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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Metabolic engineering of energycane to hyperaccumulate lipids in vegetative biomass

Abstract Background The metabolic engineering of high-biomass crops for lipid production in their vegetative biomass has recently been proposed as a strategy to elevate energy density and lipid yields for biodiesel production. Energycane and sugarcane are highly polyploid, interspecific hybrids between Saccharum officinarum and Saccharum spontaneum that differ in the amount of ancestral contribution to their genomes. This results in greater biomass yield and persistence in energycane, which makes it the preferred target crop for biofuel production. Results Here, we report on the hyperaccumulation of triacylglycerol (TAG) in energycane following the overexpression of the lipogenic factors Diacylglycerol acyltransferase 1-2 ( DGAT 1-2) and Oleosin 1 ( OLE 1) in combination with RNAi suppression of SUGAR-DEPENDENT 1 ( SDP 1) and Trigalactosyl diacylglycerol 1 ( TGD 1). TAG accumulated up to 1.52% of leaf dry weight (DW,) a rate that was 30-fold that of non-modified energycane, in addition to almost doubling the total fatty acid content in leaves to 4.42% of its DW. Pearson’s correlation analysis showed that the accumulation of TAG had the highest correlation with the expression level of ZmDGAT 1-2, followed by the level of RNAi suppression for SDP 1. Conclusions This is the first report on the metabolic engineering of energycane and demonstrates that this resilient, high-biomass crop is an excellent target for the further optimization of the production of lipids from vegetative tissues.

1-2↗
DOE OSTI2019

Engineered Pseudomonas putida KT2440 co-utilizes galactose and glucose

Abstract Background Efficient conversion of plant biomass to commodity chemicals is an important challenge that needs to be solved to enable a sustainable bioeconomy. Deconstruction of biomass to sugars and lignin yields a wide variety of low molecular weight carbon substrates that need to be funneled to product. Pseudomonas putida KT2440 has emerged as a potential platform for bioconversion of lignin and the other components of plant biomass. However, P. putida is unable to natively utilize several of the common sugars in hydrolysate streams, including galactose. Results In this work, we integrated a De Ley–Doudoroff catabolic pathway for galactose catabolism into the chromosome of P. putida KT2440, using genes from several different organisms. We found that the galactonate catabolic pathway alone (DgoKAD) supported slow growth of P. putida on galactose. Further integration of genes to convert galactose to galactonate and to optimize the transporter expression level resulted in a growth rate of 0.371 h −1 . Additionally, the best-performing strain was demonstrated to co-utilize galactose with glucose. Conclusions We have engineered P. putida to catabolize galactose, which will allow future engineered strains to convert more plant biomass carbon to products of interest. Further, by demonstrating co-utilization of glucose and galactose, continuous bioconversion processes for mixed sugar streams are now possible.

09 BIOMASS FUELS↗
DOE OSTI2021

Identification and characterization of proteins of unknown function (PUFs) in Clostridium thermocellum DSM 1313 strains as potential genetic engineering targets

Abstract Background Mass spectrometry-based proteomics can identify and quantify thousands of proteins from individual microbial species, but a significant percentage of these proteins are unannotated and hence classified as proteins of unknown function (PUFs). Due to the difficulty in extracting meaningful metabolic information, PUFs are often overlooked or discarded during data analysis, even though they might be critically important in functional activities, in particular for metabolic engineering research. Results We optimized and employed a pipeline integrating various “guilt-by-association” (GBA) metrics, including differential expression and co-expression analyses of high-throughput mass spectrometry proteome data and phylogenetic coevolution analysis, and sequence homology-based approaches to determine putative functions for PUFs in Clostridium thermocellum . Our various analyses provided putative functional information for over 95% of the PUFs detected by mass spectrometry in a wild-type and/or an engineered strain of C. thermocellum . In particular, we validated a predicted acyltransferase PUF (WP_003519433.1) with functional activity towards 2-phenylethyl alcohol, consistent with our GBA and sequence homology-based predictions. Conclusions This work demonstrates the value of leveraging sequence homology-based annotations with empirical evidence based on the concept of GBA to broadly predict putative functions for PUFs, opening avenues to further interrogation via targeted experiments.

09 BIOMASS FUELS↗
DOE OSTI2023

Metabolic engineering to improve production of 3-hydroxypropionic acid from corn-stover hydrolysate in Aspergillus species

Fuels and chemicals derived from non-fossil sources are needed to lessen human impacts on the environment while providing a healthy and growing economy. 3-hydroxypropionic acid (3-HP) is an important chemical building block that can be used for many products. Biosynthesis of 3-HP is possible; however, low production is typically observed in those natural systems. Biosynthetic pathways have been designed to produce 3-HP from a variety of feedstocks in different microorganisms. In this study, the 3-HP β-alanine pathway consisting of aspartate decarboxylase, β-alanine-pyruvate aminotransferase, and 3-hydroxypropionate dehydrogenase from selected microorganisms were codon optimized for Aspergillus species and placed under the control of constitutive promoters. The pathway was introduced into Aspergillus pseudoterreus and subsequently into Aspergillus niger, and 3-HP production was assessed in both hosts. A. niger produced higher initial 3-HP yields and fewer co-product contaminants and was selected as a suitable host for further engineering. Proteomic and metabolomic analysis of both Aspergillus species during 3-HP production identified genetic targets for improvement of flux toward 3-HP including pyruvate carboxylase, aspartate aminotransferase, malonate semialdehyde dehydrogenase, succinate semialdehyde dehydrogenase, oxaloacetate hydrolase, and a 3-HP transporter. Overexpression of pyruvate carboxylase improved yield in shake-flasks from 0.09 to 0.12 C-mol 3-HP C-mol -1 glucose in the base strain expressing 12 copies of the β-alanine pathway. Deletion or overexpression of individual target genes in the pyruvate carboxylase overexpression strain improved yield to 0.22 C-mol 3-HP C-mol -1 glucose after deletion of the major malonate semialdehyde dehydrogenase. Further incorporation of additional β-alanine pathway genes and optimization of culture conditions (sugars, temperature, nitrogen, phosphate, trace elements) for 3-HP production from deacetylated and mechanically refined corn stover hydrolysate improved yield to 0.48 C-mol 3-HP C-mol -1 sugars and resulted in a final titer of 36.0 g/L 3-HP. The results of this study establish A. niger as a host for 3-HP production from a lignocellulosic feedstock in acidic conditions and demonstrates that 3-HP titer and yield can be improved by a broad metabolic engineering strategy involving identification and modification of genes participated in the synthesis of 3-HP and its precursors, degradation of intermediates, and transport of 3-HP across the plasma membrane.

09 BIOMASS FUELS↗
DOE OSTI2023

Ethanol tolerance in engineered strains of Clostridium thermocellum

Abstract Clostridium thermocellum is a natively cellulolytic bacterium that is promising candidate for cellulosic biofuel production, and can produce ethanol at high yields (75–80% of theoretical) but the ethanol titers produced thus far are too low for commercial application. In several strains of C. thermocellum engineered for increased ethanol yield, ethanol titer seems to be limited by ethanol tolerance. Previous work to improve ethanol tolerance has focused on the WT organism. In this work, we focused on understanding ethanol tolerance in several engineered strains of C. thermocellum . We observed a tradeoff between ethanol tolerance and production. Adaptation for increased ethanol tolerance decreases ethanol production. Second, we observed a consistent genetic response to ethanol stress involving mutations at the AdhE locus. These mutations typically reduced NADH-linked ADH activity. About half of the ethanol tolerance phenotype could be attributed to the elimination of NADH-linked activity based on a targeted deletion of adhE . Finally, we observed that rich growth medium increases ethanol tolerance, but this effect is eliminated in an adhE deletion strain. Together, these suggest that ethanol inhibits growth and metabolism via a redox-imbalance mechanism. The improved understanding of mechanisms of ethanol tolerance described here lays a foundation for developing strains of C. thermocellum with improved ethanol production.

09 BIOMASS FUELS↗
DOE OSTI2023

Tolerance of engineered Rhodosporidium toruloides to sorghum hydrolysates during batch and fed-batch lipid production

Abstract Background Oleaginous yeasts are a promising candidate for the sustainable conversion of lignocellulosic feedstocks into fuels and chemicals, but their growth on these substrates can be inhibited as a result of upstream pretreatment and enzymatic hydrolysis conditions. Previous studies indicate a high citrate buffer concentration during hydrolysis inhibits downstream cell growth and ethanol fermentation in Saccharomyces cerevisiae . In this study, an engineered Rhodosporidium toruloides strain with enhanced lipid accumulation was grown on sorghum hydrolysate with high and low citrate buffer concentrations. Results Both hydrolysis conditions resulted in similar sugar recovery rates and concentrations. No significant differences in cell growth, sugar utilization rates, or lipid production rates were observed between the two citrate buffer conditions during batch fermentation of R. toruloides . Under fed-batch growth on low-citrate hydrolysate a lipid titer of 16.7 g/L was obtained. Conclusions Citrate buffer was not found to inhibit growth or lipid production in this engineered R. toruloides strain, nor did reducing the citrate buffer concentration negatively affect sugar yields in the hydrolysate. As this process is scaled-up, $131 per ton of hydrothermally pretreated biomass can be saved by use of the lower citrate buffer concentration during enzymatic hydrolysis. Graphical Abstract

09 BIOMASS FUELS↗
DOE OSTI2023

Data for Tolerance of Engineered Rhodosporidium toruloides to Sorghum Hydrolysates During Batch and Fed-Batch Lipid Production

Oleaginous yeasts are a promising candidate for the sustainable conversion of lignocellulosic feedstocks into fuels and chemicals, but their growth on these substrates can be inhibited as a result of upstream pretreatment and enzymatic hydrolysis conditions. Previous studies indicate a high citrate buffer concentration during hydrolysis inhibits downstream cell growth and ethanol fermentation in Saccharomyces cerevisiae . In this study, an engineered Rhodosporidium toruloides strain with enhanced lipid accumulation was grown on sorghum hydrolysate with high and low citrate buffer concentrations. Both hydrolysis conditions resulted in similar sugar recovery rates and concentrations. No significant differences in cell growth, sugar utilization rates, or lipid production rates were observed between the two citrate buffer conditions during batch fermentation of R. toruloides . Under fed-batch growth on low-citrate hydrolysate a lipid titer of 16.7 g/L was obtained. Citrate buffer was not found to inhibit growth or lipid production in this engineered R. toruloides strain, nor did reducing the citrate buffer concentration negatively affect sugar yields in the hydrolysate. As this process is scaled-up, $131 per ton of hydrothermally pretreated biomass can be saved by use of the lower citrate buffer concentration during enzymatic hydrolysis.

Conversion↗
DOE OSTI2022

Data for Bioprocessing, Recovery, and Mass Balance of Vegetative Lipids from Metabolically Engineered ‘Oilcane’ Demonstrates Its Potential as an Alternative Feedstock for Drop-In Fuel Production

Plant oils are increasingly in demand as renewable feedstocks for biodiesel and biochemicals. Currently, oilseeds are the primary source of plant oils. Although the vegetative tissues of plants express lipid metabolism pathways, they do not hyper-accumulate lipids. Elevated synthesis, storage, and accumulation of lipids in vegetative tissues have been achieved by metabolic engineering of sugarcane to produce “oilcane.” This study evaluates the potential of oilcane as a renewable feedstock for the co-production of lipids and fermentable sugars. Oilcane was grown under favorable climatic and field conditions in Florida (FLOC) as well as during an abbreviated growing season, outside its typical growing region, in Illinois (ILOC). The potential lipid yield of 0.35 tons/ha was projected from the hyperaccumulation of fatty acids in the stored vegetative biomass of FLOC, which is approaching the lipid yield of soybean (0.44 tons/ha). Processing of the vegetative tissues of oilcane recovered 0.20 tons/ha, which represents the recovery of 55% of the total lipids from FLOC. Chemical-free hydrothermal bioprocessing of ILOC and FLOC bagasse and leaves at 180 °C for 10 min prevented the degeneration of in situ plant lipids. This allowed the recovery of lipids at the end of the bioprocess with a major fraction of lipids remaining in the biomass residues after pretreatment and saccharification. Improvements through refined biomass processing, crop management, and metabolic engineering are expected to boost lipid yields and make oilcane a prime feedstock for the production of biodiesel.

Conversion↗
DOE OSTI2023

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗
DOE OSTI2022

Historical review and proof-of-concept future method demonstration of adaptive mesh refinement in nuclear engineering for increased fidelity and computational efficiency

As the nuclear industry's use of computational tool increases, the need for increased fidelity and computational efficiency is well known. While most approaches to increased fidelity rely on applying a fine mesh over the problem domain, a more efficient method is to apply an adaptive mesh refinement (AMR) algorithm to the mesh definition. In the field of nuclear engineering, AMR has previously been used in conjunction with deterministic methods, including: S{sub N} transport methods, Lattice Boltzmann Methods, and COMSOL. The future of AMR in nuclear engineering is to couple it to a Monte Carlo code with the goal of reducing calculation time. A proof-of-concept example yielded positive results for using the gradient of the flux as a refinement criteria. The refinement criteria was varied from 0.01 to 0.10, which yielded a recommended range of 0.01 to 0.04, and the number of refinement iterations was varied from 0 to 7, with diminishing returns seen after 5 iterations. After the success of the proof-of-concept exercise, work began on creating a full program coupling MCNP6.2 and the AMR algorithm in the deal.II library. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Description and Use of SCALE Sampler Parametric Capability for Engineering Analysis and Optimization

The Sampler sequence was introduced into the SCALE nuclear modeling and simulation suite in SCALE 6.2 to perform uncertainty quantification via random sampling of nuclear data, material number densities, and dimensions. Sampler was expanded with the introduction of a parametric capability in SCALE 6.2.2. This paper discusses input for the Sampler parametric sequence and presents two case studies of analyses performed using the sequence. These case studies include preconceptual design of a package for transporting high assay low-enriched uranium (HALEU) oxide and scoping calculations to support subcritical limit development for a future update of the ANSI/ANS-8.1 (ANS-8.1) standard. The parametric capability within Sampler provides many benefits to analysts. For instance, parametric sweeps are frequently used to identify optimum parameter values as part of safety analysis or system design, but such sweeps can require substantial engineering time or may rely on custom-written scripts or scripts such as Write One, Run Many (or WORM) developed outside of any software quality assurance program. With the parametric capabilities in Sampler, however, a large number of inputs can be generated automatically without recourse to scripting by individual analysts. The parametric capability can also be used in lieu of the CSAS5S search sequence to identify optimum parameters more simply with straightforward inputs and outputs. Sampler can also be used to calculate input parameters from engineering specifications. For example, diameters can be converted to radii, or masses can be used to calculate number densities. Overall, the Sampler parametric capability provides a robust feature within SCALE, eliminating the need for user-developed scripting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Fabrication of engineered dopant profiles in Er/Lu:YAG transparent laser ceramics via additive manufacturing

Transparent ceramic Er:YAG laser rods were fabricated via the direct ink write (DIW) method with engineered doping profiles featuring an Er-doped core with endcaps and core-clad structures. Laser rods up to 11 cm in length were produced which required development of a scalable process. To achieve this, multiple improvements were implemented, including printing the rods horizontally on a substrate, rather than vertically, eliminating the need for an external support structure and using a sacrificial drying layer to mitigate warping and defects. Highly transparent rods were achieved with optical scatter levels as low as 0.5%/cm (at 543 nm). A small refractive index difference of 5.7 ppm was measured at the interface between the Er-doped core and the Lu-doped endcaps and cladding. These results demonstrate DIW as a straightforward method for making good optical quality laser rods with engineered doping profiles to improve laser performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Phonon engineering of boron nitride via isotopic enrichment

Phonon polaritons (PhPs) enable a variety of applications, yet it requires PhPs supported in the desired frequency range. The two BN allotropes (cubic and hexagonal, cBN and hBN) are of particular interest, as their optic phonons fall within the so-called molecular-fingerprint region (~ 1000–1610 cm -1 ). However, there remains a spectral gap between PhPs covered by these two, limiting applications. Thus, we isotopically engineered hBN and cBN and examined the optic phonons. Furthermore, for hBN, enhancement of the optic phonon lifetimes and shifted frequencies are observed. However, lifetimes are observed to decrease with the enrichment of cBN by 10 B, 11 B, and 15 N. We propose that the reduced lifetimes are not due to intrinsic loss, but rather increased defect concentrations resulting from the modified growth, supported by first-principles calculations. Thus, reducing the extrinsic defects in isotopically engineered cBN may present a path toward overcoming these restrictions for applications in the molecular-fingerprint region.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optimizing thermal stability and mechanical behavior in segregation-engineered nanocrystalline Al–Ni–Ce alloys: A combinatorial study

The deliberate use of solute enrichment at grain boundaries, otherwise known as segregation engineering, is a promising approach to tailor the properties of interface-dominated materials such as nanocrystalline alloys. Here, the ensuing chemical and structural evolution at grain boundaries can give rise to thermal stability and excellent mechanical properties, but the interplay between enrichment, phase decomposition, grain growth, and mechanical behavior exists in a vast composition and processing space. In this study, a combinatorial synthesis and rapid characterization approach was applied to segregation-engineered nanocrystalline Al–Ni–Ce alloys to assess the evolution of microstructure and resulting mechanical behavior as functions of alloying content and annealing conditions. In addition to the identification of alloys and processing conditions that give rise to exceptional thermal stability, strength retention, and homogeneous plastic flow, we construct combined thermal stability and deformation mechanism maps that demarcate several important regimes of behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nuclear spin engineering for quantum information science

Semiconductors are the backbone of modern technology, garnering decades of investment in high-quality materials and devices. Electron spin systems in semiconductors, including atomic defects and quantum dots, have been demonstrated in the last two decades to host quantum coherent spin qubits, often with coherent spin–photon interfaces and proximal nuclear spins. These systems are at the center of developing quantum technology. However, new material challenges arise when considering the isotopic composition of host and qubit systems. The isotopic composition governs the nature and concentration of nuclear spins, which naturally occur in leading host materials. These spins generate magnetic noise—detrimental to qubit coherence—but also show promise as local quantum memories and processors, necessitating careful engineering dependent on the targeted application. Reviewing recent experimental and theoretical progress toward understanding local nuclear spin environments in semiconductors, we show this aspect of material engineering as critical to quantum information technology.

Defects↗
DOE OSTI2021

2020 ETI Annual Summer School: Data Science and Engineering

The Consortium for Enabling Technologies & Innovation (ETI) was established in 2019 to address emerging technologies within the context of nuclear nonproliferation. ETI creates a research and education environment to support cross-cutting technologies across three core disciplines: 1) computer and engineering science research specifically in a form of machine learning and high performance computing (HPC), 2) advanced manufacturing, and 3) nuclear detection technologies. For outreach and development, ETI hosted the first of three summer schools from August 24-28, 2020 with the theme of “Data Science and Engineering”. The school was hosted in an on-line format and had over 200 participants. The recorded content is available on-line as a resource for students. The summer school had four modules: 1) Fundamentals of data Applications, 2) Computational Machine Learning, 3) Bayesian Modeling and Inference, and 4) Data Science for Safeguards. Modules contained both lectures as well as student exercises. Poll Everywhere was utilized in some modules as an on-line method to engage large groups of students. Upcoming ETI Summer Schools include Novel Instrumentation in 2021 and Advanced Manufacturing in 2022.

Biegalski, Steven R.↗
DOE OSTI2024

An engineering prototype of a late stage ionization cooling cell for a muon collider

Achieving the low emittances necessary for a muon collider requires ionization cooling. Much of that cooling occurs in compact cooling cells where superconducting coils and conventional RF cavities are closely interleaved [1]. The real challenges for these cooling cells reside in their engineering challenges: high field solenoids, RF cavities, and absorbers, often designed near technological limits, placed in close proximity to each other. We thus propose to build a prototype ionization cooling cell to demonstrate the capability of constructing an ionization cooling channel reaching the lowest emittances and to provide engineering input for the design of such beamlines. The magnets and cavities will be powered at their design values, and an absorber will be included along with a mechanism for heating the absorber similarly to how a beam would.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Thermosteam: BioSTEAM's Premier Thermodynamic Engine

Thermosteam is a thermodynamic engine capable of solving mass and energy balances, estimating mixture properties, solving thermodynamic phase equilibria, and modeling stoichiometric reactions. All chemical data in Thermosteam is imported from the chemicals library, an open-source compilation of data and functions for the estimation of pure component chemical and mixture properties. Thermosteam’s fast and flexible platform has enabled the evaluation of conceptual and emerging biochemical production processes. The Biorefinery Simulation and Techno-Economic Analysis Modules (BioSTEAM) — capable of modeling reactors, distillation columns, heat exchangers, and other unit operations — has adopted Thermosteam as its premier thermodynamic engine. Published biorefinery designs modeled in BioSTEAM implement thermodynamic property packages created with Thermosteam, including a cornstover biorefinery for the production of cellulosic ethanol, a lipid-cane biorefinery for the co-production of ethanol and biodiesel, and a wheatstraw biorefinery for the production of cellulosic ethanol.

97 MATHEMATICS AND COMPUTING↗