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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Software For Detecting, Analyzing, And Mitigating Anomalous Network Packets Through A Multi Dimensional Latent Space Representation

The code ingests network packet payloads, classifies the payload as anomalous or normal, and plots the payload in a 3-D latent space representation. It also enables user interaction with the representation to allow for the user to click on the packet payload in the latent space and determine host id, network topology, and access the raw packet data.

Anderson, MatthewW.↗
DOE OSTI2012

National Geothermal Data System: Interactive Assessment of Geothermal Energy Potential in the U.S.

Geothermal-relevant geosciences data from all 50 states (www.stategeothermaldata.org), federal agencies, national labs, and academic centers are being digitized and linked in a distributed online network via the U.S. Department of Energy-funded National Geothermal Data System (NGDS) to foster geothermal energy exploration and development through use of interactive online ‘mashups,’data integration, and applications. Emphasis is first to make as much information as possible accessible online, with a long range goal to make data interoperable through standardized services and interchange formats. An initial set of thirty geoscience data content models is in use or under development to define a standardized interchange format: aqueous chemistry, borehole temperature data, direct use feature, drill stem test, earthquake hypocenter, fault feature, geologic contact feature, geologic unit feature, thermal/hot spring description, metadata, quaternary fault, volcanic vent description, well header feature, borehole lithology log, crustal stress, gravity, heat flow/temperature gradient, permeability, and feature descriptions data like developed geothermal systems, geologic unit geothermal properties, permeability, production data, rock alteration description, rock chemistry, and thermal conductivity. Map services are also being developed for isopach maps, aquifer temperature maps, and several states are working on geothermal resource overview maps. Content models are developed preferentially from existing community use in order to encourage widespread adoption and promulgate minimum metadata quality standards. Geoscience data and maps from other NGDS participating institutions, or “nodes” (USGS, Southern Methodist University, Boise State University Geothermal Data Coalition) are being supplemented with extensive land management and land use resources from the Western Regional Partnership (15 federal agencies and 5 Western states) to provide access to a comprehensive, holistic set of data critical to geothermal energy development. As of September 2011, we have over 34,000 records registered in the system catalog, and 234,942 data resources online, along with scores of Web services to deliver integrated data to the desktop for free downloading or online use. The data exchange mechanism is built on the U.S. Geoscience Information Network (USGIN, http://usgin.org and http://lab.usgin.org) protocols and standards developed as a partnership of the Association of American State Geologists (AASG) and U.S. Geological Survey.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Laponite® and Laponite®‐PEO hydrogels with enhanced elasticity in phosphate‐buffered saline

Hydrogels of the synthetic clay Laponite® and Laponite®‐poly (ethylene oxide) (PEO) have long been studied as model systems to understand fundamental aspects of colloidal disks and colloid‐polymer systems. More recently, these systems have been explored for a variety of biomedical applications. However, there is limited information in the literature on the fundamental properties of Laponite and Laponite‐polymer gels at pH < 9. Here, we report the rheological behavior of Laponite and Laponite‐PEO systems at biologically relevant conditions (e.g. physiological pH and ionic strength) and examine the effect of phosphate‐buffered saline on the properties of the gel. Our results show that the elastic modulus of both Laponite and Laponite‐PEO gels increases dramatically, in some cases by one order of magnitude or more, after immersing gels in phosphate‐buffered saline. This may be due to an enhanced edge–face interaction between particles in buffered solutions, which would promote a long‐lasting network structure of clay particles. These results are relevant to the design of clay‐polymer gels and nanocomposites hydrogels for biomaterials applications. Copyright © 2015 John Wiley & Sons, Ltd.

Liu, Xiao↗
DOE OSTI2024

Coupled Thermo-Hydro-Mechanical Processes in Fractured Rocks: Some Past Scientific Highlights and Future Research Directions

Abstract Coupled thermo-hydro-mechanical (THM) processes in fractured rocks have been a topic of intense scientific research for more than 30 years. The present paper takes a look into the past and highlights some scientific advances which are of an unusual “out-of-the-box” nature, and then looks forward and discusses possible directions of future research in this interesting field of study. Concerning future research directions, we see a trend from a focus on coupled THM processes in single fractures or a few interacting fractures, to the study of coupled THM behavior in complex fracture network systems where the fractures act collectively giving rise to local stress concentration points and points of large pressure gradients. Three examples of future research directions are presented. First is an effort towards identifying characterizing parameters of a fracture network that play a direct controlling role in major coupled THM phenomena (such as induced seismicity and flow channeling), rather than parameters of stochastic distributions of fractures in the network. The second example of research direction is accounting for the heterogeneity and hierarchy of fractures in a fault or fracture zone which has been associated with major THM events in a number of geo-energy projects. The third example is at the opposite end of the first; here it is recognized that in some cases, the coupled THM processes in fractured rocks may be controlled dominantly by only a few key bridges. Identification, characterization, and evaluation of these key bridges should be one of the important research directions in the coming days.

58 GEOSCIENCES↗
DOE OSTI2016

Computational approaches to detect allosteric pathways in transmembrane molecular machines

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Biochemistry & Molecular Biology↗
DOE OSTI2015

Crystal structure analysis of a bacterial aryl acylamidase belonging to the amidase signature enzyme family

The atomic structure of a bacterial aryl acylamidase (EC 3.5.1.13; AAA) is reported and structural features are investigated to better understand the catalytic profile of this enzyme. Structures of AAA were determined in its native form and in complex with the analgesic acetanilide, p-acetaminophenol, at 1.70 Å and 1.73 Å resolutions, respectively. The overall structural fold of AAA was identified as an α/β fold class, exhibiting an open twisted β-sheet core surrounded by α-helices. The asymmetric unit contains one AAA molecule and the monomeric form is functionally active. The core structure enclosing the signature sequence region, including the canonical Ser-cisSer-Lys catalytic triad, is conserved in all members of the Amidase Signature enzyme family. The structure of AAA in a complex with its ligand reveals a unique organization in the substrate-binding pocket. The binding pocket consists of two loops (loop1 and loop2) in the amidase signature sequence and one helix (α10) in the non-amidase signature sequence. We identified two residues (Tyr{sup 136} and Thr{sup 330}) that interact with the ligand via water molecules, and a hydrogen-bonding network that explains the catalytic affinity over various aryl acyl compounds. The optimum activity of AAA at pH > 10 suggests that the reaction mechanism employs Lys{sup 84} as the catalytic base to polarize the Ser{sup 187} nucleophile in the catalytic triad. - Highlights: • We determined the first structure of a bacterial aryl acylamidase (EC 3.5.1.13). • Structure revealed spatially distinct architecture of the substrate-binding pocket. • Hydrogen-bonding with Tyr{sup 136} and Thr{sup 330} mediates ligand-binding and substrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Crystal structure of mupirocin form I, C26H44O9

The crystal structure of mupirocin Form I has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Mupirocin Form I crystallizes in space group P 2 1 (#4) with a = 12.562 81(16), b = 5.103 63(4), c = 21.713 34(29) Å, β = 100.932(1)°, V = 1366.91(2) Å 3 , and Z = 2. Although the three hydroxyl groups and the carboxylic acid participate in a three-dimensional hydrogen bond network, the crystal energy appears to be dominated by van der Waals interactions. The Rietveld-refined and density functional optimized structures differ significantly. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File ™ .

Kaduk, James A.↗
DOE OSTI2025

Affinity for OH – Produces Four-Coordinated Zn 2+ Impurities in Hydrated Amorphous Calcium Carbonate

Using ab initio based molecular dynamics and electronic structure calculations, we show that Zn impurities in hydrated amorphous calcium carbonate (ACC) have a much lower coordination number than other divalent impurities due to covalent interactions between the 3d Zn shell and the oxygen atoms of the carbonate and water groups. Further, the local structure around Zn in ACC, including the predicted low coordination number, is confirmed by X-ray absorption spectroscopy of synthetic Zn-bearing ACC. The strong Zn–O chemical interaction leads to substantial water dissociation and slightly disrupts the hydrogen bonding network. Implications of Zn 2+ incorporation for ACC stability are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Energy Minimization of Discrete Protein Titration State Models Using Graph Theory

There are several applications in computational biophysics which require the optimization of discrete interacting states; e.g., amino acid titration states, ligand oxidation states, or discrete rotamer angles. Such optimization can be very time-consuming as it scales exponentially in the number of sites to be optimized. In this paper, we describe a new polynomial-time algorithm for optimization of discrete states in macromolecular systems. This algorithm was adapted from image processing and uses techniques from discrete mathematics and graph theory to restate the optimization problem in terms of maximum flow-minimum cut graph analysis. The interaction energy graph, a graph in which vertices (amino acids) and edges (interactions) are weighted with their respective energies, is transformed into a flow network in which the value of the minimum cut in the network equals the minimum free energy of the protein, and the cut itself encodes the state that achieves the minimum free energy. Because of its deterministic nature and polynomial-time performance, this algorithm has the potential to allow for the ionization state of larger proteins to be discovered.

energy minimization↗
DOE OSTI2023

Understanding the Effect of Single Atom Cationic Defect Sites in an Al 2 O 3 (012) Surface on Altering Selenate and Sulfate Adsorption: An Ab Initio Study

Adsorption is a promising under-the-sink selenate remediation technique for distributed water systems. Recently it was shown that adsorption induced water network rearrangement control adsorption energetics on the α-Al 2 O 3 (012) surface. Here, we aim to elucidate the relative importance of the water network effects and surface cation identity on controlling selenate and sulfate adsorption energy using density functional theory calculations. Density functional theory (DFT) calculations predicted the adsorption energies of selenate and sulfate on nine transition metal cations (Sc–Cu) and two alkali metal cations (Ga and In) in the α-Al 2 O 3 (012) surface under simulated acidic and neutral pH conditions. We find that the water network effects had a larger impact on the adsorption energy than the cationic identity. However, cation identity secondarily controlled adsorption. Most cations decreased the adsorption energy, weakening the overall performance, the larger Sc and In cations enabled inner-sphere adsorption in acidic conditions because they relaxed outward from the surface, providing more space for adsorption. Additionally, only Ti induced Se selectivity over S by reducing the adsorbing selenate to selenite but not reducing the sulfate. Altogether, this study indicates that tuning water network structure will likely have a larger impact than tuning cation–selenate interactions for increasing adsorbate effectiveness.

Adsorption↗
DOE OSTI2022

Tuning the Solvation Structure in Aqueous Zinc Batteries to Maximize Zn-Ion Intercalation and Optimize Dendrite-Free Zinc Plating

Aqueous zinc batteries are recognized to suffer from H + /Zn 2+ coinsertion in the cathode, but few approaches have been reported to suppress deleterious H + intercalation. We realize this goal by tuning the solvation structure, using LiV 2 (PO 4 ) 3 (LVP) as a model cathode. Phase conversion of LVP induced by H + intercalation is observed in 4 m Zn(OTf) 2 , whereas dominant Zn 2+ insertion is confirmed in a ZnCl 2 water-in-salt electrolyte (WiSE). This disparity is ascribed to the complete absence of free water and a strong Zn 2+ –H 2 O interaction in the latter that interrupts the H 2 O hydrogen bonding network, thus suppressing H + intercalation. On the basis of this strategy, a novel PEG-based hybrid electrolyte is designed to replace the corrosive ZnCl2 WiSE. This system exhibits an optimized Zn 2+ solvation sheath with a similar low free water content, showing not only much better suppression of H + intercalation but also highly reversible Zn plating/stripping with a CE of ~99.7% over 150 cycles.

25 ENERGY STORAGE↗
DOE OSTI2023

Dynamic conformational switching underlies TFIIH function in transcription and DNA repair and impacts genetic diseases

Transcription factor IIH (TFIIH) is a protein assembly essential for transcription initiation and nucleotide excision repair (NER). Yet, understanding of the conformational switching underpinning these diverse TFIIH functions remains fragmentary. TFIIH mechanisms critically depend on two translocase subunits, XPB and XPD. To unravel their functions and regulation, we build cryo-EM based TFIIH models in transcription- and NER-competent states. Using simulations and graph-theoretical analysis methods, we reveal TFIIH’s global motions, define TFIIH partitioning into dynamic communities and show how TFIIH reshapes itself and self-regulates depending on functional context. Our study uncovers an internal regulatory mechanism that switches XPB and XPD activities making them mutually exclusive between NER and transcription initiation. By sequentially coordinating the XPB and XPD DNA-unwinding activities, the switch ensures precise DNA incision in NER. Mapping TFIIH disease mutations onto network models reveals clustering into distinct mechanistic classes, affecting translocase functions, protein interactions and interface dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Structure, electronic properties, and aggregation behavior of hydroxylated carbon nanotubes

We present a combined experimental and theoretical study to analyze the structure, electronic properties, and aggregation behavior of hydroxylated multiwalled carbon nanotubes (OH–MWCNT). Our MWCNTs have average diameters of ∼2 nm, lengths of approximately 100–300 nm, and a hydroxyl surface coverage θ∼0.1. When deposited on the air/water interface the OH–MWCNTs are partially soluble and the floating units interact and link with each other forming extended foam-like carbon networks. Surface pressure-area isotherms of the nanotube films are performed using the Langmuir balance method at different equilibration times. The films are transferred into a mica substrate and atomic force microscopy images show that the foam like structure is preserved and reveals fine details of their microstructure. Density functional theory calculations performed on model hydroxylated carbon nanotubes show that low energy atomic configurations are found when the OH groups form molecular islands on the nanotube's surface. This patchy behavior for the OH species is expected to produce nanotubes having reduced wettabilities, in line with experimental observations. OH doping yields nanotubes having small HOMO–LUMO energy gaps and generates a nanotube → OH direction for the charge transfer leading to the existence of more hole carriers in the structures. Our synthesized OH–MWCNTs might have promising applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Crystal Structures of SlyA Protein, a Master Virulence Regulator of Salmonella, in Free and DNA-bound States

SlyA is a master virulence regulator that controls the transcription of numerous genes in Salmonella enterica. We present here crystal structures of SlyA by itself and bound to a high-affinity DNA operator sequence in the slyA gene. SlyA interacts with DNA through direct recognition of a guanine base by Arg-65, as well as interactions between conserved Arg-86 and the minor groove and a large network of non-base-specific contacts with the sugar phosphate backbone. Our structures, together with an unpublished structure of SlyA bound to the small molecule effector salicylate (Protein Data Bank code 3DEU), reveal that, unlike many other MarR family proteins, SlyA dissociates from DNA without large conformational changes when bound to this effector. We propose that SlyA and other MarR global regulators rely more on indirect readout of DNA sequence to exert control over many genes, in contrast to proteins (such as OhrR) that recognize a single operator.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Neural network reconstruction of the dense matter equation of state from neutron star observables

The Equation of State (EoS) of strongly interacting cold and hot ultra-dense QCD matter remains a major challenge in the field of nuclear astrophysics. With the advancements in measurements of neutron star masses, radii, and tidal deformabilities, from electromagnetic and gravitational wave observations, neutron stars play an important role in constraining the ultra-dense QCD matter EoS. Here, in this work, we present a novel method that exploits deep learning techniques to reconstruct the neutron star EoS from mass-radius (M-R) observations. We employ neural networks (NNs) to represent the EoS in a model-independent way, within the range of ~1-7 times the nuclear saturation density. The unsupervised Automatic Differentiation (AD) framework is implemented to optimize the EoS, so as to yield through TOV equations, an M-R curve that best fits the observations. We demonstrate that this method works by rebuilding the EoS on mock data, i.e., mass-radius pairs derived from a randomly generated polytropic EoS. The reconstructed EoS fits the mock data with reasonable accuracy, using just 11 mock M-R pairs observations, close to the current number of actual observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Benchmarking machine learning interatomic potentials via phonon anharmonicity

Abstract Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, machine learning interatomic potentials (MLIPs) can accurately reproduce first-principles data at a cost similar to that of conventional interatomic potential approaches. While MLIPs have been extensively tested across various classes of materials and molecules, a clear characterization of the anharmonic terms encoded in the MLIPs is lacking. Here, we benchmark popular MLIPs using the anharmonic vibrational Hamiltonian of ThO 2 in the fluorite crystal structure, which was constructed from density functional theory (DFT) using our highly accurate and efficient irreducible derivative methods. The anharmonic Hamiltonian was used to generate molecular dynamics (MD) trajectories, which were used to train three classes of MLIPs: Gaussian approximation potentials, artificial neural networks (ANN), and graph neural networks (GNN). The results were assessed by directly comparing phonons and their interactions, as well as phonon linewidths, phonon lineshifts, and thermal conductivity. The models were also trained on a DFT MD dataset, demonstrating good agreement up to fifth-order for the ANN and GNN. Our analysis demonstrates that MLIPs have great potential for accurately characterizing anharmonicity in materials systems at a fraction of the cost of conventional first principles-based approaches.

interatomic potentials↗
DOE OSTI2020

Genomics-enabled analysis of specialized metabolism in bioenergy crops: Current progress and challenges

Plants produce a staggering diversity of specialized small molecule metabolites that play vital roles in mediating environmental interactions and stress adaptation. This chemical diversity derives from dynamic biosynthetic pathway networks that are often species-specific and operate under tight spatiotemporal and environmental control. A growing divide between demand and environmental challenges in food and bioenergy crop production have intensified research on these complex metabolite networks and their contribution to crop fitness. High-throughput omics technologies provide access to ever-increasing data resources for investigating plant metabolism. However, the efficiency of using such system-wide data to decode the gene and enzyme functions controlling specialized metabolism has remained limited; due largely to the recalcitrance of many plants to genetic approaches and the lack of ‘user-friendly’ biochemical tools for studying the diverse enzyme classes involved in specialized metabolism. With emphasis on terpenoid metabolism in the bioenergy crop switchgrass as an example, this review aims to illustrate current advances and challenges in the application of DNA synthesis and synthetic biology tools for accelerating the functional discovery of genes, enzymes and pathways in plant specialized metabolism. These technologies have accelerated knowledge development on the biosynthesis and physiological roles of diverse metabolite networks across many ecologically and economically important plant species and can provide resources for application to precision breeding and natural product metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗