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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Deletion of biofilm synthesis in Eubacterium limosum ATCC 8486 improves handling and transformation efficiency

Abstract Eubacterium limosum is an acetogenic bacterium of potential industrial relevance for its ability to efficiently metabolize a range of single carbon compounds. However, extracellular polymeric substance (EPS) produced by the type strain ATCC 8486 is a serious impediment to bioprocessing and genetic engineering. To remove these barriers, here we bioinformatically identified genes involved in EPS biosynthesis, and targeted several of the most promising candidates for inactivation, using a homologous recombination-based approach. Deletion of a single genomic region encoding homologues for epsABC, ptkA, and tmkA resulted in a strain incapable of producing EPS. This strain is significantly easier to handle by pipetting and centrifugation, and retains important wild-type phenotypes including the ability to grow on methanol and carbon dioxide and limited oxygen tolerance. Additionally, this strain is also more genetically tractable with a 2-fold increase in transformation efficiency compared to the highest previous reports. This work advances a simple, rapid protocol for gene knockouts in E. limosum using only the native homologous recombination machinery. These results will hasten the development of this organism as a workhorse for valorization of single carbon substrates, as well as facilitate exploration of its role in the human gut microbiota.

Sanford, Patrick A.↗
DOE OSTI2025

Denoising Seismograms in the Time Domain Using a Deep Learning Model

Deep learning has emerged as a transformative tool for enhancing the extraction of reliable information from seismograms, addressing the increasing demand for precise and efficient seismic data analysis. We introduce an innovative encoder–decoder deep learning model, named WaveDenoiser, designed for noise reduction in the time domain, thereby eliminating the need for spectrogram computations that have been used for existing deep learning tools and significantly improving processing speed. Utilizing the benchmark dataset that is Stanford Earthquake Dataset, we developed three models of varying sizes: base, medium, and large. Notably, the large (referred to as WaveDenoiser) model demonstrated superior performance, achieving a median signal‐to‐noise ratio improvement of 8.8 dB on in‐distribution unseen data (in the same geographic region) and 7.7 dB on out‐distribution unseen data (in a new geographic region), outpacing both the base and medium models. Further evaluation of the WaveDenoiser model revealed a reduction in median arrival‐time errors by 0.02 s for P waves and 0.01 s for S waves when processing waveforms prior to phase picking using PhaseNet on in‐distribution unseen data. When tested on out‐distribution unseen data, the model also effectively reduced the P‐wave median arrival‐time error by 0.02 and 0.01 s in median arrival‐time error for S waves. Importantly, the application of WaveDenoiser resulted in a significant reduction of phase picking outliers by 1.1% to 3.6% for both P and S waves. In addition, we achieved over five times acceleration in processing speed compared with the seisBench implementation of DeepDenoiser. Our findings underscore the potential of WaveDenoiser as a powerful tool for improving seismic data analysis and processing efficiency.

P-waves↗
DOE OSTI2024

Anaerobic benzene oxidation in Geotalea daltonii involves activation by methylation and is regulated by the transition state regulator AbrB

ABSTRACT Benzene is a widespread groundwater contaminant that persists under anoxic conditions. The aim of this study was to more accurately investigate anaerobic microbial degradation pathways to predict benzene fate and transport. Preliminary genomic analysis of Geotalea daltonii strain FRC-32, isolated from contaminated groundwater, revealed the presence of putative aromatic-degrading genes. G. daltonii was subsequently shown to conserve energy for growth on benzene as the sole electron donor and fumarate or nitrate as the electron acceptor. The hbs gene, encoding for 3-hydroxybenzylsuccinate synthase (Hbs), a homolog of the radical-forming, toluene-activating benzylsuccinate synthase (Bss), was upregulated during benzene oxidation in G. daltonii , while the bss gene was upregulated during toluene oxidation. Addition of benzene to the G. daltonii whole-cell lysate resulted in toluene formation, indicating that methylation of benzene was occurring. Complementation of σ 54 - (deficient) E. coli transformed with the bss operon restored its ability to grow in the presence of toluene, revealing bss to be regulated by σ 54 . Binding sites for σ 70 and the transition state regulator AbrB were identified in the promoter region of the σ 54 -encoding gene rpoN, and binding was confirmed. Induced expression of abrB during benzene and toluene degradation caused G. daltonii cultures to transition to the death phase. Our results suggested that G. daltonii can anaerobically oxidize benzene by methylation, which is regulated by σ 54 and AbrB. Our findings further indicated that the benzene, toluene, and benzoate degradation pathways converge into a single metabolic pathway, representing a uniquely efficient approach to anaerobic aromatic degradation in G. daltonii . IMPORTANCE The contamination of anaerobic subsurface environments including groundwater with toxic aromatic hydrocarbons, specifically benzene, toluene, ethylbenzene, and xylene, has become a global issue. Subsurface groundwater is largely anoxic, and further study is needed to understand the natural attenuation of these compounds. This study elucidated a metabolic pathway utilized by the bacterium Geotalea daltonii capable of anaerobically degrading the recalcitrant molecule benzene using a unique activation mechanism involving methylation. The identification of aromatic-degrading genes and AbrB as a regulator of the anaerobic benzene and toluene degradation pathways provides insights into the mechanisms employed by G. daltonii to modulate metabolic pathways as necessary to thrive in anoxic contaminated groundwater. Our findings contribute to the understanding of novel anaerobic benzene degradation pathways that could potentially be harnessed to develop improved strategies for bioremediation of groundwater contaminants.

Bullows, James E.↗
DOE OSTI2021

State-operator correspondence in celestial conformal field theory

The bulk-to-boundary dictionary for 4D celestial holography is given a new entry defining 2D boundary states living on oriented circles on the celestial sphere. The states are constructed using the 2D CFT state-operator correspondence from operator insertions corresponding to either incoming or outgoing particles which cross the celestial sphere inside the circle. The BPZ construction is applied to give an inner product on such states whose associated bulk adjoints are shown to involve a shadow transform. Scattering amplitudes are then given by BPZ inner products between states living on the same circle but with opposite orientations. 2D boundary states are found to encode the same information as their 4D bulk counterparts, but organized in a radically different manner.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Targeted nonviral delivery of genome editors in vivo

Cell-type-specific in vivo delivery of genome editing molecules is the next breakthrough that will drive biological discovery and transform the field of cell and gene therapy. Here, we discuss recent advances in the delivery of CRISPR-Cas genome editors either as preassembled ribonucleoproteins or encoded in mRNA. Both strategies avoid pitfalls of viral vector-mediated delivery and offer advantages including transient editor lifetime and potentially streamlined manufacturing capability that are already proving valuable for clinical use. We review current applications and future opportunities of these emerging delivery approaches that could make genome editing more efficacious and accessible in the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Design Methodologies for Integrated Quantum Frequency Processors

We report frequency-encoded quantum information offers intriguing opportunities for quantum communications and networking, with the quantum frequency processor paradigm—based on electro-optic phase modulators and Fourier-transform pulse shapers—providing a path for scalable construction of quantum gates. Yet all experimental demonstrations to date have relied on discrete fiber-optic components that occupy significant physical space and impart appreciable loss. In this article, we introduce a model for the design of quantum frequency processors comprising microring resonator-based pulse shapers and integrated phase modulators. We estimate the performance of single and parallel frequency-bin Hadamard gates, finding high fidelity values that extend to frequency bins with relatively wide bandwidths. By incorporating multi-order filter designs as well, we explore the limits of tight frequency spacings, a regime extremely difficult to obtain in bulk optics. Overall, our model is general, simple to use, and extendable to other material platforms, providing a much-needed design tool for future frequency processors in integrated photonics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Omics-Lethal Human Viruses, Ebola Experiment EHUVEC001

The purpose of this experiment was to evaluate the human host response to Zaire Ebola wild-type virus and mutant virus infection in VP30 expression background. Samples were obtained from human umbilical cord endothelial cells (HUVEC) infected with wild-type Zaire Ebola virus in the ΔVP30 background (deltaVP30-WT) and mutant lacking the mucin domain (deltaVP30-deltamucin) encoding a glycoprotein lacking the mucin domain for mRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific Ebola virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Inozemtsev system as Seiberg-Witten integrable system

In this work we establish that the Inozemtsev system is the Seiberg-Witten integrable system encoding the Coulomb branch physics of 4d \( \mathcal{N} \) = 2 USp(2 N ) gauge theory with four fundamental and (for N ≥ 2) one antisymmetric tensor hypermultiplets. We describe the transformation from the spectral curves and canonical one-forms of the Inozemtsev system in the N = 1 and N = 2 cases to the Seiberg-Witten curves and differentials explicitly, along with the explicit matching of the modulus of the elliptic curve of spectral parameters to the gauge coupling of the field theory, and of the couplings of the Inozemtsev system to the field theory mass parameters. This result is a particular instance of a more general correspondence between crystallographic elliptic Calogero-Moser systems with Seiberg-Witten integrable systems, which will be explored in future work.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Alignment switching in 3D-printed smectic liquid crystal elastomers

Extrusion-based additive manufacturing has emerged as a powerful platform for designing shape-morphing materials through controlled orientation. However, existing approaches primarily rely on a single mode of flow-induced alignment, limiting orientation programmability. Herein, we present a direct-ink-writing approach for smectic liquid crystal elastics that exploits two distinct alignment modes within a single ink. The smectic ink exhibits shear- and temperature-dependent orientation switching, enabling molecular alignment either perpendicular or parallel to the print direction. Combined rheological, X-ray, and molecular dynamics analyses reveal that this alignment inversion arises from the preservation or collapse of smectic layers under flow. This reversible switching encodes both contractile and elongational actuation within individual filaments, greatly expanding the design freedom of printed liquid crystal elastomers. We demonstrate 2D and 3D structures with diverse programmed shape transformations, highlighting the potential of this platform for adaptive soft actuators and architected functional materials.

Lee, Jin Hyeong [Pusan National University, Busan,↗
DOE OSTI2021

Omics-Lethal Human Viruses, Ebola Experiment EHUH001

The purpose of this experiment was to evaluate the human host response to Zaire Ebola wild-type virus and mutant virus infection. Samples were obtained from human hepatoma carcinoma cells (HUH-7) infected with Zaire Ebola ΔVP30-WT background, in addition to mutant viruses Ebola-ΔsGP (eliminating expression of soluble glycoprotein ssGP) and Ebola-Δmucin (encoding a glycoprotein lacking the mucin domain) for mRNA and miRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific Ebola virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics Lethal Human Viruses, Ebola Experiment EU937001

The purpose of this experiment was to evaluate the human host response to Zaire Ebola wild-type virus and mutant virus infection. Samples were obtained from human histiocytic lymphoma cells (U937), expressing the Ebola VP30 protein, infected with wild-type Zaire Ebola (in ΔVP30 background) and Δmucin mutant virus encoding a glycoprotein lacking the mucin domain for mRNA and miRNA transcriptome expression analysis. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics dataset downloads have a direct relationship to a primary sample submission corresponding to a specific Ebola virus infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

When does global attention help: a unified empirical study on atomistic graph learning

Graph neural networks (GNNs) are widely used as surrogates for costly experiments and first-principles simulations to study the behavior of compounds at atomistic scale, and their architectural complexity is constantly increasing to enable the modeling of complex physics. While most recent GNNs combine more traditional message passing neural networks (MPNNs) layers to model short-range interactions with more advanced graph transformers (GTs) with global attention mechanisms to model long-range interactions, it is still unclear when global attention mechanisms provide real benefits over well-tuned MPNN layers due to inconsistent implementations, features, or hyperparameter tuning. We introduce the first unified, reproducible benchmarking framework–built on HydraGNN–that enables seamless switching among four controlled model classes: MPNN, MPNN with chemistry/topology encoders, GPS-style hybrids of MPNN with global attention, and fully fused localglobal models with encoders. Using seven diverse open-source datasets for benchmarking across regression and classification tasks, we systematically isolate the contributions of message passing, global attention, and encoder-based feature augmentation. Our study shows that encoder-augmented MPNNs form a robust baseline, while fused localglobal models yield the clearest benefits for properties governed by long-range interaction effects. We further quantify the accuracycompute trade-offs of attention, reporting its overhead in memory. Together, these results establish the first controlled evaluation of global attention in atomistic graph learning and provide a reproducible testbed for future model development.

Equivariant graph neural networks↗
DOE OSTI2026

Quantifying Microstructure Variability in Laser Powder Bed Fusion 316 L Stainless Steel Microstructures with Spatial Statistics

Here, we have explored data-driven methods for material microstructure quantification that improve sensitivity to microstructural changes compared to traditional approaches. The methods integrate multiple microstructural properties, including grain morphology, crystallographic orientation, and material phase information. The simpler method employs maps of the Euclidean distance transformation metric to evaluate the morphology of grain boundary networks. The more intensive approach employs generalized spherical harmonic mapping for crystallographic orientations, per-pixel phase information, and a variational auto-encoder for dimensionality reduction and results in a multidimensional clustering of by microstructure similarity. Applied to an experimental dataset of additively manufactured steel, both methods detected slight variations in samples produced under nominally identical processing conditions. Both methods were able to distinguish between samples from multiple (nominally identical) builds, while the generalized spherical harmonics-based method could additionally cluster data samples rotated at two orientations on the build plate. The improved sensitivity of the methods, demonstrated through comparison with traditional microstructure characterization techniques, offers advantages for microstructure quantification and comparisons in advanced manufacturing applications.

SS316L↗
DOE OSTI2021

Mercury methylation by metabolically versatile and cosmopolitan marine bacteria

Microbes transform aqueous mercury (Hg) into methylmercury (MeHg), a potent neurotoxin that accumulates in terrestrial and marine food webs, with potential impacts on human health. This process requires the gene pair hgcAB, which encodes for proteins that actuate Hg methylation, and has been well described for anoxic environments. However, recent studies report potential MeHg formation in suboxic seawater, although the microorganisms involved remain poorly understood. In this study, we conducted large-scale multi-omic analyses to search for putative microbial Hg methylators along defined redox gradients in Saanich Inlet, British Columbia, a model natural ecosystem with previously measured Hg and MeHg concentration profiles. Analysis of gene expression profiles along the redoxcline identified several putative Hg methylating microbial groups, including Calditrichaeota, SAR324 and Marinimicrobia, with the last the most active based on hgc transcription levels. Marinimicrobia hgc genes were identified from multiple publicly available marine metagenomes, consistent with a potential key role in marine Hg methylation. Computational homology modelling predicts that Marinimicrobia HgcAB proteins contain the highly conserved amino acid sites and folding structures required for functional Hg methylation. Furthermore, a number of terminal oxidases from aerobic respiratory chains were associated with several putative novel Hg methylators. Our findings thus reveal potential novel marine Hg-methylating microorganisms with a greater oxygen tolerance and broader habitat range than previously recognized.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Predictive model for real-time energy disaggregation using long short-term memory

To provide affordable energy-saving solutions for the small and medium-sized manufacturers (SMMs), we propose a unified framework for generating predictive models that support real-time disaggregation of power consumption from combined inputs, enabling automatic machine state identification simultaneously for joint analysis of energy usage patterns. Further, the proposed framework transforms raw power consumption into a time series with look-back and bootstrap capabilities for historical pattern detection, while a learning architecture utilizes the stacked long short-term memory (LSTM) layers as encoders for embedding generation with sequential awareness. Experimental results demonstrate 93.65% minimum accuracy in ideal case of real-time energy usage and machine state prediction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Co-designing Spectral Transformation Oracles with Hybrid Oscillator-Qubit Quantum Processors: From Algorithms to Compilation

We co-design a family of quantum eigenvalue transformation oracles that can be efficiently implemented on hybrid discrete- or continuous-variable (qubit or qumode) hardware. To illustrate the oracle’s representation-theoretic power and near-term experimental accessibility, we encode a Gaussian imaginary time-evolution spectral filter. As a result, we define a continuous linear combination of unitaries block encoding. Due to the ancillary qumode’s infinite-dimensional nature, continuous-variable qumodes constitute a powerful compilation tool for encoding continuous spectral functions without discretization errors while minimizing resource requirements. We then focus on the ubiquitous task of preparing eigenstates in quantum spin models. For completeness, we provide an end-to-end compilation which expresses high-level oracles in terms of an experimentally realizable instruction set architecture in both 1D and 2D. Finally, we examine the leading-order effects of physical errors and highlight open research directions. Our algorithms scale linearly with the spatial extent of the target system and are applicable to both near-term and large-scale quantum processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Optimal Control for the Quantum Simulation of Nuclear Dynamics

We propose a method for enacting the unitary time propagation of two interacting neutrons at leading order of chiral effective-field theory by efficiently encoding the nuclear dynamics into a single multilevel quantum device. The emulated output of the quantum simulation shows that, by applying a single gate that draws on the underlying characteristics of the device, it is possible to observe multiple cycles of the nuclear dynamics before the onset of decoherence. Owing to the signal's longevity, we can then extract spectroscopic properties of the simulated nuclear system. This allows us to validate the encoding of the nuclear Hamiltonian and the robustness of the simulation in the presence of quantum-hardware noise by comparing the extracted spectroscopic information to exact calculations. This work paves the way for transformative calculations of the dynamical properties of nuclei on near-term quantum devices.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

TDCOSMO - IV. Hierarchical time-delay cosmography – joint inference of the Hubble constant and galaxy density profiles

The H0LiCOW collaboration inferred via strong gravitational lensing time delays a Hubble constant value of H0 = 73.3−1.8+1.7 km s−1 Mpc−1, describing deflector mass density profiles by either a power-law or stars (constant mass-to-light ratio) plus standard dark matter halos. The mass-sheet transform (MST) that leaves the lensing observables unchanged is considered the dominant source of residual uncertainty in H0. We quantify any potential effect of the MST with a flexible family of mass models, which directly encodes it, and they are hence maximally degenerate with H0. Our calculation is based on a new hierarchical Bayesian approach in which the MST is only constrained by stellar kinematics. The approach is validated on mock lenses, which are generated from hydrodynamic simulations. We first applied the inference to the TDCOSMO sample of seven lenses, six of which are from H0LiCOW, and measured H0 = 74.5−6.1+5.6 km s−1 Mpc−1. Secondly, in order to further constrain the deflector mass density profiles, we added imaging and spectroscopy for a set of 33 strong gravitational lenses from the Sloan Lens ACS (SLACS) sample. For nine of the 33 SLAC lenses, we used resolved kinematics to constrain the stellar anisotropy. From the joint hierarchical analysis of the TDCOSMO+SLACS sample, we measured H0 = 67.4−3.2+4.1 km s−1 Mpc−1. This measurement assumes that the TDCOSMO and SLACS galaxies are drawn from the same parent population. The blind H0LiCOW, TDCOSMO-only and TDCOSMO+SLACS analyses are in mutual statistical agreement. The TDCOSMO+SLACS analysis prefers marginally shallower mass profiles than H0LiCOW or TDCOSMO-only. Without relying on the form of the mass density profile used by H0LiCOW, we achieve a ∼5% measurement of H0. While our new hierarchical analysis does not statistically invalidate the mass profile assumptions by H0LiCOW – and thus the H0 measurement relying on them – it demonstrates the importance of understanding the mass density profile of elliptical galaxies. The uncertainties on H0 derived in this paper can be reduced by physical or observational priors on the form of the mass profile, or by additional data.Key words: gravitational lensing: strong / galaxies: general / galaxies: kinematics and dynamics / distance scale / cosmological parameters / cosmology: observations⋆ The full analysis is available at https://github.com/TDCOSMO/hierarchy_analysis_2020_public.

79 ASTRONOMY AND ASTROPHYSICS↗