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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Additively Reinforced Thermoformable PETG Composite Sheets for Improved Structural Efficiency

Thermoforming of short-fiber reinforced thermoplastic sheets offers a viable pathway for producing lightweight composite components; however, inherent anisotropy in fiber-reinforced sheets can limit structural performance under multidirectional loading. In this work, short carbon fiber, glass fiber, and hybrid fiber–reinforced PETG sheets were evaluated as candidate feedstock materials for thermoforming, with flexural and tensile testing performed both along the primary fiber direction and in the off-axis orientation to establish baseline stiffness, strength, and anisotropy. As expected, short carbon fiber PETG exhibited the highest stiffness and strength in the primary fiber direction, while all systems showed reduced performance in the off-axis direction. This off-axis performance reduction provides clear justification for the use of additive reinforcement when such thermoformed sheets are intended for structural applications. The intended manufacturing sequence involves thermoforming the reinforced sheet first, followed by the application of additively manufactured lattice reinforcement; therefore, the reinforcement strategy does not impose limitations on sheet formability during thermoforming. Post-forming lattice reinforcement significantly reduced load-normalized displacement by approximately 95–99% relative to non-reinforced sheets and improved weight-normalized stiffness by ~70%. These findings demonstrate that geometry-driven additive reinforcement can effectively compensate for off-axis property reductions in thermoformed PETG composites, enabling enhanced multidirectional structural performance without compromising manufacturability.

Talabi, Isaac [ORNL] (ORCID:0000000340215594)↗
DOE OSTI2022

Programmable pseudo-random sequence generator for use with universal lidar and its associated method of operation

A pseudo-random sequence generator for use within a universal lidar system and its corresponding method of operation. The pseudo-random sequence generator uses synchronized shift registers that are in series Binary adders are provided. The signal output of each of the shift registers is tapped and directed to the binary adders. High-speed switches are provided between the shift registers and the binary adders. The switches are programmed to connect only two of the shift registers to the binary adders for each of the pseudo-random patterns being generated. The binary adders generate an output signal that is received by the first shift register. The signal propagates through all the shift registers to the last shift register. The last shift register outputs a pseudo-random sequence.

Datta, Shubhashish↗
DOE OSTI2023

Unraveling Anisotropic and Pulsating Etching of ZnO Nanorods in Hydrochloric Acid via Correlative Electron Microscopy

Despite much technical progress achieved so far, the exact surface and shape evolution during wet chemical etching is less unraveled, especially in ionically bonded ceramics. Herein, by using in situ liquid cell transmission electron microscopy, a repeated two-stage anisotropic and pulsating periodic etching dynamic is discovered during the pencil shape evolution of a single crystal ZnO nanorod in aqueous hydrochloric acid. Specifically, the nanopencil tip shrinks at a slower rate along [0001̅] than that along the $\langle$101̅0$\rangle$ directions, resulting in a sharper ZnO pencil tip. Afterward, rapid tip dissolution happens due to accelerated etching rates along various crystal directions. Concurrently, the vicinal base region of the original nanopencil tip emerges as a new tip followed by the repeated sequence of tip shrinking and removal. The high-index surfaces, such as {101̅m} (m = 0, 1, 2, or 3) and {21̅1̅n} (n = 0, 1, 2, or 3), are found to preferentially expose in different ratios. Our 3D electron tomography, convergent beam electron diffraction, middle-angle bright-field STEM, and XPS results indicate the dissociative Cl – species were bound to the Zn-terminated tip surfaces. Furthermore, DFT calculation suggests the preferential Cl – passivation over the {101̅1} and (0001) surfaces of lower energy than others, leading to preferential surface exposures and the oscillatory variation of different facet etching rates. The boosted reactivity due to high-index nanoscale surface exposures is confirmed by comparatively enhanced chemical sensing and CO 2 hydrogenation activity. In conclusion, these findings provide an in-depth understanding of anisotropic wet chemical etching of ionic nanocrystals and offer a design strategy for advanced functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electrochemical Observation and pH Dependence of All Three Expected Redox Couples in an Extremophilic Bifurcating Electron Transfer Flavoprotein with Fused Subunits

Bifurcating enzymes employ energy from a favorable electron transfer to drive unfavorable transfer of a second electron, thereby generating a more reactive product. They are therefore highly desirable in catalytic systems, for example, to drive challenging reactions such as nitrogen fixation. While most bifurcating enzymes contain air-sensitive metal centers, bifurcating electron transfer flavoproteins (bETFs) employ flavins. However, they have not been successfully deployed on electrodes. Herein, we demonstrate immobilization and expected thermodynamic reactivity of a bETF from a hyperthermophilic archaeon, Sulfolobus acidocaldarius (SaETF). SaETF differs from previously biochemically characterized bETFs in being a single protein, representing a concatenation of the two subunits of known ETFs. However, SaETF retains the chemical properties of heterodimeric bETFs, including possession of two FADs: one that undergoes sequential 1-electron (1e) reductions at high E° and forms an anionic semiquinone, and another that is amenable to lower-E° 2e reduction, including by NADH. We found homologous monomeric ETF genes in archaeal and bacterial genomes, accompanied by genes that also commonly flank heterodimeric ETFs, and SaETF’s sequence conservation is 50% higher with bETFs than with canonical ETFs. Thus, SaETF is best described as a bETF. Our direct electrochemical trials capture reversible redox couples for all three thermodynamically expected redox events. We document electrochemical activity over a range of pH values and reveal a conformational change coupled to proton acquisition that affects the electrochemical activity of the higher-E° FAD. Thus, this well-behaved monomeric bETF opens the door to bioinspired bifurcating devices or bifurcation on a chip.

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

Shock tube experiments on the three-layer Richtmyer–Meshkov instability

Here, a vertical shock tube is used for experiments on the three-layer Richtmyer–Meshkov instability. Two closely spaced membrane-less interfaces are formed by the flow of two different sects of three gases: one with air above CO 2 above SF 6 and the other with helium above air above SF 6 . The lightest of the three gases enters the shock tube at the top of the driven section and flows downward. Conversely, the heaviest gas enters at the bottom of the shock tube and flows upward while the intermediate density gas enters at the middle through porous plates. All three gases are allowed to escape through holes at the layer location, leaving an approximately 30-mm layer of intermediate-density gas suspended between the lightest gas from above and the heaviest gas from below. A single-mode, two-dimensional initial perturbation is then imposed on the lower interface by oscillating the shock tube in the horizontal direction. The flow is visualized by seeding the intermediate gas with particles and illuminating it with a pulsed laser. Image sequences are then captured using high-speed video cameras. Perturbation amplitude measurements are made from the three-layer system and compared with measurements from 2, two-layer systems. It is observed that the presence of the upper, initially flat interface produces a decrease in growth of instability amplitude in the nonlinear phase over an equivalent single-interface configuration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Evolution-inspired design of multicolored photoswitches from a single cyanobacteriochrome scaffold

Significance Cyanobacteriochromes (CBCRs) are small cyanobacterial photoreceptors which are highly diversified and categorized into many lineages based on their primary sequences. In this study, we identified an atypical CBCR exhibiting an orange/green reversible photocycle. Step-by-step site-directed mutagenesis was performed on this native CBCR, and seven new photoconvertible variants were created. During this process, we identified residues crucial for each color tuning event. These seven molecules covering the shorter-wavelength blue-to-orange region would contribute to the future development of multicolored optogenetic tools and are complementary to recently developed molecules sensing longer wavelengths of light.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Reliability processing of remote direct memory access

Methods and systems for monitoring remote transmissions of messages among a plurality of nodes are described. A processing element in a first node may allocate a sequence number to a request to read and/or update data in a second node. The processing element may be different from main processors of the first node. The processing element may send the message and the sequence number to the second node. The processing element may modify a status of the sequence number to an active state, indicating a transmission of the message is pending. The processing element may, in response to a response from the second node, modify the status of the sequence number to an inactive state, indicating a completed transmission of the message. The processing element may, in response to no response from the second node within a time period, resend the message and the sequence number to the second node.

Kumar, Sameer↗
DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A combinatorially complete epistatic fitness landscape in an enzyme active site

Protein engineering often targets binding pockets or active sites which are enriched in epistasis—nonadditive interactions between amino acid substitutions—and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable β-subunit of tryptophan synthase (TrpB) in a nonnative environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences—a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling.

biocatalysis↗
DOE OSTI2020

Probing the Consequences of Cubic Particle Shape and Applied Field on Colloidal Crystal Engineering with DNA

In a magnetic field, cubic Fe 3 O 4 nanoparticles exhibit assembly behavior that is a consequence of a competition between magnetic dipole-dipole and ligand interactions. In most cases, the interactions between short hydrophobic ligands dominate and dictate assembly outcome. To better tune the face-to-face interactions, cubic Fe3O4 nanoparticles were functionalized with DNA. Their assembly behaviors were investigated both with and without an applied magnetic field. Upon application of a field, the tilted orientation of cubes, enabled by the flexible DNA ligand shell, led to an unexpected crystallographic alignment of the entire superlattice, as opposed to just the individual particles, along the field direction as revealed by small and wide-angle X-ray scattering. This observation is dependent upon DNA length and sequence and cube dimensions. Taken together, these studies show how combining physical and chemical control can expand the possibilities of crystal engineering with DNA.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Large-scale harmonic balance simulations with Krylov subspace and preconditioner recycling

The multi-harmonic balance method combined with numerical continuation provides an efficient framework to compute a family of time-periodic solutions, or response curves, for large-scale, nonlinear mechanical systems. The predictor and corrector steps repeatedly solve a sequence of linear systems that scale by the model size and number of harmonics in the assumed Fourier series approximation. In this paper, a novel Newton–Krylov iterative method is embedded within the multi-harmonic balance and continuation algorithm to efficiently compute the approximate solutions from the sequence of linear systems that arise during the prediction and correction steps. Further, the method recycles, or reuses, both the preconditioner and the Krylov subspace generated by previous linear systems in the solution sequence. A delayed frequency preconditioner refactorizes the preconditioner only when the performance of the iterative solver deteriorates. The GCRO-DR iterative solver recycles a subset of harmonic Ritz vectors to initialize the solution subspace for the next linear system in the sequence. The performance of the iterative solver is demonstrated on two exemplars with contact-type nonlinearities and benchmarked against a direct solver with traditional Newton–Raphson iterations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Divergence in the ABA gene regulatory network underlies differential growth control

The phytohormone abscisic acid (ABA) is a central regulator of acclimation to environmental stress; however, its contribution to differences in stress tolerance between species is unclear. To establish a comparative framework for understanding how stress hormone signalling pathways diverge across species, we studied the growth response of four Brassicaceae species to ABA treatment and generated transcriptomic and DNA affinity purification and sequencing datasets to construct a cross-species gene regulatory network (GRN) for ABA. In this work, comparison of genes bound directly by ABA-responsive element binding factors suggests that cis-factors are most important for determining the target loci represented in the ABA GRN of a particular species. Using this GRN, we reveal how rewiring of growth hormone subnetworks contributes to stark differences in the response to ABA in the extremophyte Schrenkiella parvula. Our study provides a model for understanding how divergence in gene regulation can lead to species-specific physiological outcomes in response to hormonal cues.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Magnetic tunnel junction random number generators applied to dynamically tuned probability trees driven by spin orbit torque

Abstract Perpendicular magnetic tunnel junction (pMTJ)-based true-random number generators (RNGs) can consume orders of magnitude less energy per bit than CMOS pseudo-RNGs. Here, we numerically investigate with a macrospin Landau–Lifshitz-Gilbert equation solver the use of pMTJs driven by spin–orbit torque to directly sample numbers from arbitrary probability distributions with the help of a tunable probability tree. The tree operates by dynamically biasing sequences of pMTJ relaxation events, called ‘coinflips’, via an additional applied spin-transfer-torque current. Specifically, using a single, ideal pMTJ device we successfully draw integer samples on the interval [0, 255] from an exponential distribution based on p -value distribution analysis. In order to investigate device-to-device variations, the thermal stability of the pMTJs are varied based on manufactured device data. It is found that while repeatedly using a varied device inhibits ability to recover the probability distribution, the device variations average out when considering the entire set of devices as a ‘bucket’ to agnostically draw random numbers from. Further, it is noted that the device variations most significantly impact the highest level of the probability tree, with diminishing errors at lower levels. The devices are then used to draw both uniformly and exponentially distributed numbers for the Monte Carlo computation of a problem from particle transport, showing excellent data fit with the analytical solution. Finally, the devices are benchmarked against CMOS and memristor RNGs, showing faster bit generation and significantly lower energy use.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

High Throughput expression and characterization of laccases in Saccharomyces cerevisiae

Laccases are oxidative enzymes containing 4 conserved copper heteroatoms. Laccases catalyze cleavage of bonds in lignin using radical chemistry, yet their exact specificity for bonds (such as the β-O-4 or C-C) in lignin remains unknown and may vary with the diversity of laccases across fungi, plants and bacteria. Bond specificity may perhaps even vary for the same enzyme across different reaction conditions. Determining these differences has been difficult due to the fact that heterologous expression of soluble, active laccases has proven difficult. Here we describe the successful heterologous expression of functional laccases in two strains of Saccharomyces cerevisiae, including one we genetically modified with CRISPR. We phylogenically map the enzymes that we successfully expressed, compared to those that did not express. We also describe differences protein sequence differences and pH and temperature profiles and their ability to functionally express, leading to a potential future screening platform for directed evolution of laccases and other ligninolytic enzymes such as peroxidases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Repurposing Hanford Waste Tank AP-106 for Interim Storage of Treated Low-Activity Waste - 20044

Hanford Double-Shell Tank AP-106 is being repurposed to serve as the lag storage tank holding feed for the Direct Feed Low-Activity Waste (DFLAW) process at the Waste Treatment and Immobilization Plant (WTP). The repurposing process is the sequence of tank additions and transfers that will remove the Cs 137 inventory from AP-106. The repurposing process steps are designed to remove Cs-137 more effectively and efficiently as compared to regular supernatant transfers. The process steps are estimated to take 2-months to complete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its “fitness” for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Intestinal microbiome profile of the brown rock sea cucumber ( Holothuria glaberrima ) using ITS and 16S rDNA amplicons from direct mechanical, enzymatic, and chemical metagenomic extraction

Using direct mechanical, enzymatic, and chemical extraction methods, the intestinal microbiome of the marine invertebrate Holothuria glaberrima was obtained. ITS and 16S rDNA regions were sequenced to enrich and investigate the prokaryotic and fungal diversity profiles from different anatomical regions within the sea cucumber’s intestinal biology.

16S↗
DOE OSTI2020

Bypassing the Energy Functional in Density Functional Theory: Direct Calculation of Electronic Energies from Conditional Probability Densities

Density functional calculations can fail for want of an accurate exchange-correlation approximation. The energy can instead be extracted from a sequence of density functional calculations of conditional probabilities (CP DFT). Simple CP approximations yield usefully accurate results for two-electron ions, the hydrogen dimer, and the uniform gas at all temperatures. CP DFT has no self-interaction error for one electron, and correctly dissociates H2, both major challenges. For warm dense matter, classical CP DFT calculations can overcome the convergence problems of Kohn-Sham DFT.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗