling does not capture the increase of liquid penetration during the expansion stroke. Finally, the only important EP model calibration constant, Cliq, does not affect momentum transfer, but it changes the local charge cooling distribution through the local energy transfer, which makes it candidate to additional research. The results confirm that non-equilibrium spray processes do not need to be resolved in engineering simulations of high-pressure diesel sprays.

42 ENGINEERING↗
DOE OSTI2024

Verazine biosynthesis from simple sugars in engineered Saccharomyces cerevisiae

Steroidal alkaloids are FDA-approved drugs (e.g., Zytiga) and promising drug candidates/leads (e.g., cyclopamine); yet many of the ≥697 known steroidal alkaloid natural products remain underutilized as drugs because it can be challenging to scale their biosynthesis in their producing organisms. Cyclopamine is a steroidal alkaloid produced by corn lily (Veratrum spp.) plants, and it is an inhibitor of the Hedgehog (Hh) signaling pathway. Therefore, cyclopamine is an important drug candidate/lead to treat human diseases that are associated with dysregulated Hh signaling, such as basal cell carcinoma and acute myeloid leukemia. Cyclopamine and its semi-synthetic derivatives have been studied in (pre)clinical trials as Hh inhibitor-based drugs. However, challenges in scaling the production of cyclopamine have slowed efforts to improve its efficacy and safety profile through (bio)synthetic derivatization, often limiting drug development to synthetic analogs of cyclopamine such as the FDA-approved drugs Odomzo, Daurismo, and Erivedge. If a platform for the scalable and sustainable production of cyclopamine were established, then its (bio)synthetic derivatization, clinical development, and, ultimately, widespread distribution could be accelerated. Ongoing efforts to achieve this goal include the biosynthesis of cyclopamine in Veratrum plant cell culture and the semi-/total chemical synthesis of cyclopamine. Herein, this work advances efforts towards a promising future approach: the biosynthesis of cyclopamine in engineered microorganisms. We completed the heterologous microbial production of verazine (biosynthetic precursor to cyclopamine) from simple sugars (i.e., glucose and galactose) in engineered Saccharomyces cerevisiae (S. cerevisiae) through the inducible upregulation of the native yeast mevalonate and lanosterol biosynthetic pathways, diversion of biosynthetic flux from ergosterol (i.e., native sterol in S. cerevisiae) to cholesterol (i.e., biosynthetic precursor to verazine), and expression of a refactored five-step verazine biosynthetic pathway. The engineered S. cerevisiae strain that produced verazine contains eight heterologous enzymes sourced from seven different species. Importantly, S. cerevisiae-produced verazine was indistinguishable via liquid chromatography-mass spectrometry from both a commercial standard (Veratrum spp. plant-produced) and Nicotiana benthamiana-produced verazine. To the best of our knowledge, this is the first report describing the heterologous production of a steroidal alkaloid in an engineered yeast. Verazine production was ultimately increased through design-build-test-learn cycles to a final titer of 83 ± 3 μg/L (4.1 ± 0.1 μg/g DCW). Finally, this research lays the groundwork for future microbial biosynthesis of cyclopamine, (bio)synthetic derivatives of cyclopamine, and other steroidal alkaloid natural products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Engineering an Extremely Hybrid PKS for Adipic Acid Production

Polyketide synthases (PKSs) are modular enzymes with exceptional potential as biocatalysts for producing non-native compounds. Here, we report the first PKS-based pathway for adipic acid (AA), an industrial monomer for nylon production, by engineering one of the most extensively hybridized PKS systems to date. Using a retrobiosynthetic approach, we identified EtnB, a succinyl-CoA-loading module that uniquely retains the terminal carboxyl group, enabling access to dicarboxylic polyketide products, rarely produced by canonical PKSs. EtnB was coupled to a fully reducing extension module through an engineered communication linker, which improved ACP–KS interactions, enhanced titers, and demonstrated selective succinyl-CoA loading in vivo . This construct integrates genes from five organisms─with domains from seven PKS modules joined across six non-natural junctions─and functions in both Escherichia coli and Pseudomonas putida . Additional engineering that included AT domain exchanges, optimization of extender unit supply, and host strain metabolic rewiring further increased AA production. Together, this work demonstrates that highly chimeric PKSs can be rendered functional through rational design, expands the PKS toolkit with a carboxyl-retaining loading module, and establishes a versatile platform for engineering diacids and other noncanonical products through PKS pathways.

biomanufacturing↗
DOE OSTI2020

Chemoinformatic-Guided Engineering of Polyketide Synthases

Polyketide synthase (PKS) engineering is an attractive method to generate new molecules such as commodity, fine and specialty chemicals. A significant challenge is re-engineering a partially reductive PKS module to produce a saturated β-carbon through a reductive loop (RL) exchange. In this work, we sought to establish that chemoinformatics, a field traditionally used in drug discovery, offers a viable strategy for RL exchanges. We first introduced a set of donor RLs of diverse genetic origin and chemical substrates into the first extension module of the lipomycin PKS (LipPKS1). Product titers of these engineered unimodular PKSs correlated with chemical structure similarity between the substrate of the donor RLs and recipient LipPKS1, reaching a titer of 165 mg/L of short-chain fatty acids produced by the host Streptomyces albus J1074. Finally, expanding this method to larger intermediates that require bimodular communication, we introduced RLs of divergent chemosimilarity into LipPKS2 and determined triketide lactone production. Collectively, we observed a statistically significant correlation between atom pair chemosimilarity and production, establishing a new chemoinformatic method that may aid in the engineering of PKSs to produce desired, unnatural products.

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

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

Abstract Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be combined to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets, efficient library construction of metabolic pathway designs, and high-throughput biosensor-enabled screening for training diverse machine learning algorithms. From a single data-generation cycle, this enables successful forward engineering of complex aromatic amino acid metabolism in yeast, with the best machine learning-guided design recommendations improving tryptophan titer and productivity by up to 74 and 43%, respectively, compared to the best designs used for algorithm training. Thus, this study highlights the power of combining mechanistic and machine learning models to effectively direct metabolic engineering efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Operando measurement of lattice strain in internal combustion engine components by neutron diffraction

Significance Internal combustion engine components experience extreme thermomechanical cycling during operation, and the continuing need to improve engine efficiency while maintaining or improving reliability drives the development of lightweight materials with improved thermal and mechanical integrity. Understanding the behavior of new materials in dynamic operation requires operando characterization tools, but conventional in situ measurements of material behavior during real engine operation are very limited, and no practical means exist to replicate such extreme dynamics for ex situ study. In this work, we demonstrate that the penetrating power of neutrons can provide noninvasive measurement of lattice strains inside components of a firing engine, enabling the operando study of complex load states and thermal gradients throughout the solid materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Engineered mRNA–ribosome fusions for facile biosynthesis of selenoproteins

Ribosomes are often used in synthetic biology as a tool to produce desired proteins with enhanced properties or entirely new functions. However, repurposing ribosomes for producing designer proteins is challenging due to the limited number of engineering solutions available to alter the natural activity of these enzymes. In this study, we advance ribosome engineering by describing a novel strategy based on functional fusions of ribosomal RNA (rRNA) with messenger RNA (mRNA). Specifically, we create an mRNA–ribosome fusion called RiboU, where the 16S rRNA is covalently attached to selenocysteine insertion sequence (SECIS), a regulatory RNA element found in mRNAs encoding selenoproteins. When SECIS sequences are present in natural mRNAs, they instruct ribosomes to decode UGA codons as selenocysteine (Sec, U) codons instead of interpreting them as stop codons. This enables ribosomes to insert Sec into the growing polypeptide chain at the appropriate site. Our work demonstrates that the SECIS sequence maintains its functionality even when inserted into the ribosome structure. As a result, the engineered ribosomes RiboU interpret UAG codons as Sec codons, allowing easy and site-specific insertion of Sec in a protein of interest with no further modification to the natural machinery of protein synthesis. To validate this approach, we use RiboU ribosomes to produce three functional target selenoproteins in Escherichia coli by site-specifically inserting Sec into the proteins’ active sites. Overall, our work demonstrates the feasibility of creating functional mRNA–rRNA fusions as a strategy for ribosome engineering, providing a novel tool for producing Sec-containing proteins in live bacterial cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Single-atom heat engine as a sensitive thermal probe

We propose employing a quantum heat engine as a sensitive probe for thermal baths. In particular, we study a single-atom Otto engine operating in an open thermodynamic cycle. Owing to its cyclic nature, the engine is capable of translating small temperature differences between two baths into a macroscopic oscillation in a flywheel. We present analytical and numerical modeling of the quantum dynamics of the engine and estimate it to be capable of detecting temperature differences as small as 2 μK. This sensitivity can be further improved by utilizing quantum resources such as squeezing of the ion motion. The proposed scheme does not require quantum state initialization and is able to detect small temperature differences in a wide range of base temperatures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering

Lidar-assisted control is a promising technology for reducing the levelized cost of energy from wind turbines, but quantifying its impact at the overall system level requires sophisticated systems engineering analysis and optimization frameworks. The joint workshop on Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering was held by the International Energy Agency Wind Task 32 (Lidar) and Task 37 (Systems Engineering) in October 2019 to address this challenge. This paper summarizes the outcome of the workshop and presents a road map for further research. The most promising applications of lidar-assisted control identified at the workshop and discussed here include 1) increasing annual energy production, 2) decreasing capital expenditure costs by reducing design loads, 3) extending turbine lifetime by reducing operating loads, and 4) enabling wind turbine class upgrades. For each application, we review the state of the art and highlight remaining research needs. Finally, we discuss strategies for addressing these research needs by conducting high-fidelity systems engineering optimizations.

17 WIND ENERGY↗
DOE OSTI2026

Dressed-State Hamiltonian Engineering in a Strongly Interacting Solid-State Spin Ensemble

In quantum science applications, ranging from many-body physics to quantum metrology, dipolar interactions in spin ensembles are often controlled via Floquet engineering. However, this technique typically reduces the interaction strength between spins and effectively weakens the coupling to a target sensing field, limiting the metrological sensitivity. In this Letter, we develop and demonstrate an alternative method that directly tunes the native dipolar interaction in an ensemble of nitrogen-vacancy (NV) centers in diamond, thereby overcoming these limitations inherent to Floquet engineering. Our approach utilizes dressed-state qubit encoding under a bias magnetic field applied perpendicular to the crystal lattice orientation. This method leads to a 3.2× enhancement of the dimensionless coherence parameter JT 2 compared to state-of-the-art Floquet engineering and a 2.6× (8.3 dB) enhanced sensitivity in ac magnetometry. Furthermore, our results provide a powerful Hamiltonian engineering tool for future studies with NV ensembles and other interacting higher-spin (S > $\frac{1}{2}$) systems.

Quantum control↗
DOE OSTI2021

Quantum Engineering With Hybrid Magnonic Systems and Materials (Invited Paper)

Quantum technology has made tremendous strides over the past two decades with remarkable advances in materials engineering, circuit design and dynamic operation. In particular, the integration of different quantum modules has benefited from hybrid quantum systems, which provide an important pathway for harnessing the different natural advantages of complementary quantum systems and for engineering new functionalities. This review focuses on the current frontiers with respect to utilizing magnetic excitations or magnons for novel quantum functionality. Magnons are the fundamental excitations of magnetically ordered solid-state materials and provide great tunability and exibility for interacting with various quantum modules for integration in diverse quantum systems. The concomitant rich variety of physics and material selections enable exploration of novel quantum phenomena in materials science and engineering. In addition, the relative ease of generating strong coupling and forming hybrid dynamic systems with other excitations makes hybrid magnonics a unique platform for quantum engineering. We start our discussion with circuit-based hybrid magnonic systems, which are coupled with microwave photons and acoustic phonons. Subsequently, we are focusing on the recent progress of magnon-magnon coupling within confined magnetic systems. Next we highlight new opportunities for understanding the interactions between magnons and nitrogen-vacancy centers for quantum sensing and implementing quantum interconnects. Lastly, we focus on the spin excitations and magnon spectra of novel quantum materials investigated with advanced optical characterization.

42 ENGINEERING↗
DOE OSTI2023

Environmental microbiome engineering for the mitigation of climate change

Abstract Environmental microbiome engineering is emerging as a potential avenue for climate change mitigation. In this process, microbial inocula are introduced to natural microbial communities to tune activities that regulate the long‐term stabilization of carbon in ecosystems. In this review, we outline the process of environmental engineering and synthesize key considerations about ecosystem functions to target, means of sourcing microorganisms, strategies for designing microbial inocula, methods to deliver inocula, and the factors that enable inocula to establish within a resident community and modify an ecosystem function target. Recent work, enabled by high‐throughput technologies and modeling approaches, indicate that microbial inocula designed from the top‐down, particularly through directed evolution, may generally have a higher chance of establishing within existing microbial communities than other historical approaches to microbiome engineering. We address outstanding questions about the determinants of inocula establishment and provide suggestions for further research about the possibilities and challenges of environmental microbiome engineering as a tool to combat climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cooled Spray Technology for Particulate Reduction in a Heavy-Duty Engine

Cooled spray (CS) technology passively reduces particulate matter (PM) emissions from diesel engines compared to non-CS-equipped diesel engines. CS inserts are mounted near the injector nozzle and control mixing so that the fuel and air can premix while limiting combustion near fuel-rich zones, thereby reducing the formation of particulate matter. CS components contain no moving parts and could be installed as a retrofit or built into new engines. However, CS technology is early in its development, and further investigations are needed to understand the overall performance implications and practicality of the technology. In this paper, we investigate several important aspects of CS, providing a clearer picture of some challenges and potential benefits of CS. Two alignment techniques are used to characterize measurement ease and bias, namely, an optical alignment and spray-plug impact alignment. While the optical technique facilitates alignment more easily, a bias was measured between the optical and spray-plug techniques, suggesting the optical technique may have insufficient accuracy without additional corrections. We also evaluate the engine performance of a well-aligned and poorly aligned CS insert, compared to the baseline configuration. The poorly aligned insert shows slower combustion than the baseline and mixed overall performance. However, the well-aligned insert shows faster combustion than the baseline and PM emission reduction at most operating conditions, with some conditions showing PM reduction up to 80%. Furthermore, the results of this paper highlight the alignment challenges of CS technology as well as the potential PM reduction benefit of the technology.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Deep reinforcement learning for dynamic control of fuel injection timing in multi-pulse compression ignition engines

Conventional compression-ignition (CI) engines have long offered high thermal efficiencies and torque across a wide range of loads, but often require extensive exhaust gas treatment that decreases efficiency to meet ever-increasing emissions regulations. One strategy to decrease emissions is to split the fuel injection into a series of smaller injections. In this paper, we explore a new way of discovering optimal control strategies for the next generation of CI engines using deep reinforcement learning (DRL). We outline a DRL procedure to maximize the weighted reward of engine work while minimizing end-of-cycle NO x emissions. Through the procedure outlined in this paper, we show that the DRL agent is able to reduce NO x emissions threefold while only decreasing network by 2%. We demonstrate the use of transfer learning (TL) across hierarchies of physical models to accelerate the learning process, making this approach feasible for a range of control problems within this space. This paper presents a framework and demonstration for using DRL to design control systems in technology areas such as multi-pulse engine control where a hierarchy of models combined with multi-objective rewards are used for optimal operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Fuel-air mixing in motored CFR engine at research octane number (RON) relevant condition

This paper presents a three-dimensional (3-D) computational fluid dynamics (CFD) study of a motored cooperative fuel research (CFR) engine at research octane number (RON) relevant condition. The boundary conditions for 3-D simulations were generated with a one-dimensional GT-Power model. For the first time in literature, a carburetor was added to a virtual CFR engine model with 3-D CFD. Therefore, the proposed setup can simulate the fuel and thermal stratifications inside the engine cylinder with realistic detail. The transient simulations in this work were performed within the Reynolds-averaged Navier-Stokes (RANS) framework with a Realizable k-ε turbulence model. Major conclusions from the present work are: (1) The in-cylinder flow of the CFR engine is swirl-dominated due to the existence of the intake valve shroud. (2) There is a significant amount of liquid droplets entering the cylinder during the intake stroke. The maximum instantaneous amount of liquid for 50% PRF 87 (containing 87% iso-octane and 13% n-heptane (v/v)) and 50% ethanol mixture is indicated to be around 26% of total injected fuel mass. (3) The heat of vaporization (HoV) of the fuel is responsible for creating both temperature and charge stratification inside the cylinder.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Systematic approaches to C-lignin engineering in Medicago truncatula

Abstract Background C-lignin is a homopolymer of caffeyl alcohol present in the seed coats of a variety of plant species including vanilla orchid, various cacti, and the ornamental plant Cleome hassleriana . Because of its unique chemical and physical properties, there is considerable interest in engineering C-lignin into the cell walls of bioenergy crops as a high-value co-product of bioprocessing. We have used information from a transcriptomic analysis of developing C. hassleriana seed coats to suggest strategies for engineering C-lignin in a heterologous system, using hairy roots of the model legume Medicago truncatula . Results We systematically tested strategies for C-lignin engineering using a combination of gene overexpression and RNAi-mediated knockdown in the caffeic acid/5-hydroxy coniferaldehyde 3/5-O-methyltransferase ( comt ) mutant background, monitoring the outcomes by analysis of lignin composition and profiling of monolignol pathway metabolites. In all cases, C-lignin accumulation required strong down-regulation of caffeoyl CoA 3- O -methyltransferase (CCoAOMT) paired with loss of function of COMT. Overexpression of the Selaginella moellendorffii ferulate 5-hydroxylase ( SmF5H ) gene in comt mutant hairy roots resulted in lines that unexpectedly accumulated high levels of S-lignin. Conclusion C-Lignin accumulation of up to 15% of total lignin in lines with the greatest reduction in CCoAOMT expression required the strong down-regulation of both COMT and CCoAOMT, but did not require expression of a heterologous laccase, cinnamyl alcohol dehydrogenase (CAD) or cinnamoyl CoA reductase (CCR) with preference for 3,4-dihydroxy-substituted substrates in M. truncatula hairy roots. Cell wall fractionation studies suggested that the engineered C-units are not present in a heteropolymer with the bulk of the G-lignin.

09 BIOMASS FUELS↗
DOE OSTI2021

Data for Cloning and Characterization of a Panel of Mitochondrial Targeting Sequences for Compartmentalization Engineering in Saccharomyces cerevisiae

Mitochondrion is generally considered as the most promising subcellular organelle for compartmentalization engineering. Much progress has been made in reconstituting whole metabolic pathways in the mitochondria of yeast to harness the precursor pools (i.e., pyruvate and acetyl-CoA), bypass competing pathways, and minimize transportation limitations. However, only a few mitochondrial targeting sequences (MTSs) have been characterized (i.e., MTS of COX4), limiting the application of compartmentalization engineering for multigene biosynthetic pathways in the mitochondria of yeast. In the present study, based on the mitochondrial proteome, a total of 20 MTSs were cloned and the efficiency of these MTSs in targeting heterologous proteins, including the Escherichia coli FabI and enhanced green fluorescence protein (EGFP) into the mitochondria was evaluated by growth complementation and confocal microscopy. After systematic characterization, six of the well-performed MTSs were chosen for the colocalization of complete biosynthetic pathways into the mitochondria. As proof of concept, the full α-santalene biosynthetic pathway consisting of 10 expression cassettes capable of converting acetyl-coA to α-santalene was compartmentalized into the mitochondria, leading to a 3.7-fold improvement in the production of α-santalene. The newly characterized MTSs should contribute to the expanded metabolic engineering and synthetic biology toolbox for yeast mitochondrial compartmentalization engineering.

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