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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

pyEGAF: Modernization of the EGAF database

One of the most comprehensive resources for thermal neutron-capture data is the Evaluated Gamma-ray Activation File (EGAF), containing data from prompt gamma activation analysis measurements carried out at the Budapest Research Reactor for 245 isotopes. Although these valuable datasets have been freely available for many years, the outdated and cryptic adopted format makes it difficult to utilize the data and it is not generally suitable for modern computational technologies. Furthermore, to help overcome these challenges, we have converted the datasets into an open standard JSON format. Additionally, we have developed a Python implementation of an open-source software package, pyEGAF, designed to interact with the JSON data structures for general purpose access, manipulation, and rapid assessment of the capture-gamma data in EGAF.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Structure of the peptidoglycan polymerase RodA resolved by evolutionary coupling analysis

The shape, elongation, division and sporulation (SEDS) proteins are a large family of ubiquitous and essential transmembrane enzymes with critical roles in bacterial cell wall biology. The exact function of SEDS proteins was for a long time poorly understood, but recent work has revealed that the prototypical SEDS family member RodA is a peptidoglycan polymerase—a role previously attributed exclusively to members of the penicillin-binding protein family4. This discovery has made RodA and other SEDS proteins promising targets for the development of next-generation antibiotics. However, little is known regarding the molecular basis of SEDS activity, and no structural data are available for RodA or any homologue thereof. Here we report the crystal structure of Thermus thermophilus RodA at a resolution of 2.9 Å, determined using evolutionary covariance-based fold prediction to enable molecular replacement. The structure reveals a ten-pass transmembrane fold with large extracellular loops, one of which is partially disordered. Here, the protein contains a highly conserved cavity in the transmembrane domain, reminiscent of ligand-binding sites in transmembrane receptors. Mutagenesis experiments in Bacillus subtilis and Escherichia coli show that perturbation of this cavity abolishes RodA function both in vitro and in vivo, indicating that this cavity is catalytically essential. These results provide a framework for understanding bacterial cell wall synthesis and SEDS protein function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage

Data acquisition systems are a key component for successful data taking in any experiment. The DAQ is a complex distributed computing system and coordinates all operations, from the data selection stage of interesting events to storage elements. For the High Luminosity upgrade of the Large Hadron Collider, the experiments at CERN need to meet challenging requirements to record data with a much higher occupancy in the detectors. The DAQ system will receive and deliver data with a significantly increased trigger rate, one million events per second, and capacity, terabytes of data per second. An effective way to meet these requirements is to decouple real-time data acquisition from event selection. Data fragments can be temporarily stored in a large distributed key-value store. Fragments belonging to the same event can be then queried on demand, by the data selection processes. Implementing such a model relies on a proper combination of emerging technologies, such as persistent memory, NVMe SSDs, scalable networking, and data structures, as well as high performance, scalable software. In this paper, we present DAQDB (Data Acquisition Database) — an open source implementation of this design that was presented earlier, with an extensive evaluation of this approach, from the single node to the distributed performance. Furthermore, we complement our study with a description of the challenges faced and the lessons learned while integrating DAQDB with the existing software framework of the ATLAS experiment.

Abed Abud, Adam↗
DOE OSTI2018

ARCHIE: Data Analysis Acceleration with Array Caching in Hierarchical Storage

© 2018 IEEE. Scientific data analysis typically involves reading massive amounts of data that was generated by simulations, experiments, and observations. Performance of reading such large volumes of data from disk-based file systems is often poor because of the slow and mechanical components in the disks. Recent supercomputing systems are adding non-volatile storage layers in a hierarchy to handle the performance gap between fast main memory and slow disk-based storage. Software libraries for managing this hierarchy not only need efficient reading of data but also reduce user-involvement for cross-layer data movement. Furthermore, these libraries need to support array data access patterns into hierarchical storage management as scientific data is often organized in array-based data structures. Existing software typically manage individual storage layers requiring significant manual process in moving data among them. In this paper, we introduce a new array caching in hierarchical storage (ARCHIE) to accelerate array data analysis in a seamless fashion. ARCHIE evaluates array access patterns and prefetches data with array semantics between storage layers. Our evaluation shows that ARCHIE outperforms state-of-the-art file systems, i.e., Lustre and DataWarp, on a production supercomputing system by up to 5.8× in accessing data by scientific analysis applications.

Dong, Bin↗
DOE OSTI2019

BCM polytype structures from DFT - Data and Resources

This dataset contains structure files and results of density functional theory (DFT) calculations for the 12R (ground state) and 10H (metastable at ambient temperature) polytypes of BaCe0.25Mn0.75O3 (BCM). Starting from the experimentally determined average crystal structures, the structures were generated by sampling of the magnetic (12R and 10H) and atomic (10H) configurations based on DFT energies.

08 HYDROGEN↗
DOE OSTI2020

Physically Based Modeling of PEMFC Cathode Catalyst Layers: Effective Microstructure and Ionomer Structure–Property Relationship Impacts

Abstract This work presents a pseudo-two-dimensional proton exchange membrane fuel cell (PEMFC) model incorporating Nafion ionomer structure–property relationships in the cathode catalyst layer (CL) to capture and explain losses at low Pt loading. Structural data from neutron reflectometry and thin film Nafion conductivity measurements predict variations in the oxygen diffusion coefficient and ionic conductivity with changing CL ionomer thickness and Pt loading. By including these structure–property relationships, predicted polarization curves agree closely with previously published experimental data from cells with Pt loadings between 0.025 and 0.2 mg/cm2. Results demonstrate that structure–property relationships based on physically measurable ionomer and CL properties provide a feasible interpretation of PEMFC CL phenomena for a range of Pt loadings and help explain previously unaccounted-for losses at low Pt. Results also show that simulations must account for surface species coverage variations in order to properly capture the kinetic losses. Finally, results suggest that an increase in ionomer thickness surrounding the C/Pt surfaces may lead to improved cell performance due to improved ionic conductivity.

Electrochemistry↗
DOE OSTI2018

Common helical V1V2 conformations of HIV-1 Envelope expose the α4β7 binding site on intact virions

The α4β7 integrin is a non-essential HIV-1 adhesion receptor, bound by the gp120 V1V2 domain, facilitating rapid viral dissemination into gut-associated lymphoid tissues. Antibodies blocking this interaction early in infection can improve disease outcome, and V1V2-targeted antibodies were correlated with moderate efficacy reported from the RV144 HIV-1 vaccine trial. Monoclonal α4β7-blocking antibodies recognise two slightly different helical V2 conformations, and current structural data suggests their binding sites are occluded in prefusion envelope trimers. Here, we report cocrystal structures of two α4β7-blocking antibodies from an infected donor complexed with scaffolded V1V2 or V2 peptides. Both antibodies recognised the same helix-coil V2 conformation as RV144 antibody CH58, identifying a frequently sampled alternative conformation of full-length V1V2. In the context of Envelope, this α-helical form of V1V2 displays highly exposed α4β7-binding sites, potentially providing a functional role for non-native Envelope on virion or infected cell surfaces in HIV-1 dissemination, pathogenesis, and vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

PymePix : a python library for SPIDR readout of Timepix3

PymePix is a new Python 3 library that provides control and acquisition for the Timepix3-SPIDR hardware. The rich set of data-structures and intuitive routines reduces time and coding effort to quickly configure, acquire, and visualize data from Timepix3. The highly extensible high-performance data-pipeline allows for alteration of the Timepix3 datastream into a form that is convinient for the user. This library is intended to be easily inserted into a standard scientific software stack as well as to allow for more direct interaction of Timepix3 with interactive flavors of Python. Included with the library are two example programs using PymePix: pymepix-acq is a command line control and acquisition program that can capture UDP packets and decode them into pixels and triggers. The second is pymepixviewer, an online control and data-acquisition program for general use, but with features geared toward mass-spectroscopy and ion imaging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Smart Data Mapping for Connecting Power System Model and Geospatial Data

Knowing the geospatial locations of power system model elements is the foundation for analyzing system vulnerability to natural hazards and connecting loads with end users and their communities. However, power system models and geospatial data for power grid assets may have been developed asynchronously without close coordination. Creating a direct mapping between the two may be a challenging task, considering heterogeneous data structures, target uses, historical legacies, and human errors. This work aims to build an automatic data mapping workflow to connect power system model elements and geospatial data for transmission network, and to support energy grid resilience studies for Puerto Rico. The primary steps in this workflow include constructing graphs using geospatial data, and aligning them to the transmission networks defined in the power system data. The results have been evaluated against existing manual mapping practices for part of the Puerto Rico Power Grid model to illustrate the performance of such auto-mapping solutions.

Resilience, geospatial data, grid transmission net↗
DOE OSTI2021

Structural basis for antibody binding to adenylate cyclase toxin reveals RTX linkers as neutralization-sensitive epitopes

RTX leukotoxins are a diverse family of prokaryotic virulence factors that are secreted by the type 1 secretion system (T1SS) and target leukocytes to subvert host defenses. T1SS substrates all contain a C-terminal RTX domain that mediates recruitment to the T1SS and drives secretion via a Brownian ratchet mechanism. Neutralizing antibodies against the Bordetella pertussis adenylate cyclase toxin, an RTX leukotoxin essential for B . pertussis colonization, have been shown to target the RTX domain and prevent binding to the α M β 2 integrin receptor. Knowledge of the mechanisms by which antibodies bind and neutralize RTX leukotoxins is required to inform structure-based design of bacterial vaccines, however, no structural data are available for antibody binding to any T1SS substrate. Here, we determine the crystal structure of an engineered RTX domain fragment containing the α M β 2 -binding site bound to two neutralizing antibodies. Notably, the receptor-blocking antibodies bind to the linker regions of RTX blocks I–III, suggesting they are key neutralization-sensitive sites within the RTX domain and are likely involved in binding the α M β 2 receptor. As the engineered RTX fragment contained these key epitopes, we assessed its immunogenicity in mice and showed that it elicits similar neutralizing antibody titers to the full RTX domain. The results from these studies will support the development of bacterial vaccines targeting RTX leukotoxins, as well as next-generation B . pertussis vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Singleton Sieving: Overcoming the Memory/Speed Trade-Off in Exascale k-mer Analysis

Traditional filter data structures, such as Bloom filters, do not offer necessary features that modern high-performance data analytics applications need in order to efficiently perform complex data analysis tasks. For example, MetaHipMer, a de novo metagenome assembler, can use filters to weed out singleton k-mers and reduce memory usage by 30%-70%. However, the filter needs the ability to associate values with k-mers in order to perform the analysis in a single communication pass. Bloom filters do not support value associations and cause the application to perform an extra communication pass, thereby increasing the run time. Therefore, MetaHipMer faces a trade off between memory and speed due to the limited capabilities of traditional filters. In this paper, we overcome the memory and speed trade off in MetaHipMer by integrating a GPU-based feature-rich filter, the Two-Choice filter (TCF), in the MetaHipMer pipeline. The TCF uses key-value association to approximately store k-mers with extensions. This allows MetaHipMer to perform k-mer analysis on the GPUs in a single communication pass. Our empirical analysis shows a 50% reduction in memory usage in k-mer analysis on each node in MetaHipMer without any effect on the overall run time or assembly quality. The memory reduction in turn results in a 43% reduction in the number of nodes required to assemble datasets and enables MetaHipMer to scale to much larger datasets.

McCoy, Hunter↗
DOE OSTI2023

3-O-Methyltolcapone and Its Lipophilic Analogues Are Potent Inhibitors of Transthyretin Amyloidogenesis with High Permeability and Low Toxicity

Transthyretin (TTR) is an amyloidogenic homotetramer involved in the transport of thyroxine in blood and cerebrospinal fluid. To date, more than 130 TTR point mutations are known to destabilise the TTR tetramer, leading to its extracellular pathological aggregation accumulating in several organs, such as heart, peripheral and autonomic nerves, and leptomeninges. Tolcapone is an FDA-approved drug for Parkinson’s disease that has been repurposed as a TTR stabiliser. We characterised 3-O-methyltolcapone and two newly synthesized lipophilic analogues, which are expected to be protected from the metabolic glucuronidation that is responsible for the lability of tolcapone in the organism. Immunoblotting assays indicated the high degree of TTR stabilisation, coupled with binding selectivity towards TTR in diluted plasma of 3-O-methyltolcapone and its lipophilic analogues. Furthermore, in vitro toxicity data showed their several-fold improved neuronal and hepatic safety compared to tolcapone. Calorimetric and structural data showed that both T4 binding sites of TTR are occupied by 3-O-methyltolcapone and its lipophilic analogs, consistent with an effective TTR tetramer stabilisation. Moreover, in vitro permeability studies showed that the three compounds can effectively cross the blood-brain barrier, which is a prerequisite for the inhibition of TTR amyloidogenesis in the cerebrospinal fluid. Our data demonstrate the relevance of 3-O-methyltolcapone and its lipophilic analogs as potent inhibitors of TTR amyloidogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Fox Trails

1. This software utilizes python pandas to pull data from P6 databases or XER files. The software transforms the datasets into multiple main tables by joining, filtering, iteratively flattening hierarchical structured data, and pivoting datasets to give simple flat output tables. The activity table includes all of the information related to an activity including activity codes, global, EPS, and project codes, UDFs, and WBS information as separate columns. This includes the code id, code value and sequence number for all levels in hierarchical codes. The resource table is similar to the activity table and includes all of the information related to resources on activities including UPFs and resource codes. The resource time phased table takes the resource information and time phases it for the budget, forecast, late, and actual dates/units/costs that closely matches P6's user interface's values as it implements the resource curve and calendars. The wbs table contains the WBS structure broken out by levels and includes UDFs, codes, and notebook topics. The final P6 data table is the relationships table which simply contains the relationships. 2. When a user updates the tool with data (via giving it P6 project names with database username/password information or XER files) the system creates the data in #1, then creates a networkx graph with the activity data imbedded in the node data and the relationships added as edges. Each edge also has it's float calculated (working time distance between the predecessor and successor) and attached to the edge. Activities are also tagged as a potential start of a path based on their constraints, constraint dates, remaining start date, and activity status. When a user enters an activity ID into the UI, it runs a shortest path calculation on the network graph between each node tagged as potential start to the entered activity id based on the float tagged on the edge. Each path returned by the algorithm contains all of the nodes on the path in order, as well as the total float of the edges that make the path. This data is then collected and returned to the user in the form of a gantt chart with groupings for each path that includes the total float for each group. 3. Similar to 2, if the user passes through a reference dataset each activity set in the path is checked to see if it had a path in the reference dataset, if that path was the primary path between the start and end activities, and what has changed regarding logic and durations. These changes are color coded and summarized before sent to the user to be displayed by the UI for simple discovery. 4. Utilizing the data from #1, the user can submit desired grouping code(s) and filters to the system. The system will then pull the activities, resources, and relationships and create a gantt chart based on the groupings sent and filtered based on the filters sent. 5. The system will produce a gantt chart in a similar method to #4, but allows interactivity with the data. As the user interacts with the gantt chart, the software captures the changes and stores it with the user making the change so that project controls and implement those changes in P6.

Fox, Ben↗
DOE OSTI2018

Recon3D enables a three-dimensional view of gene variation in human metabolism

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. As a result, these data provide a unique resource for investigating molecular mechanisms of human metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Thermodynamic Assessment of the Ag-Se System Aided by First-Principles Calculations

The substitution of Ag for Cu in CuIn x Ga 1-x Se 2 -based photovoltaic absorber layers can be used to adjust the bandgap energy to better optimize the overall cell efficiency. Based on available thermochemical, equilibrium, and structural data, the Ag-Se system has been assessed and modeled. Given the order-disorder structure transition Ag 2 Se, the 2- and 3-sublattice models were used to represent the low- and high-temperature phases of the intermetallic compound respectively. Density functional theory based first-principles calculations were used to calculate the Gibbs energy of formation of the end-member compounds. A set of modeling parameters was obtained by the CALculation of PHAse Diagram approach and reasonable agreement was obtained between the experimental thermodynamic properties of the stable phases and the phase relationships in the Ag-Se system.

Chemistry↗
DOE OSTI2025

Insights into the Complexation of Actinides by Diethylenetriaminepentaacetic Acid from Characterization of the Americium(III) Complex

Diethylenetriaminepentaacetic acid (DTPA) is a frequently used chelator in the nuclear and medical industries, especially for the complexation of trivalent actinides. However, structural data on these complexes in the solid-state have long remained elusive. Herein, a detailed structural analysis of the presented crystal structures of [C(NH 2 ) 3 ] 4 [Nd(DTPA)] 2 · n H 2 O and [C(NH 2 ) 3 ] 4 [Am(DTPA)] 2 · n H 2 O, where [C(NH 2 ) 3 ] + is guanidinium, details the subtle differences in the Lewis acidity between a lanthanide/actinide pair of similar ionic sizes. Contractions in nitrogen–metal bond lengths between neodymium(III) and americium(III) were observed, while the metal–oxygen bonds remained relatively consistent, highlighting the marginal favorability for actinide complexation over the lanthanides with moderately soft N-donors. Spectroscopic analysis shows significant splitting of many transitions and relatively strong electronic interactions with traditionally low-intensity transitions in the americium complex, as is demonstrated in the 7 F 0 → 7 F 5 transitions. Pressure-induced spectroscopic analysis showed surprisingly little effect on the americium complex, with 5 f →5 f transitions either not shifting or marginally shifting from 2 to 3 nm at 11.93 ± 0.06 GPa─atypical of a soft, N-donor americium complex under pressure. Finally, large voids occupied by water molecules in between the complexes within the crystal structure may be responsible for the lack of pressure response in the 5 f →5 f transitions.

absorption spectroscopy↗
DOE OSTI2018

Structure and mutagenic analysis of the lipid II flippase MurJ from Escherichia coli

The peptidoglycan cell wall provides an essential protective barrier in almost all bacteria, defining cellular morphology and conferring resistance to osmotic stress and other environmental hazards. The precursor to peptidoglycan, lipid II, is assembled on the inner leaflet of the plasma membrane. However, peptidoglycan polymerization occurs on the outer face of the plasma membrane, and lipid II must be flipped across the membrane by the MurJ protein before its use in peptidoglycan synthesis. Due to its central role in cell wall assembly, MurJ is of fundamental importance in microbial cell biology and is a prime target for novel antibiotic development. However, relatively little is known regarding the mechanisms of MurJ function, and structural data for MurJ are available only from the extremophile Thermosipho africanus. Here, we report the crystal structure of substrate-free MurJ from the gram-negative model organism Escherichia coli, revealing an inward-open conformation. Taking advantage of the genetic tractability of E. coli, we performed high-throughput mutagenesis and next-generation sequencing to assess mutational tolerance at every amino acid in the protein, providing a detailed functional and structural map for the enzyme and identifying sites for inhibitor development. Finally, through the use of sequence coevolution analysis, we identify functionally important interactions in the outward-open state of the protein, supporting a rocker-switch model for lipid II transport.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

CVEVOLVE

CVEvolve is an agentic AI system for autonomous algorithm discovery for scientific data processing. It creates workflows where large language model agents freely set up and configure development environments and evaluation harnesses, develop and improve data processing algorithms with designed exploration-exploitation balancing mechanisms, log history and findings in a structured database, and run holdout testing to ensure algorithm generalizability. CVEvolve offers a zero-code interface and does not require users to provide structured data and evaluation scripts.

Cherukara, MatthewJoseph [Argonne National Laborat↗