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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Three dimensional cluster analysis for atom probe tomography using Ripley’s K-function and machine learning

The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley’s K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K (r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K (r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. Here we find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K (r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Out-of-Oblivion Cage Molecules and Their Porous Crystalline Phases

An automated molecular porosity detection approach was developed and applied to PubChem, a repository of ca. 94 million molecules, to discover intrinsically porous cage molecules, which, although previously considered by chemists, have remained in oblivion to the porous solids community as neither their crystal structures nor solid-state porosity have been previously reported. The effort led to identification of six such cage molecules reported over the span of the last two decades. The following crystal structure prediction effort suggested that these molecules can form stable low-energy porous crystalline phases. One of the identified lowest energy phases exhibits zeolite-range porosity with pore diameters of ca. 8 Å and internal surface area of 1070 m 2 /g.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel–Ligand Docking

The identification of promising lead compounds showing pharmacological activities toward a biological target is essential in early stage drug discovery. With the recent increase in available small-molecule databases, virtual high-throughput screening using physics-based molecular docking has emerged as an essential tool in assisting fast and cost-efficient lead discovery and optimization. However, the best scored docking poses are often suboptimal, resulting in incorrect screening and chemical property calculation. We address the pose classification problem by leveraging data-driven machine learning approaches to identify correct docking poses from AutoDock Vina and Glide screens. To enable effective classification of docking poses, we present two convolutional neural network approaches: a three-dimensional convolutional neural network (3D-CNN) and an attention-based point cloud network (PCN) trained on the PDBbind refined set. We demonstrate the effectiveness of our proposed classifiers on multiple evaluation data sets including the standard PDBbind CASF-2016 benchmark data set and various compound libraries with structurally different protein targets including an ion channel data set extracted from Protein Data Bank (PDB) and an in-house KCa3.1 inhibitor data set. Our experiments show that excluding false positive docking poses using the proposed classifiers improves virtual high-throughput screening to identify novel molecules against each target protein compared to the initial screen based on the docking scores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Water freezing and ice melting

The generalized replica exchange method (gREM) is designed to sample states with coexisting phases and thereby to describe strong first order phase transitions. The isobaric MD version of the gREM is presented and applied to freezing of liquid water, and melting of hexagonal and cubic ice. It is confirmed that coexisting states are well sampled. The statistical temperature as a function of enthalpy, T S (H), is obtained. Hysteresis between freezing and melting is observed and discussed. The entropic analysis of phase transitions is applied and equilibrium transition temperatures, latent heats, and surface tensions are obtained for hexagonal ice↔liquid and cubic ice↔liquid, with excellent agreement with published values. A new method is given to assign water molecules among various symmetry types. As a result, pathways for water freezing, ultimately leading to hexagonal ice, are found to contain intermediate layered structures built from hexagonal and cubic ice.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Confusion-Driven Machine Learning of Structural Phases of a Flexible, Magnetic Stockmayer Polymer

We use a semisupervised, neural-network-based machine learning technique, the confusion method, to investigate structural transitions in magnetic polymers, which we model as chains of magnetic colloidal nanoparticles characterized by dipole–dipole and Lennard-Jones interactions. As input for the neural network, we use the particle positions and magnetic dipole moments of equilibrium polymer configurations, which we generate via replica-exchange Wang–Landau simulations. We demonstrate that by measuring the classification accuracy of neural networks, we can effectively identify transition points between multiple structural phases without any prior knowledge of their existence or location. We corroborate our findings by investigating relevant conventional order parameters. Our study furthermore examines previously unexplored low-temperature regions of the phase diagram, where we find new structural transitions between highly ordered helicoidal polymer configurations.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Pathways through equilibrated states with coexisting phases for gas hydrate formation

Under ambient conditions, water freezes to either hexagonal ice or a hexagonal/cubic composite ice. The presence of hydrophobic guest molecules introduces a competing pathway: gas hydrate formation, with the guests in clathrate cages. Here, the pathways of the phase transitions are sought as sequences of states with coexisting phases, using a generalized replica exchange algorithm designed to sample them in equilibrium, avoiding nonequilibrium processes. For a dilute solution of methane in water under 200 atm, initializing the simulation with the full set of replicas leads to methane trapped in hexagonal/cubic ice, while gradually adding replicas with decreasing enthalpy produces the initial steps of hydrate growth. Once a small amount of hydrate is formed, water rearranges to form empty cages, eventually transforming the remainder of the system to metastable β ice, a scaffolding for hydrates. It is suggested that configurations with empty cages are reaction intermediates in hydrate formation when more guest molecules are available. Furthermore, free energy profiles show that methane acts as a catalyst reducing the barrier for β ice versus hexagonal/cubic ice formation.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Isobaric molecular dynamics version of the generalized replica exchange method (gREM): Liquid–vapor equilibrium

A prescription for sampling isobaric generalized ensembles with molecular dynamics is presented and applied to the generalized replica exchange method (gREM), which was designed for simulating first-order phase transitions. The properties of the isobaric gREM ensemble are discussed and a study is presented of the liquid-vapor equilibrium of the guest molecules given for gas hydrate formation with the mW water model. As a result, phase diagrams, critical parameters, and a law of corresponding states are obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Molecular Dynamics Study of the Effect of Grafting Density on Ion Diffusivity in a MARTINI Coarse-Grained Strong Polyelectrolyte Brush

Because surface-grafted polyelectrolyte brushes (PEBs) are responsive to external stimuli, such as electric fields and ionic strength, PEBs are attractive for applications ranging from drug delivery to separation technologies. Essential to PEB utilization is understanding how critical parameters like grafting density (σ) impact the PEB structure and the dynamics of the PEB and counterions. To study the effect of σ on PEB and the counterion structure and dynamics, we fine-tune a coarse-grained model that retains the chemical specificity of a strong polyelectrolyte, poly[(2-(methacryloyloxy)ethyl) trimethylammonium chloride] (PMETAC), using the MARTINI force field. Using “salt-free” conditions where the counterion concentration balances the charge on the brush, we build coarse-grained (CG) molecular dynamics simulations for MARTINI PMETAC brushes (N = 150 monomers; M W = 31.2 kg/mol) at experimentally relevant values of σ = 0.05, 0.10, 0.20, and 0.40 chains/nm 2 . Using 5 μs simulations, we investigate the effects of grafting density on the PEB structure, ion dissociation dynamics, polymer mobility, and counterion diffusivity. Results show that competition between electrostatic interactions, steric hindrance, and polymer mobility controls counterion diffusivity. Finally, the interplay of these factors leads to diffusivity that depends non-monotonically on σ, with counterion diffusivity peaking at an intermediate σ = 0.10 chains/nm 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2025

..delta..-Learning of High-Fidelity Electronic Structure Using Graph Neural Networks with Modified Node-Level Features

In this work, we present a ..delta..-learning approach for predicting the eigenvalues calculated with the hybrid functional HSE06 (..epsilon..nkHSE) for a set of metal and nitrogen doped graphene catalysts (MNCs) from Perdew-Burke-Ernzerhof (PBE) inputs. The model presented here incorporates electronic scalar features along with structural information in a graph neural network (GNN). In particular, the PBE eigenvalues for different bands and k-points and orbital-resolved projectors are combined with the applied potential as node-level features along with structural information within the Atomistic Line Graph Neural Network (ALIGNN) architecture. These features enable flexibility for systems with electrified interfaces, such as in electrocatalysts and achieves mean absolute error (MAE) of less than 0.1 eV. The machine learning model reported here achieves a strong generalization to left-out adsorbates (MAE = 0.074 eV) and leave-one-chemical-space-out (MAE = 0.08 eV) and completely left-out metals (MAE = 0.072 eV), confirming the robustness of the machine learning (ML) model in predicting ..epsilon..nkHSE.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Alkali-Metal Interlocking of 2D V 4 O 10 Sheets Defines Discretized Interlayer Shear Relationships

Low-dimensional materials manifest structural anisotropy, quantum confinement, and tightly bound excitonic states, which make them attractive building blocks that can be assembled within three-dimensional laterally stitched heterostructures, stacked van der Waals solids, and complex moiré superlattices. Ion intercalation in the galleries between layered materials provides a means of modifying interlayer separation and coupling, but it is also known to drive the shearing of the layers. In this article, we explore the distinct ligand coordination environments afforded by vanadyl oxygens of singular [V 4 O 10 ] sheets and examine how the size, polarizability, and stoichiometry of Group I cations sandwiched between such layers determine the interlocking of the sheets in stacked structures. Based on the topochemical insertion of alkali-metal ions into the layered λ-V 2 O 5 , we identify seven types of guest ion coordination sites discretized into four distinct regimes of interlayer shear in units of half octahedral widths. The coordination preferences of intercalated cations govern how they interlock 2D [V 4 O 10 ] sheets and engender specific shear conformations. We present evidence that static and dynamic disorder in guest ion arrangement modulate the magnetic structure of the intercalated compounds based on electrostatic polarization, localization of charge and spin density, and lattice distortion. The results illustrate the use of topochemical ion insertion to modulate stacking relationships and magnetic transition characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Structural basis of promiscuous substrate transport by Organic Cation Transporter 1

Organic Cation Transporter 1 (OCT1) plays a crucial role in hepatic metabolism by mediating the uptake of a range of metabolites and drugs. Genetic variations can alter the efficacy and safety of compounds transported by OCT1, such as those used for cardiovascular, oncological, and psychological indications. Despite its importance in drug pharmacokinetics, the substrate selectivity and underlying structural mechanisms of OCT1 remain poorly understood. Here, we present cryo-EM structures of full-length human OCT1 in the inward-open conformation, both ligand-free and drug-bound, indicating the basis for its broad substrate recognition. Comparison of our structures with those of outward-open OCTs provides molecular insight into the alternating access mechanism of OCTs. We observe that hydrophobic gates stabilize the inward-facing conformation, whereas charge neutralization in the binding pocket facilitates the release of cationic substrates. These findings provide a framework for understanding the structural basis of the promiscuity of drug binding and substrate translocation in OCT1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Organosolv-Water Cosolvent Phase Separation on Cellulose and its Influence on the Physical Deconstruction of Cellulose: A Molecular Dynamics Analysis

Deconstruction of cellulose is crucial for the chemical conversion of lignocellulose into fuel/bioproduct precursors. Recently, a water-organosolv cosolvent system (THF-water) has been shown to both phase-separate on cellulose surfaces and partially deconstruct Avicel (cellulose) in the absence of acid. Here we employ molecular dynamics simulations to determine whether other common water-organosolv cosolvent systems (acetone, ethanol, and γ-valerolactone) exhibit phase separation at cellulose surface and whether this alters a purely physical cellulose dissociation pathway. Despite finding varied degrees of phase-separation of organosolv on cellulose surfaces, physical dissociation is not enhanced. Interestingly, however, the total amount the median water-cellulose contact lifetimes increases for the cosolvent systems in the order of THF > acetone > ethanol > γ-valerolactone. Together our results indicate two points: a purely physical process for deconstruction of cellulose is unlikely for these cosolvents, and in THF-water, unlike γ-valerolactone- (and some concentrations of acetone and ethanol) water cosolvents, a significant fraction of surface water is slowed. As a result, this slowing may be of importance in enhancing chemical deconstruction of cellulose, as it permits an increase in potential THF-water-cellulose reactions, even while the amount of water near cellulose is decreased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Effect of structure and composition on the electronic excitation induced amorphization of La2Ti2−xZrxO7 ceramics

Abstract Understanding the response of ceramics operating in extreme environments is of interest for a variety of applications. Ab initio molecular dynamic simulations have been used to investigate the effect of structure and B -site (=Ti, Zr) cation composition of lanthanum-based oxides (La 2 B 2 O 7 ) on electronic-excitation-induced amorphization. We find that the amorphous transition in monoclinic layered perovskite La 2 Ti 2 O 7 occurs for a lower degree of electronic excitation than for cubic pyrochlore La 2 Zr 2 O 7 . While in each case the formation of O 2 -like molecules drives the structure to an amorphous state, an analysis of the polyhedral connection network reveals that the rotation of TiO 6 octahedra in the monoclinic phase can promote such molecule formation, while such octahedral rotation is not possible in the cubic phase. However, once the symmetry of the cubic structure is broken by substituting Ti for Zr, it becomes less resistant to amorphization. A compound made of 50% Ti and 50% Zr (La 2 TiZrO 7 ) is found to be more resistant in the monoclinic than in the cubic phase, which may be related to the lower bandgap of the cubic phase. These results illustrate the complex interplay of structure and composition that give rise to the radiation resistance of these important functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Electronic Excitation Dynamics in Liquid Water under Proton Irradiation

Molecular behaviour of liquid water under proton irradiation is of great importance to a number of technological and medical applications. The highly energetic proton generates a time-varying field that is highly localized and heterogeneous at the molecular scale, and massive electronic excitations are produced as a result of the field-matter interaction. Using first-principles quantum dynamics simulations, we reveal details of how electrons are dynamically excited through non-equilibrium energy transfer from highly energetic protons in liquid water on the atto/femto-second time scale. Water molecules along the path of the energetic proton undergo ionization at individual molecular level, and the excitation primarily derives from lone pair electrons on the oxygen atom of water molecules. A reduced charge state on the energetic proton in the condensed phase of water results in the strongly suppressed electronic response when compared to water molecules in the gas phase. These molecular-level findings provide important insights into understanding the water radiolysis process under proton irradiation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗