Computational Analyses of a Low Inductance Z-Machine Explosive Closure Device
An overview of various computational methods used to analyze and verify functionality of the new Z-Machine explosive closure device.
Cuneo, Nicolas Francis↗
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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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Best Practices for Nuclear Experiment Data Preservation at Idaho National Laboratory: A Guide for Researchers and Reactor Operators
Preserving experimental data is essential for supporting advancements in nuclear science and ensuring the longevity of Idaho National Laboratory's contributions to reactor technology and safety. This report provides a comprehensive guide to best practices for experimental data management and preservation, focusing on standardized data formats, redundancy in storage, metadata documentation, and alignment with international standards. By following these recommendations, experimentalists and reactor operators can enhance the accessibility, reproducibility, and utility of critical datasets for regulatory review, validation computational methods, and future research.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Multimodal Ligand Non-Innocence for Reduction Catalysis (Final Technical Report)
The goal of this project was to develop multimodal ligand non-innocence in late transition metal complexes of aminophenolate ligands and to apply this ligand-centered reactivity to small-molecule reduction reactions relevant to energy-conversion chemistry. Specific aims were, 1) Prepare new coordination complexes of aminophenolate ligands and characterize them using a battery of structural, spectroscopic, and computational methods. 2) Benchmark the thermodynamics and kinetics of e - , H + , H • , and H - transfer reactivity to establish the baseline reactivity of new metal complexes containing aminophenolate ligands. 3) Apply new aminophenolate complexes to catalytic reduction reactions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Reconstruction of 6D Phase Space
A ‘Phase Space’ is a mathematical representation of all possible physical states of matter of a physical volume or system. Particle beams at Fermilab exist in a six-dimensional phase space: three position dimensions, and three momentum dimensions. To ‘reconstruct’ that space means to take measurement data from virtual detectors along those beams and map out where particles are and how they’re moving, using computational methods. In this experiment, we simulated a particle beam (Fig 1) and used the position distribution of each particle at each detector to map out the magnitude of the beam’s initial momentum.
Shirlee, Jermaine [DuPage Coll.]↗
Predictive Phenomics Initiative Project Dataset Catalog Collection
The Predictive Phenomics Science & Technology Initiative (PPI) at Pacific Northwest National Laboratory are tackling the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems. Research projects within this initiative are divided into three Thrust Areas (TAs): TA1) Enhancing Multi-Scale Phenomics Measurements, TA2) Identifying Molecular Patterns of Biological Function, and TA3) Computational Methods - Phenotypic Signatures. In efforts to enable discovery, reproducibility, and reuse of PPI-funded digital research data generated or used through the course of the proposed research-funded lifecycles, all corresponding digital data assets conducted under the Laboratory Directed Research and Development Program at PNNL are linked to this PPI dataset catalog collection.
59 BASIC BIOLOGICAL SCIENCES↗
Predictive Phenomics Initiative Project Dataset Catalog Collection
The Predictive Phenomics Science & Technology Initiative (PPI) at Pacific Northwest National Laboratory are tackling the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems. Research projects within this initiative are divided into three Thrust Areas (TAs): TA1) Enhancing Multi-Scale Phenomics Measurements, TA2) Identifying Molecular Patterns of Biological Function, and TA3) Computational Methods - Phenotypic Signatures. In efforts to enable discovery, reproducibility, and reuse of PPI-funded digital research data generated or used through the course of the proposed research-funded lifecycles, all corresponding digital data assets conducted under the Laboratory Directed Research and Development Program at PNNL are linked to this PPI dataset catalog collection.
59 BASIC BIOLOGICAL SCIENCES↗
Lighting application efficacy: A framework for holistically measuring lighting use in buildings
Lighting consumes significant energy in buildings, but current measurements of lighting efficiency are inadequate in capturing the spatial and temporal effectiveness of light. The most widely used lighting energy efficiency measure, luminous efficacy, quantifies the amount of light generated by individual light sources. While luminous efficacy provides manufacturers and designers with a useful metric for quantifying the energy efficiency of individual lighting devices, it does not fully address the use of lighting in architectural spaces. Instead, application efficacy, the relationship between the electrical power consumed by lighting hardware and the amount of light that contributes to the visual perception of building occupants, must be measured. Here, we propose a framework for calculating lighting application efficacy (LAE) based on the primary pathway of light in architectural settings: the generation and emission of light from a luminaire, the travel of the light throughout the space and into occupants’ eyes, and the process of visual perception. The LAE framework will include the development of computational methods for estimating the proportion of emitted light that is directed to task areas and areas corresponding to occupants’ visual fields using ray-tracing lighting design software. Future modeling and validation work will quantify energy efficiency of buildings.
Durmus, Dorukalp↗
Short- and Intermediate-Range Structure and Dynamics of Fe-Ni-C Liquid Under Compression
Properties of liquid Fe alloys under high-pressure conditions are crucial for understanding the composition, thermal state, and dynamics of Earth’s core. Experiments on such liquids, however, are often performed under pressures far below those of the outer core, necessitating long extrapolations of experimental results to core conditions. Such estimates can be complicated by light elements possibly forming pressure-dependent molecular clusters that can significantly affect the physical properties of liquids as core conditions are approached. First-principles molecular dynamics simulations were employed to compute the properties of an Fe-Ni-C liquid with a composition of Fe 3.7 Ni 0.37 C at 1673 K and pressures from 0 to 67 GPa to benchmark computational methods on pressure effects on the structure and properties of the liquid relative to low pressure experimental results. The short-range structure is manifested by the coordination number (CN) of Fe/Ni-Fe/Ni being around 12, indicative of a nearly close-packed structure in the pressure range, and the CN of C-Fe/Ni gradual increasing from 6.5 to 8.5, indicative of an approximately octahedral to cubic transition as pressure increases. The Fe/Ni-Fe/Ni bond distance, however, is found to be 10 times more compressible than the C-Fe/Ni distance. The intermediate-range structure of Fe/Ni-Fe/Ni and C-Fe/Ni subsystems, described by a partial configurationally decomposed distribution function, undergoes substantial changes, characterized by a significant increase of the number of polyhedra that share 3 atoms with each other. Such dense configurations are related to an increased bulk modulus, decreased diffusion coefficient, decreased activation volume for diffusion, and increased shear viscosity. Reproducing the experimental observations at low pressures provides important support for modeling the liquid under the conditions relevant to the outer core.
58 GEOSCIENCES↗
A Thermogravimetric Temperature-Programmed Thermal Redox Protocol for Rapid Screening of Metal Oxides for Solar Thermochemical Hydrogen Production
As combinatorial and computational methods accelerate the identification of potentially suitable thermochemically-active oxides for use in solar thermochemical hydrogen production (STCH), the onus shifts to quickly evaluating predicted performance. Traditionally, this has required an experimental setup capable of directly carrying out a two-stage thermochemical water-splitting process. But this can be a difficult endeavor, as most off-the-shelf equipment cannot adequately deal simultaneously with the high temperatures, varying oxygen partial pressures, and high H 2 O partial pressures required; achieving sufficient temporal sensitivity to accurately quantify the kinetics is also a major challenge. However, as proposed here, a less complicated experiment can be used as a first screening for thermochemical water splitting potential. Temperature-Programmed Thermal Redox (TPTR) using thermogravimetry evaluates the thermal reduction behavior of materials. This technique does not require water splitting or CO 2 -splitting analogs but can nonetheless predict water-splitting performance. Three figures of merit are obtained from the TPTR experiment: reduction onset temperature, extent of reduction, and extent of recovery upon reoxidation. These metrics can collectively be used to determine if a material is capable of thermochemical water-splitting, and, to good approximation, predict whether the thermodynamics are favorable for use under more challenging high-conversion conditions. This paper discusses the pros and cons of using TPTR and proposes a protocol for use within the STCH community.
08 HYDROGEN↗
Whole-Genome Sequencing and Bioinformatic Analysis of Environmental, Agricultural, and Human Campylobacter jejuni Isolates From East Tennessee
As a leading cause of bacterial-derived gastroenteritis worldwide, Campylobacter jejuni has a significant impact on human health in both the developed and developing worlds. Despite its prevalence as a human pathogen, the source of these infections remains poorly understood due to the mutation frequency of the organism and past limitations of whole genome analysis. Recent advances in both whole genome sequencing and computational methods have allowed for the high-resolution analysis of intraspecies diversity, leading multiple groups to postulate that these approaches may be used to identify the sources of Campylobacter jejuni infection. To address this hypothesis, our group conducted a regionally and temporally restricted sampling of agricultural and environmental Campylobacter sources and compared isolated C. jejuni genomes to those that caused human infections in the same region during the same time period. Through a network analysis comparing genomes from various sources, we found that human C. jejuni isolates clustered with those isolated from cattle and chickens, indicating these as potential sources of human infection in the region.
59 BASIC BIOLOGICAL SCIENCES↗
Ontology-Enriched Specifications Enabling Findable, Accessible, Interoperable, and Reusable Marine Metagenomic Datasets in Cyberinfrastructure Systems
Marine microbial ecology requires the systematic comparison of biogeochemical and sequence data to analyze environmental influences on the distribution and variability of microbial communities. With ever-increasing quantities of metagenomic data, there is a growing need to make datasets Findable, Accessible, Interoperable, and Reusable (FAIR) across diverse ecosystems. FAIR data is essential to developing analytical frameworks that integrate microbiological, genomic, ecological, oceanographic, and computational methods. Although community standards defining the minimal metadata required to accompany sequence data exist, they haven’t been consistently used across projects, precluding interoperability. Moreover, these data are not machine-actionable or discoverable by cyberinfrastructure systems. By making ‘omic and physicochemical datasets FAIR to machine systems, we can enable sequence data discovery and reuse based on machine-readable descriptions of environments or physicochemical gradients. In this work, we developed a novel technical specification for dataset encapsulation for the FAIR reuse of marine metagenomic and physicochemical datasets within cyberinfrastructure systems. This includes using Frictionless Data Packages enriched with terminology from environmental and life-science ontologies to annotate measured variables, their units, and the measurement devices used. This approach was implemented in Planet Microbe, a cyberinfrastructure platform and marine metagenomic web-portal. Here, we discuss the data properties built into the specification to make global ocean datasets FAIR within the Planet Microbe portal. We additionally discuss the selection of, and contributions to marine-science ontologies used within the specification. Finally, we use the system to discover data by which to answer various biological questions about environments, physicochemical gradients, and microbial communities in meta-analyses. This work represents a future direction in marine metagenomic research by proposing a specification for FAIR dataset encapsulation that, if adopted within cyberinfrastructure systems, would automate the discovery, exchange, and re-use of data needed to answer broader reaching questions than originally intended.
59 BASIC BIOLOGICAL SCIENCES↗
Editorial: Structure and mechanism of microbial membrane active transporters
Membrane active transporters play essential roles in microbial physiology. They couple energy transduction to conformational changes that drive translocation of nutrients, substrates and ions, as well as molecular communication. The structure and function of microbial membrane active transporters are highly diverse. Typical examples include the primary active transporters in the ATP-binding cassette (ABC) superfamily (Thomas and Tampé, 2020; Davidson et al., 2008; Locher et al., 2002), the secondary active transporters in the Major Facilitator Superfamily (MFS) (Drew et al., 2021; Kaback and Guan, 2019), and the ligand-gated porins in the TonB-dependent transporter (TBDT) family (Klebba et al., 2021). As structural, proteogenomic, and computational methods advance, active transporters are increasingly recognized as dynamic molecular machines whose mechanisms can now be visualized and modeled with remarkable precision, building on decades of biochemical and biophysical discovery that established the foundations of this field. The transporter studies recruited in this Research Topic provide us with new insights into the field including structure-function of sugar transporters in yeast, structural prediction and classification of ABC complexes in Bacillus subtilis, Type VI Secretion System (T6SS) in Bacteroides fragilis, amino acids uptake in Escherichia coli and bacterial spore germination.
mechanism↗
Processes at lithium-hydride/deuteride surfaces upon low energy impact of H/D
Sputtering, reflection, and retention processes at amorphous and crystalline lithium hydride surfaces due to impact of low energy (1–100 eV) hydrogen and deuterium atoms over the range of 0 o −85 o angle of incidence at 300 K surface temperature were investigated by atomistic computational methods. Classical molecular dynamics simulations were performed with improved reactive bond-order force field (ReaxFF) potentials that include long-range polarization effects. In addition to probabilities of surface processes, the energy and angular spectra of ejected particles were obtained. Comparison of these results with those previously obtained on pristine lithium surfaces indicates the importance of saturation of the Li surface and near-surface region with hydrogen. We show that such saturation, which is typical in both laboratory and fusion device experiments with lithium coating of the plasma-facing surfaces, significantly changes the surface processes with hydrogen irradiation in the understudied low-energy region of impact energies.
74 ATOMIC AND MOLECULAR PHYSICS↗
The Architectural Dynamics of the Bacterial Flagellar Motor Switch
The rotary bacterial flagellar motor is remarkable in biochemistry for its highly synchronized operation and amplification during switching of rotation sense. The motor is part of the flagellar basal body, a complex multi-protein assembly. Sensory and energy transduction depends on a core of six proteins that are adapted in different species to adjust torque and produce diverse switches. Motor response to chemotactic and environmental stimuli is driven by interactions of the core with small signal proteins. The initial protein interactions are propagated across a multi-subunit cytoplasmic ring to switch torque. Torque reversal triggers structural transitions in the flagellar filament to change motile behavior. Subtle variations in the core components invert or block switch operation. The mechanics of the flagellar switch have been studied with multiple approaches, from protein dynamics to single molecule and cell biophysics. The architecture, driven by recent advances in electron cryo-microscopy, is available for several species. Computational methods have correlated structure with genetic and biochemical databases. The design principles underlying the basis of switch ultra-sensitivity and its dependence on motor torque remain elusive, but tantalizing clues have emerged. This review aims to consolidate recent knowledge into a unified platform that can inspire new research strategies.
59 BASIC BIOLOGICAL SCIENCES↗
Modeling Clustered DNA Damage by Ionizing Radiation Using Multinomial Damage Probabilities and Energy Imparted Spectra
Simple and complex clustered DNA damage represent the critical initial damage caused by radiation. In this paper, a multinomial probability model of clustered damage is developed with probabilities dependent on the energy imparted to DNA and surrounding water molecules. The model consists of four probabilities: (A) direct damage of sugar-phosphate moieties leading to SSB, (B) OH− radical formation with subsequent SSB and BD formation, (C) direct damage to DNA bases, and (D) energy imparted to histone proteins and other molecules in a volume not leading to SSB or BD. These probabilities are augmented by introducing probabilities for the relative location of SSB using a ≤10 bp criteria for a double-strand break (DSB) and for the possible success of a radical attack that leads to SSB or BD. Model predictions for electrons, 4He, and 12C ions are compared to the experimental data and show good agreement. Thus, the developed model allows an accurate and rapid computational method to predict simple and complex clustered DNA damage as a function of radiation quality and to explore the resulting challenges to DNA repair.
Biochemistry & Molecular Biology↗
Design of Monolithic Bi-Layer High-Z PAL-Si Hard X-ray CMOS Image Sensors for Quantum Efficiency Enhancement
This article experimentally investigates the inception of an innovative hard X-ray photon energy attenuation layer (PAL) to advance high-energy X-ray detection (20–50 keV). A bi-layer design with a thin film high-Z PAL on the top and Si image sensor on the bottom has previously demon-strated quantum yield enhancement via computational methods by the principle of photon energy down conversion (PEDC), where high-energy X-ray photon energies are attenuated via inelastic scattering down to ≤10 keV, which is suitable for efficient photoelectric absorption by Si. Quantum yield enhancement has been experimentally confirmed via a preliminary demonstration using PAL-integrated Si-based CMOS image sensors (Si CIS). Furthermore, substituting the high-Z PAL with a lower-Z material—Sn—and alternatively coupling it with a conventional scintillator ma-terial—Lutetium-yttrium oxyorthosilicate (LYSO)—have been compared to demonstrate the most prominent efficacy of monolithic integration of high-Z PAL on Si CIS to detect hard X-rays, paving the way for next-generation high-energy X-ray detection methods.
47 OTHER INSTRUMENTATION↗
Ground State Properties of the Wide Band Gap Semiconductor Beryllium Sulfide (BeS)
We report the results from self-consistent calculations of electronic, transport, and bulk properties of beryllium sulfide (BeS) in the zinc-blende phase, and employed an ab-initio local density approximation (LDA) potential and the linear combination of atomic orbitals (LCAO). We obtained the ground state properties of zb-BeS with the Bagayoko, Zhao, and Williams (BZW) computational method, as enhanced by Ekuma and Franklin (BZW-EF). Our findings include the electronic energy bands, the total (DOS) and partial (pDOS) densities of states, electron and hole effective masses, the equilibrium lattice constant, and the bulk modulus. The calculated band structure clearly shows that zb-BeS has an indirect energy band gap of 5.436 eV, from Γ to a point between Γ and X, for an experimental lattice constant of 4.863 Å. This is in excellent agreement with the experiment, unlike the findings of more than 15 previous density functional theory (DFT) calculations that did not perform the generalized minimization of the energy functional, required by the second DFT theorem, which is inherent to the implementation of our BZW-EF method.
36 MATERIALS SCIENCE↗
Nerpa: A Tool for Discovering Biosynthetic Gene Clusters of Bacterial Nonribosomal Peptides
Microbial natural products are a major source of bioactive compounds for drug discovery. Among these molecules, nonribosomal peptides (NRPs) represent a diverse class of natural products that include antibiotics, immunosuppressants, and anticancer agents. Recent breakthroughs in natural product discovery have revealed the chemical structure of several thousand NRPs. However, biosynthetic gene clusters (BGCs) encoding them are known only for a few hundred compounds. Here, we developed Nerpa, a computational method for the high-throughput discovery of novel BGCs responsible for producing known NRPs. After searching 13,399 representative bacterial genomes from the RefSeq repository against 8368 known NRPs, Nerpa linked 117 BGCs to their products. We further experimentally validated the predicted BGC of ngercheumicin from Photobacterium galatheae via mass spectrometry. Nerpa supports searching new genomes against thousands of known NRP structures, and novel molecular structures against tens of thousands of bacterial genomes. The availability of these tools can enhance our understanding of NRP synthesis and the function of their biosynthetic enzymes.
59 BASIC BIOLOGICAL SCIENCES↗