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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Electric Double-Layer Structure in Primitive Model Electrolytes. Comparing Molecular Dynamics with Local-Density Approximations

We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations of binary electrolytes comprised of equisized ions in an implicit solvent. The Bikerman LDA, which considers ions to occupy a lattice, poorly captures excluded volume interactions between primitive model ions. Instead, LDAs based on the Carnahan–Starling (CS) hard-sphere equation of state capture simulated values of ideal and excess chemical potential profiles extremely well, as is the relationship between surface charge density and electrostatic potential. Excellent agreement between the EDL capacitances predicted by CS-LDAs and computed in molecular simulations is found even in systems where ion correlations drive strong density and free charge oscillations within the EDL, despite the inability of LDAs to capture the oscillations in the detailed EDL profiles.

25 ENERGY STORAGE↗
DOE OSTI2023

Predicted structural proteome of Sphagnum divinum and proteome-scale annotation

Sphagnum-dominated peatlands store a substantial amount of terrestrial carbon. The genus is undersampled and under-studied. No experimental crystal structure from any Sphagnum species exists in the Protein Data Bank and fewer than 200 Sphagnum-related genes have structural models available in the AlphaFold Protein Structure Database. Tools and resources are needed to help bridge these gaps, and to enable the analysis of other structural proteomes now made possible by accurate structure prediction. We present the predicted structural proteome (25,134 primary transcripts) of Sphagnum divinum computed using AlphaFold, structural alignment results of all high-confidence models against an annotated nonredundant crystallographic database of over 90,000 structures, a structure-based classification of putative Enzyme Commission (EC) numbers across this proteome, and the computational method to perform this proteome-scale structure-based annotation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Global and adaptive K-nearest neighbor graphs in a spectral target detector based on Schroedinger Eigenmaps

The Schroedinger Eigenmaps (SE) embedding has been previously introduced and applied to spectral target detection problems in hyperspectral imagery (HSI). The proposed SEbased detection approach combines the spectral and spatial connectivity of target-like pixels into the Schroedinger operator by using a “knowledge propagation” scheme. Likewise, it has been noted the impact that the local data structure modeling has over the SE-based detector. This local data structure is modeled by using an adjacency graph, i.e, set of vertices and edges, that in most of the applications is a k nearest neighbor (knn) graph. In this paper, the impact of k in the graph-building process is analyzed and assessed from a target detection point of view. Here, two ways to estimate the parameter k in the graph construction are considered and their assessment is performed by using two HSI data sets and the Receiver Optimal Curve (ROC) as a detection performance metric

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Knowledge Graph for End-to-End Traceability of an Integrated Human-Earth System Model

Integrated human-Earth system models inform energy-water-land system dynamics and policies, yet their results are difficult to trace through input-data, model structure, scenario configurations, and solved outputs. Because this information is siloed across disconnected artifacts, process-based IAMs have historically lacked a unified, queryable representation. Such lack of traceability prevents researchers from systematically isolating the multi-sector drivers of complex outcomes (such as tracing water-scarcity results back to distant energy-system dynamics) or conducting holistic uncertainty attribution across hundreds of interacting parameters. To address this concern, our work documents the software engineering process of a knowledge graph that unifies these four layers for the Global Change Analysis Model (GCAM-USA_Reference scenario, GCAM v9.1). The graph was built as a relational property graph in DuckDB from the run’s own artifacts: the input-preparation dependency map (gcamdata chunk map), the model’s XML input files, the run configuration, and the results database (BaseX), successfully mapping the model’s declared structure. The resulting graph comprises 204,321 nodes and 1,687,814 edges across 16 node types and 15 edge types, with approximately 16.3 million time-series values stored separately to maintain structural efficiency. To ensure representation fidelity, every edge carries an epistemic-status annotation recording the warrant for the relationship (structural, provenance, dependency, or model-derived), and a machine-readable provenance ledger classifying the origin of every schema element. Evaluation against a fixed five-benchmark suite with locked baselines reports zero structural orphans, zero dangling edge endpoints, and 100% of output-producing technologies traceable to raw input files. Two interactive interfaces present the graph, including a serverless browser application built on DuckDB-Wasm. By establishing the first end-to-end provenance framework for an IAM, this work enables researchers and scientists to systematically audit complex policy scenarios, debug model structures, and trace policy-relevant outputs to their data origins in real time.

Artifical Intelligence↗
DOE OSTI2018

Potential-specific structure at the hematite-electrolyte interface

The atomic-scale structure of interfaces between metal oxides and aqueous electrolytes controls their catalytic, geochemical, and corrosion behavior. Measurements that probe these interfaces in situ provide important details of ion and solvent arrangements, but atomically precise structural models do not exist for common oxide-electrolyte interfaces far from equilibrium. Using a novel cell, we measured the structure of the hematite (a-Fe 2 O 3 ) (110$\bar{2}$)-electrolyte interface under controlled electrochemical bias using synchrotron crystal truncation rod X ray scattering. At increasingly cathodic potentials, charge-compensating protonation of surface oxygen groups increases the coverage of specifically bound water while adjacent water layers displace outwardly and became disordered. Returning to open circuit potential leaves the surface in a persistent metastable protonation state. The flux of current and ions at applied potential is thus regulated by a unique interfacial electrolyte environment, suggesting that electrical double layer models should be adapted to the dynamically changing interfacial structure far from equilibrium.

electrochemistry↗
DOE OSTI2023

Study of beyond nearest-neighbor environment and intermediate-range order in a sodium aluminosilicate geopolymer using Reverse Monte Carlo modeling

A large scale three-dimensional structural model of a geopolymer with an approximate composition of NaAlSi 2 O 6 .5.5H 2 O obtained by Reverse Monte Carlo (RMC) modeling based on experimental high-energy x-ray diffraction is presented for the first time in order to obtain information regarding beyond nearest-neighbor environment and intermediate-range order (IRO). RMC model exhibits a three-dimensional network consisting of randomly cross-linked AlO 4 and SiO 4 tetrahedral units with uniformly distributed Na atoms and H 2 O molecules. The bond angle distributions, i.e. T-O-T, O-T-O and Na-O-Na angles, are somewhat distorted with lower values compared to analogous crystal systems. The origin of the first peak in the structure factor indicating IRO is investigated using the partial structure factors; Na-Na, Si-Na, Al-Si, O-H, and H-H atom pairs are found to be the main contributors. Ring size distribution analysis demonstrates that the structure mainly involves 6-, 7- and 8-membered rings. Finally, the coherence length of these IRO characteristics is ~10.3 Å.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Chasing the open-state structure of pentameric ligand-gated ion channels

Remarkable advances have been made toward the structural characterization of ion channels in the last two decades. However, the unambiguous assignment of well-defined functional states to the obtained structural models has proved challenging. In the case of the superfamily of nicotinic-receptor channels (also referred to as pentameric ligand-gated ion channels [pLGICs]), for example, two different types of model of the open-channel conformation have been proposed on the basis of structures solved to resolutions better than 4.0 Å. At the level of the transmembrane pore, the open-state models of the proton-gated pLGIC from Gloeobacter violaceus (GLIC) and the invertebrate glutamate-gated Cl – channel (GluCl) are very similar to each other, but that of the glycine receptor (GlyR) is considerably wider. Indeed, the mean distances between the axis of ion permeation and the Cα atoms at the narrowest constriction of the pore (position -2') differ by ~2 Å in these two classes of model, a large difference when it comes to understanding the physicochemical bases of ion conduction and charge selectivity. Here, we take advantage of the extreme open-channel stabilizing effect of mutations at pore-facing position 9'. We find that the I9'A mutation slows down entry into desensitization of GLIC to the extent that macroscopic currents decay only slightly by the end of pH 4.5 solution applications to the extracellular side for several minutes. We crystallize (at pH 4.5) two variants of GLIC carrying this mutation and solve their structures to resolutions of 3.12 Å and 3.36 Å. Furthermore, we perform all-atom molecular dynamics simulations of ion permeation and picrotoxinin block, using the different open-channel structural models. On the basis of these results, we favor the notion that the open-channel structure of pLGICs from animals is much closer to that of the narrow models (of GLIC and GluCl) than it is to that of the GlyR.

Gonzalez-Gutierrez, Giovanni↗
DOE OSTI2025

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Raman spectroscopy of glasses in the As-Te system

For the first time, the Raman spectra of As{sub x}Te{sub 1-x} glasses, 0.2{<=}x{<=}0.6, have been measured over the entire glass-forming range. The spectra exhibit three broad spectral features attributed to vibrations of structural units having Te-Te, As-Te and As-As bonds. The observed chemical disorder in the glasses is discussed on the basis of partial bond fractions derived from the integrated intensity of the Raman modes. The underlying structural model suggests a dissociation of AsTe- or As{sub 2}Te{sub 3}-related units in the glass melt. The spectra of glasses quenched from different temperatures, as well as those of the annealed vitreous alloys, are consistent with predictions of the model. - Graphical abstract: Raman spectra of the As{sub x}Te{sub 1-x} glasses (0.2{<=}x{<=}0.4 and 0.4{<=}x{<=}0.6). Fractional concentrations of Te-Te, As-Te and As-As bonds in the As{sub x}Te{sub 1-x} glasses calculated using experimental Raman data. The solid lines represent predictions of the dissociation model assuming that the main chemically ordered structural units are related to AsTe. Highlights: Black-Right-Pointing-Pointer For the first time, the Raman spectra of As{sub x}Te{sub 1-x} glasses, 0.2{<=}x{<=}0.6, were measured. Black-Right-Pointing-Pointer The partial bond fractions were derived from the integrated intensity of the Raman modes. Black-Right-Pointing-Pointer An empirical quantitative approach to the Raman data was proposed for the reaction modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Structure Based Prediction of Neoantigen Immunogenicity

The development of immunological therapies that incorporate peptide antigens presented to T cells by MHC proteins is a long sought-after goal, particularly for cancer, where mutated neoantigens are being explored as personalized cancer vaccines. Although neoantigens can be identified through sequencing, bioinformatics and mass spectrometry, identifying those which are immunogenic and able to promote tumor rejection remains a significant challenge. Here we examined the potential of high-resolution structural modeling followed by energetic scoring of structural features for predicting neoantigen immunogenicity. After developing a strategy to rapidly and accurately model nonameric peptides bound to the common class I MHC protein HLA-A2, we trained a neural network on structural features that influence T cell receptor (TCR) and peptide binding energies. The resulting structurally-parameterized neural network outperformed methods that do not incorporate explicit structural or energetic properties in predicting CD8 + T cell responses of HLA-A2 presented nonameric peptides, while also providing insight into the underlying structural and biophysical mechanisms governing immunogenicity. Our proof-of-concept study demonstrates the potential for structure-based immunogenicity predictions in the development of personalized peptide-based vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from quantitative models inform actions ranging from short-term and local decisions, such as those about technology and infrastructure deployment, and global and long-term negotiations and targets. Computational limits require model designers to balance coverage and resolution (i.e., breadth versus depth). Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses with less resolution than models that focus on a single sector's energy use. GCAM balances global supply and demand of all energy carriers projecting prices using internal calculations for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This globally comprehensive model was used to frame the Long-Term Strategy of the United States: Pathways to Net-Zero Greenhouse Gas Emissions by 2050, which the White House released in 2021 and has been used to inform national and global economy-wide climate change mitigation discussions and strategy development for decades. Unlike GCAM, sectoral models focus on a portion of the energy sector and with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects electricity system capacity expansion and operation with high-fidelity representation of emerging technologies for deep decarbonization, such as variable renewable energy and energy storage, and integration of these technologies into the electric grid. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices, with a focus on adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of electrification and energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas mitigation strategies in the United States. The integrated multisector and sector-specific modeling approaches represented by GCAM and these sectoral models are complementary. The integrated multisector approach calculates energy pricing and resource allocation within the model, which is important for consistency when future conditions substantially diverge from current conditions in transformative scenarios. The sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and trade-offs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and it addresses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

On the mesoscopic origins of high viscosities in some polyelectrolyte-surfactant mixtures

Oppositely charged polyelectrolyte (PE) surfactant mixtures allow the control of rheological parameters of a solution even at fairly low concentrations. For example, addition of 0.3 wt. % of anionic surfactant to a 1 wt. % solution of the polycation JR 400 increases the viscosity by 4 orders of magnitude. Recently, we could show that this increase is related to the formation of mixed, rod-like PE/surfactant aggregates which interconnect several polyelectrolyte chains [Hoffmann et al., Europhys. Lett. 104, 28001 (2013)]. In this paper, we refine our structural model of the aggregates to obtain a more consistent picture of their internal structure for different anionic surfactants. Combining small angle neutron scattering (SANS) and neutron spin-echo (NSE) allows us to determine the size of the aggregates. By comparing different contrasts, the internal structure of the aggregates can be elucidated and it is seen that the PE in the aggregates retains a relatively high freedom of movement. We proceeded to investigate the influence of the surfactant concentration and the surfactant type on structure and dynamics of the mixed aggregates. It is seen that the structural parameters of the aggregates depend very little on the surfactant concentration and headgroup. However, it is crucial to incorporate a sufficient amount of PE in the aggregates to increase the viscosity of the aggregates. By comparing viscous samples at 1 wt. % PE concentration with samples at a PE concentration of 0.3 wt. %, where no significant increase in viscosity is observed, we find that similar aggregates are formed already at this lower PE concentrations. However, the amount of PE incorporated in them is insufficient to interconnect several PE chains and therefore, they do not increase viscosity. So, our detailed investigation combining contrast variation SANS and NSE does not only allow to explain the viscosity behavior but also to deduced detailed information regarding the structures and the dynamics especially of the polyelectrolyte within the complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

First-principle calculation of core level binding energies of Li{sub x}PO{sub y}N{sub z} solid electrolyte

We present first-principle calculations of core-level binding energies for the study of insulating, bulk phase, compounds, based on the Slater-Janak transition state model. Those calculations were performed in order to find a reliable model of the amorphous Li{sub x}PO{sub y}N{sub z} solid electrolyte which is able to reproduce its electronic properties gathered from X-ray photoemission spectroscopy (XPS) experiments. As a starting point, Li{sub 2}PO{sub 2}N models were investigated. These models, proposed by Du et al. on the basis of thermodynamics and vibrational properties, were the first structural models of Li{sub x}PO{sub y}N{sub z}. Thanks to chemical and structural modifications applied to Li{sub 2}PO{sub 2}N structures, which allow to demonstrate the relevance of our computational approach, we raise an issue concerning the possibility of encountering a non-bridging kind of nitrogen atoms (=N{sup −}) in Li{sub x}PO{sub y}N{sub z} compounds.

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

Short- and medium-range order in Sb–Se glasses

Neutron diffraction measurements were performed to investigate the structure of Sb{sub x}Se{sub 100−x} bulk glasses with x=5, 10, 15, 20 and 25 at% Sb. The total pair distribution functions show two peaks at 2.36 Å and 2.64 Å, which are attributed to Se–Se and Sb–Se bonds, respectively. The coordination numbers calculated from these peaks indicate that Sb atoms are three-coordinated and Se atoms are two-coordinated for all the above compositions. However, the composition dependences of the first two peaks in the structure factors show an obvious change between 15 and 20 at% Sb, indicating that the medium-range structure is changed in this range of Sb content. In order to elucidate the medium-range structure, reverse Monte Carlo simulation was used with coordination number constraints. The structure models consisting of a mixture of the SbSe{sub 3/2} network and Se{sub n} chain clusters were in good agreement with neutron diffraction data for Se-rich glass (5, 10 and 15 at% Sb). On the other hand, a better fit was obtained for Sb{sub 25}Se{sub 75} glass with a model based on the network structure formed by connected SbSe{sub 3} units. - Graphical abstract: A 50 Å slice of the RMC configuration for Sb{sub 15}Se{sub 85} glass. - Highlights: • Sb atoms are three-coordinated and Se atoms are two-coordinated. • The medium-range structure changes between 15 and 20 at%. • The phase-separation tendency is observed in Se-rich glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Enumeration as a Tool for Structure Solution: A Materials Genomic Approach to Solving the Cation-Ordered Structure of Na 3 V 2 (PO 4 ) 2 F 3

While powder diffraction methods are routinely utilized to optimize structural models for compounds whose crystal structures are known, the determination of unknown structures is far more challenging. When the unknown structure is large, structure solution can become a virtually intractable problem using standard structure solution methodologies, especially when the space group cannot be unambiguously resolved. One such system is the promising Na-ion battery cathode material Na 3 V 2 (PO 4 ) 2 F 3 whose high temperature and room temperature structures were previously solved, but whose more complex low-temperature structure could not be determined. Here, a novel materials genomic approach is demonstrated for the solution of the unknown 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 in which enumeration methods are first used to generate a large number (~3,000) of trial structures based on plausible orderings of Na ions and then automated Rietveld refinements are carried out to optimize each of these trial structures. Based on both the analysis of the ensemble of optimized trial structures and the density functional theory energy minimization of selected trial structures, the 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 is best described as belonging to the space group A2 1 am with unit cell dimensions of a = 9.01928(4), b = 27.1379(1), c = 10.73307(5). The 100 K unit cell has a large volume of 2627.07(2) Å 3 with Z = 12 and 33 independent crystallographic sites (9 Na, 3 V, 3 P, 12 O, and 6 F) that is 3x and 6x larger than the room- and high-temperature polymorphs of this phase, respectively. Finally, the novel methods described here will be generally applicable for the solution of the complex cation-ordered structures that commonly occur for battery materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impacts of irrigation expansion on moist-heat stress based on IRRMIP results

Irrigation rapidly expanded during the 20 th century, affecting climate via water, energy, and biogeochemical changes. Previous assessments of these effects predominantly relied on a single Earth System Model, and therefore suffered from structural model uncertainties. Here we quantify the impacts of historical irrigation expansion on climate by analysing simulation results from six Earth system models participating in the Irrigation Model Intercomparison Project (IRRMIP). Results show that irrigation expansion causes a rapid increase in irrigation water withdrawal, which leads to less frequent 2-meter air temperature heat extremes across heavily irrigated areas (≥4 times less likely). However, due to the irrigation-induced increase in air humidity, the cooling effect of irrigation expansion on moist-heat stress is less pronounced or even reversed, depending on the heat stress metric. In summary, this study indicates that irrigation deployment is not an efficient adaptation measure to escalating human heat stress under climate change, calling for carefully dealing with the increased exposure of local people to moist-heat stress.

54 ENVIRONMENTAL SCIENCES↗