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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Exoproteome and Surfaceome of Toxigenic Corynebacterium diphtheriae 1737 and Its Response to Iron Restriction and Growth on Human Hemoglobin

Toxin-producing Corynebacterium diphtheriae strains are the etiological agents of the severe upper respiratory disease, diphtheria. A global phylogenetic analysis revealed that biotype gravis is particularly lethal as it produces diphtheria toxin and a range of other virulence factors, particularly when it encounters low levels of iron at sites of infection. Here, to gain insight into how it colonizes its host, we have identified iron-dependent changes in the exoproteome and surfaceome of C. diphtheriae strain 1737 using a combination of whole-cell fractionation, intact cell surface proteolysis, and quantitative proteomics. In total, we identified 1414 of the predicted 2265 proteins (62%) encoded by its reference genome. For each protein, we quantified its degree of secretion and surface exposure, revealing that exoproteases and hydrolases predominate in the exoproteome, while the surfaceome is enriched with adhesins, particularly DIP2093. Our analysis provides insight into how components in the heme-acquisition system are positioned, showing pronounced surface exposure of the strain-specific ChtA/ChtC paralogues and high secretion of the species-conserved heme-binding HtaA protein, suggesting it functions as a hemophore. Profiling the response of the exoproteome and surfaceome after microbial exposure to human hemoglobin and iron limitation reveals potential virulence factors that may be expressed at sites of infection. Data are available via ProteomeXchange with identifier PXD051674.

cell envelope↗
DOE OSTI2024

Long-Term Statistical Process Monitoring of an Ultrafiltration Water Treatment Process

As water treatment technology has improved, the amount of available process data has substantially increased, making real-time, data-driven fault detection a reality. One shortcoming of the fault detection literature is that methods are usually evaluated by comparing their performance on hand-picked, short-term case studies, which yields no insight into long-term performance. In this work, we first evaluate multiple statistical and machine learning approaches for detrending process data. Then, we evaluate the performance of a PCA-based fault detection approach, applied to the detrended data, to monitor influent water quality, filtrate quality, and membrane fouling of an ultrafiltration membrane system for indirect potable reuse. Based on two short case studies, the adaptive lasso detrending method is selected, and the performance of the multivariate approach is evaluated over more than a year. The method is tested for different sets of three critical tuning parameters, and we find that for long-term, autonomous monitoring to be successful, these parameters should be carefully evaluated. However, in comparison with industry standards of simpler, univariate monitoring or daily pressure decay tests, multivariate monitoring produces substantial benefits in long-term testing.

ammonia↗
DOE OSTI2024

Entire expressed peripheral blood transcriptome in pediatric severe malarial anemia

Abstract This study on severe malarial anemia (SMA: Hb < 6.0 g/dL), a leading global cause of childhood morbidity and mortality, compares the entire expressed whole blood host transcriptome between Kenyan children (3-48 mos.) with non-SMA (Hb ≥ 6.0 g/dL, n = 39) and SMA ( n = 18). Differential expression analyses reveal 1403 up-regulated and 279 down-regulated transcripts in SMA, signifying impairments in host inflammasome activation, cell death, and innate immune and cellular stress responses. Immune cell profiling shows decreased memory responses, antigen presentation, and immediate pathogen clearance, suggesting an immature/improperly regulated immune response in SMA. Module repertoire analysis of blood-specific gene signatures identifies up-regulation of erythroid genes, enhanced neutrophil activation, and impaired inflammatory responses in SMA. Enrichment analyses converge on disruptions in cellular homeostasis and regulatory pathways for the ubiquitin-proteasome system, autophagy, and heme metabolism. Pathway analyses highlight activation in response to hypoxic conditions [Hypoxia Inducible Factor (HIF)−1 target and Reactive Oxygen Species (ROS) signaling] as a central theme in SMA. These signaling pathways are also top-ranking in protein abundance measures and a Ugandan SMA cohort with available transcriptomic data. Targeted RNA-Seq validation shows strong concordance with our entire expressed transcriptome data. These findings identify key molecular themes in SMA pathogenesis, offering potential targets for new malaria therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Systematic determination of a material’s magnetic ground state from first principles

Abstract We present a self-consistent method based on first-principles calculations to determine the magnetic ground state of materials, regardless of their dimensionality. Our methodology is founded on satisfying the stability conditions derived from the linear spin wave theory (LSWT) by optimizing the magnetic structure iteratively. We demonstrate the effectiveness of our method by successfully predicting the experimental magnetic structures of NiO, FePS 3 , FeP, MnF 2 , FeCl 2 , and CuO. In each case, we compared our results with available experimental data and existing theoretical calculations reported in the literature. Finally, we discuss the validity of the method and the possible extensions.

Chemistry↗
DOE OSTI2024

Real space iterative reconstruction for vector tomography (RESIRE-V)

Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Microscopic calculations with noniterative finite amplitude methods and the application to neutron radiative captures and inelastic scatterings

We derive the fully self-consistent quasiparticle random-phase approximation (QRPA) equations with noniterative finite amplitude methods and calculate the transition strengths of giant resonances. Then, we apply the QRPA results to both neutron radiative capture calculations based on the statistical Hauser-Feshbach theory and inelastic scattering calculations based on distorted-wave Born approximation (DWBA). We compare the calculated results with available experimental data and demonstrate how our approach can reproduce giant resonances and various nuclear reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Alkali hydroxide (LiOH, NaOH, KOH) in water: Structural and vibrational properties, including neutron scattering results

Structural and vibrational properties of aqueous solutions of alkali hydroxides (LiOH, NaOH, and KOH) are computed using quantum molecular dynamics simulations for solute concentrations ranging between 1 and 10M. Element-resolved partial radial distribution functions, neutron and x-ray structure factors, and angular distribution functions are computed for the three hydroxide solutions as a function of concentration. The vibrational spectra and frequency-dependent conductivity are computed from the Fourier transforms of velocity autocorrelation and current autocorrelation functions. Our results for the structure are validated with the available neutron data for 17M concentration of NaOH in water [Semrouni et al., Phys. Chem. Chem. Phys. 21, 6828 (2019)]. We found that the larger ionic radius [rLi+

Chemistry↗
DOE OSTI2024

Electronic properties of corundum-like Ir 2 O 3 and Ir 2 O 3 -Ga 2 O 3 alloys

In the hexagonal, corundum-like structure, α-Ga 2 O 3 has a bandgap of ~5.1 eV, which, combined with its relatively small electron effective mass, high Baliga's figure of merit, and high breakdown field, makes it a promising candidate for power electronics. Ga 2 O 3 is easy to dope n-type, but impossible to dope p-type, impeding the realization of some electronic device designs. Developing a lattice-matched p-type material that forms a high-quality heterojunction with n-type Ga 2 O 3 would open new opportunities in electronics and perhaps optoelectronic devices. In this work, we studied Ir 2 O 3 as a candidate for that purpose. Using hybrid density functional theory calculations we predict the electronic band structure of α-Ir 2 O 3 and compare that to α-Ga 2 O 3 , and study the stability and electronic properties of α-(Ir x Ga 1–x ) 2 O 3 alloys. We discuss the band offset between the two materials and compare it with recently available experimental data. We find that the Ir d bands that compose the top of the valence band in α-Ir 2 O 3 are much higher in energy than O p bands in α-Ga 2 O 3 , possibly enabling effective p-type doping. Finally, our results provide an insight into using the Ir 2 O 3 or Ir 2 O 3 -Ga 2 O 3 alloys as p-type material lattice-matched to α-Ga 2 O 3 for the realization of p–n heterojunctions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗
DOE OSTI2024

Verification and Demonstration of One-Dimensional Freezing Model in SAM for Salt-Cooled Reactor Analysis Applications

This work presented the development and implementation of the one-dimensional freezing model in system analysis code, SAM, as well as code verification, and code demonstration during a postulated overcooling transient, for fluoride salt-cooled high-temperature reactor (FHR) system and safety analysis applications. The paper at first summarized the freezing model, finite element numerical method, and special numerical treatment for handling phase appearance/disappearance. Analytical solutions were derived for two cases (with and without solid walls) for code verifications purpose. As expected, numerical results predicted by the SAM code agreed very well with the analytical solution. A code demonstration was then performed on a postulated protected overcooling event transient of a generic reference PB-FHR design. The code was found to successfully predict salt freezing during such a postulated event. However, due to lack of salt freezing testing data, code validation has not been performed in this work, which will be pursued in later studies when such data becomes available.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

RELAP5-3D Capabilities for High-Temperature Gas-Cooled Reactor Analysis

RELAP5-3D is the premier systems thermal-hydraulic code in the world. The code has been used significantly for high-temperature gas-cooled reactor (HTGR) analyses over the last 10 years, but there has not been a comprehensive summary of RELAP5-3D capabilities and methods for HTGR modeling. In this paper, we provide a guide for how novice users can build models for prismatic HTGRs. This guide includes best practices for developing heat structures and setting up radiation and conduction heat transfer. We also provide a summary of relevant validation studies. These studies are divided into three categories: separate effects tests, integral effects tests, and nuclear reactor studies. We present a comprehensive review of RELAP5-3D HTGR applications for reactor modeling over the last 10 years. These applications include work for the Modular High-Temperature Gas-Cooled Reactor benchmark, design activities for a prismatic HTGR as part of the U.S. Department of Energy’s Advanced Demonstration and Test Reactor Options Study, and studies performed to design gas-cooled microreactors. Following the comprehensive literature review, we present a gap analysis highlighting capabilities of RELAP5-3D that are available and missing for a complete analysis of HTGR thermal hydraulics. We also discuss the limitations of existing code capabilities and potential improvements that could improve analyses. Current research efforts have yet to fully validate RELAP5-3D for a prismatic HTGR analysis; however, some of this is attributable to confounding factors in the available experimental data as opposed to code capabilities. In conclusion, this paper presents the most comprehensive review to date on RELAP5-3D capabilities, limitations, and applications for HTGR analysis.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

High-Fidelity CFD Assessments of Flow Resistance in a 61-Pin Wire-Wrapped Assembly with Partially Blocked Channels

The examination of thermal-hydraulic behaviors in wire-wrapped rod bundles continues to be an active area of research. The sodium fast reactor, a prominent candidate in next-generation nuclear designs, utilizes a hexagonal configuration of wire-wrapped fuel pins. Here, the potential for channel blockage within this compact arrangement poses a significant safety challenge, spurring a number of recent experimental and computational investigations to evaluate its impact on flow and heat transfer. The present work aims to benchmark the high-fidelity NekRS computational fluid dynamics (CFD) solver in predicting the pressure drops associated with substantial blockages, using available experimental data as a reference. A 61-pin wire-wrapped fuel assembly with two flow blockage configurations has been simulated and investigated at a range of low to moderate Reynolds numbers (487 ≤ Re ≤ 14 600). The NekRS solver demonstrates an exponential reduction of spatial discretization error with increasing polynomial order. The high level of agreement between the numerical results and measured data confirms the accuracy and consistency of the present numerical approach. This benchmark study establishes the capability of NekRS to perform reliable hydrodynamic simulations for sodium fast reactor applications and supports its use in design, licensing, and safety analyses.

CFD Benchmarking↗
DOE OSTI2025

Effects of non-equilibrium ionization and excitation on radiation absorption in plasma plumes induced by ablation of metal targets with nanosecond laser pulses

Ionization and radiation absorption in nanosecond laser-induced plasma plumes are routinely modeled using the Saha–Boltzmann equilibrium ionization model (EQM). However, the equilibrium assumption can be inaccurate during the laser pulse when non-equilibrium effects significantly impact radiation absorption. In the present work, the EQM and non-equilibrium collisional-radiative model (CRM) are compared to reveal the effect of plasma non-equilibrium on radiation absorption in non-homogeneous plumes and degree of plasma shielding. Simulations of plume expansion induced by irradiation of a copper target in 1 atm argon background gas with a 10 ns Gaussian pulse at a fluence from 8 Jcm −2 to 14 Jcm −2 are performed with a hybrid computational model that couples a lumped particle direct simulation Monte Carlo method with either CRM or EQM. The simulations show that the EQM strongly underestimates the effects of ionization and radiation absorption compared to CRM and, contrary to the CRM, predict strong ionization of the background gas. The differences between the models are explained by the qualitatively different coupling between plume expansion and dynamics of ionization and exitation processes in the CRM and EQM under conditions when the characteristic times for most radiation- and electron-induced processes are longer than the pulse duration. The CRM-based predictions are also found to agree much better with available experimental data. In conclusion, these results indicate that the model of Saha–Boltzmann equilibrium cannot be used for reliable prediction of the degree of plasma shielding in plumes induced by nanosecond laser pulses or for processing results of spectroscopic measurements at early stages of expansion of such plumes.

Physics - Plasma physics↗
DOE OSTI2024

Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data

Abstract Recent advances in machine learning, specifically transformer architecture, have led to significant advancements in commercial domains. These powerful models have demonstrated superior capability to learn complex relationships and often generalize better to new data and problems. This paper presents a novel transformer-powered approach for enhancing prediction accuracy in multi-modal output scenarios, where sparse experimental data is supplemented with simulation data. The proposed approach integrates transformer-based architecture with a novel graph-based hyper-parameter optimization technique. The resulting system not only effectively reduces simulation bias, but also achieves superior prediction accuracy compared to the prior method. We demonstrate the efficacy of our approach on inertial confinement fusion experiments, where only 10 shots of real-world data are available, as well as synthetic versions of these experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

miss-SNF: a multimodal patient similarity network integration approach to handle completely missing data sources

Abstract Motivation Precision medicine leverages patient-specific multimodal data to improve prevention, diagnosis, prognosis, and treatment of diseases. Advancing precision medicine requires the non-trivial integration of complex, heterogeneous, and potentially high-dimensional data sources, such as multi-omics and clinical data. In the literature, several approaches have been proposed to manage missing data, but are usually limited to the recovery of subsets of features for a subset of patients. A largely overlooked problem is the integration of multiple sources of data when one or more of them are completely missing for a subset of patients, a relatively common condition in clinical practice. Results We propose miss-Similarity Network Fusion (miss-SNF), a novel general-purpose data integration approach designed to manage completely missing data in the context of patient similarity networks. miss-SNF integrates incomplete unimodal patient similarity networks by leveraging a non-linear message-passing strategy borrowed from the SNF algorithm. miss-SNF is able to recover missing patient similarities and is “task agnostic”, in the sense that can integrate partial data for both unsupervised and supervised prediction tasks. Experimental analyses on nine cancer datasets from The Cancer Genome Atlas (TCGA) demonstrate that miss-SNF achieves state-of-the-art results in recovering similarities and in identifying patients subgroups enriched in clinically relevant variables and having differential survival. Moreover, amputation experiments show that miss-SNF supervised prediction of cancer clinical outcomes and Alzheimer’s disease diagnosis with completely missing data achieves results comparable to those obtained when all the data are available. Availability and implementation miss-SNF code, implemented in R, is available at https://github.com/AnacletoLAB/missSNF.

Biochemistry & Molecular Biology↗
DOE OSTI2025

DNABERT-S: pioneering species differentiation with species-aware DNA embeddings

SUMMARY: We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space. Differentiating species from genomic sequences (i.e. DNA and RNA) is vital yet challenging, since many real-world species remain uncharacterized, lacking known genomes for reference. Embedding-based methods are therefore used to differentiate species in an unsupervised manner. DNABERT-S builds upon a pre-trained genome foundation model named DNABERT-2. To encourage effective embeddings to error-prone long-read DNA sequences, we introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes the hidden representations of DNA sequences at randomly selected layers and trains the model to recognize and differentiate these mixed proportions at the output layer. We further enhance it with the proposed Curriculum Contrastive Learning (C2LR) strategy. Empirical results on 28 diverse datasets show DNABERT-S's effectiveness, especially in realistic label-scarce scenarios. For example, it identifies twice more species from a mixture of unlabeled genomic sequences, doubles the Adjusted Rand Index (ARI) in species clustering, and outperforms the top baseline's performance in 10-shot species classification with just a 2-shot training. AVAILABILITY AND IMPLEMENTATION: Model, codes, and data are publically available at https://github.com/MAGICS-LAB/DNABERT_S.

Zhou, Zhihan↗
DOE OSTI2024

Strong nebular emissions associated with Mg ii absorptions detected in the SDSS spectra of background quasars

ABSTRACT We present long-slit spectroscopic observations of 40 Galaxy On Top of Quasars (GOTOQs) at ${0.37 \leqslant z \leqslant 1.01}$ using the South African Large Telescope. Using this and available photometric data, we measure the impact parameters of the foreground galaxies to be in the range of 3–16 kpc with a median value of 8.6 kpc. This is the largest sample of galaxies producing Mg ii absorption at such low impact parameters. These quasar–galaxy pairs are ideal for probing the disc–halo interface. At such impact parameters, we do not find any anticorrelation between rest equivalent width (REW) of Ca ii, Mn ii, Fe ii, Mg ii, and Mg i absorption and impact parameter. These sight lines are typically redder than those of strong Mg ii absorbers, with the colour excess, E(B − V) for our sample ranging from −0.191 to 0.422, with a median value of 0.058. In the E(B − V) versus W3935 plane, GOTOQs occupy the same region as Ca ii absorbers. For a given E(B − V), we find larger W3935 than what has been found in the Milky Way, probably due to a smaller dust-to-gas ratio in GOTOQs. Galaxy parameters could be measured for twelve cases, and their properties seem to follow the trends found for strong Mg ii absorbers. Measuring the host galaxy properties for the full sample using HST photometry or AO-assisted ground-based imaging is important to gain insights into the relationship between the stellar mass of galaxies and the metal line REW distributions at low impact parameters.

Astronomy & Astrophysics↗
DOE OSTI2026

Glauber-theory analysis of nuclear reactions on a 12 C target with variational Monte Carlo wave functions

The application of Glauber theory has been playing an increasingly important role with the study of unstable or exotic nuclei. Its adaptation to medium and high-energy nucleus-nucleus collisions is severely limited because one has to evaluate the matrix elements of multiple-scattering operators. The extraction of physical observables has been done using ‘approximate’ Glauber theory whose validity is hard to evaluate. Here, we perform a full calculation of the matrix elements using Monte Carlo integration and analyze the elastic differential cross sections and the total reaction cross sections for p+¹²C, ⁴,⁶He+¹²C, and ¹²C+¹²C collisions. We use the variational Monte Carlo wave functions for ⁴,⁶He and ¹²C obtained by using realistic two- and three-nucleon potentials. We demonstrate the performance of the Glauber-theory calculations by comparing with available experimental data. We further discuss the accuracy of the conventional approximate methods in the light of the cumulant expansion for Glauber’s phase-shift function.

Horiuchi, W. [Osaka Metropolitan University (Japan↗