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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Observations of Molecular Isotope Fractionation in Prestellar Cores

Anomalously fractionated isotopic material is found in many primitive Solar System objects, such as meteorites and comets. It has been suggested that these extreme isotope ratios, are tracers of interstellar chemistry. We will present observations of the nitrogen and carbon fractionation chemistry in dense molecular clouds, particularly in cores where sUbstantial freeze-out of molecules, namely CO, onto dust has occurred. Recent models have suggested that non-depleted species, carbon and nitrogen-rich, may undergo isotopic enhancements in these conditions. The fractionation ratios measured in different interstellar molecules will be discussed and compared to the ratios determined in molecular clouds, comets, and meteoritic material.

Milam, Stefanie N.↗
DOE OSTI2022

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Liquid-induced topological transformations of cellular microstructures

The fundamental topology of cellular structures—the location, number and connectivity of nodes and compartments—can profoundly affect their acoustic, electrical5, chemical, mechanical and optical properties, as well as heat, fluid and particle transport. Approaches that harness swelling, electromagnetic actuation and mechanical instabilities in cellular materials have enabled a variety of interesting wall deformations and compartment shape alterations, but the resulting structures generally preserve the defining connectivity features of the initial topology. Achieving topological transformation presents a distinct challenge for existing strategies: it requires complex reorganization, repacking, and coordinated bending, stretching and folding, particularly around each node, where elastic resistance is highest owing to connectivity. Here we introduce a two-tiered dynamic strategy that achieves systematic reversible transformations of the fundamental topology of cellular microstructures, which can be applied to a wide range of materials and geometries. Our approach requires only exposing the structure to a selected liquid that is able to first infiltrate and plasticize the material at the molecular scale, and then, upon evaporation, form a network of localized capillary forces at the architectural scale that ‘zip’ the edges of the softened lattice into a new topological structure, which subsequently restiffens and remains kinetically trapped. Reversibility is induced by applying a mixture of liquids that act separately at the molecular and architectural scales (thus offering modular temporal control over the softening–evaporation–stiffening sequence) to restore the original topology or provide access to intermediate modes. Guided by a generalized theoretical model that connects cellular geometries, material stiffness and capillary forces, we demonstrate programmed reversible topological transformations of various lattice geometries and responsive materials that undergo fast global or localized deformations. In conclusion, we then harness dynamic topologies to develop active surfaces with information encryption, selective particle trapping and bubble release, as well as tunable mechanical, chemical and acoustic properties.

42 ENGINEERING↗
DOE OSTI2022

High-pressure hydrogen decompression in sulfur crosslinked elastomers

High-pressure storage and cyclic (de)pressurization of hydrogen gas is known to result in degradation and failure of gas canisters, hoses, linings, and O-rings as the relatively small hydrogen molecule can readily permeate most materials. Hence, identifying material compositions that are less susceptible to hydrogen-induced damage is of significant importance to the hydrogen energy infrastructure. Here, we use classical atomistic molecular dynamics simulations to study hydrogen exposed ethylene-propylene-diene monomer (EPDM) rubber, an elastomer typically used in O-rings. We make chemical modifications to the model by adjusting the crosslink density and report on gas solubility, diffusivity, and molecular restructuring in response to rapid decompression. Our simulations indicate that increases in crosslink density can reduce volumetric expansion during decompression and result in smaller free volume pore sizes. However, these favorable properties for sealing materials come with a tradeoff. At pressure, crosslinks introduce extra free volume, providing potential sites for gas localization, the precursor to cavitation-induced failure.

08 HYDROGEN↗
DOE OSTI2020

Theory of finite-temperature two-dimensional structural transformations in group-IV monochalcogenide monolayers

An account of two-dimensional (2D) structural transformations in 2D ferroelectrics predicts an evolution from a structure with Pnm 2 1 symmetry into a structure with square P4/nmm symmetry and is consistent with experimental evidence, while another argues for a transformation into a structure with rectangular Pnmm symmetry. An analysis of the assumptions made in these models is provided here, and six fundamental results concerning these transformations are contributed as follows: (i) Softened phonon modes produce rotational modes in these materials. (ii) The transformation to a structure with P4/nmm symmetry occurs at the lowest critical temperature T c . (iii) The hypothesis that one unidirectional optical vibrational mode underpins the 2D transformation is unwarranted. (iv) Being successively more constrained, a succession of critical temperatures ( T c < T c ' < T c " ) occurs in going from molecular dynamics calculations with the NPT and NVT ensembles onto models with unidirectional oscillations. (v) The choice of exchange-correlation functional impacts the estimate of the critical temperature. (vi) Importantly, the correct physical picture of these transformations is one in which rotational modes confer a topological character to the 2D transformation via the proliferation of vortices.

2d ferroelectrics↗
DOE OSTI2022

Revealing hidden defects through stored energy measurements of radiation damage

With full knowledge of a material’s atomistic structure, it is possible to predict any macroscopic property of interest. In practice, this is hindered by limitations of the chosen characterization techniques. For example, electron microscopy is unable to detect the smallest and most numerous defects in irradiated materials. Instead of spatial characterization, we propose to detect and quantify defects through their excess energy. Differential scanning calorimetry of irradiated Ti measures defect densities five times greater than those determined using transmission electron microscopy. Our experiments also reveal two energetically distinct processes where the established annealing model predicts one. Molecular dynamics simulations discover the defects responsible and inform a new mechanism for the recovery of irradiation-induced defects. The combination of annealing experiments and simulations can reveal defects hidden to other characterization techniques and has the potential to uncover new mechanisms behind the evolution of defects in materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Invariant surface elastic properties in FCC metals and their correlation to bulk properties revealed by machine learning methods

In this work, we present a combination of machine-learned models that predicts the surface elastic properties of general free surfaces in face-centered cubic (FCC) metals. These models are built by combining a semi-analytical method based on atomistic simulations to calculate surface properties with the artificial neural network (ANN) method or the boosted regression tree (BRT) method. The latter is also used to link bulk properties and surface orientation to surface properties. The surface elastic properties are represented by their invariants considering plane elasticity within a polar method. The resulting models are shown to accurately predict the surface elastic properties of seven pure FCC metals (Cu, Ni, Ag, Au, Al, Pd, Pt). The BRT model reveals the correlations between bulk and corresponding surface properties in terms of invariants, which can be used to guide the design of complex nano-sized particles, wires and films. Finally, by expressing the surface excess energy density as a function of surface elastic invariants, fast predictions of surface energy as a function of in-plane deformations can be made from these model constructs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Raman spectrum and polarizability of liquid water from deep neural networks

We introduce a scheme based on machine learning and deep neural networks to model the environmental dependence of the electronic polarizability in insulating materials. Application to liquid water shows that training the network with a relatively small number of molecular configurations is sufficient to predict the polarizability of arbitrary liquid configurations in close agreement with ab initio density functional theory calculations. In combination with a neural network representation of the interatomic potential energy surface, the scheme allows us to calculate the Raman spectra along 2-nanosecond classical trajectories at different temperatures for H 2 O and D 2 O. The vast gains in efficiency provided by the machine learning approach enable longer trajectories and larger system sizes relative to ab initio methods, reducing the statistical error and improving the resolution of the low-frequency Raman spectra. Decomposing the spectra into intramolecular and intermolecular contributions elucidates the mechanisms behind the temperature dependence of the low-frequency and stretch modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Hydrogenation of interstellar molecules: a survey for methylenimine (CH2NH)

Methylenimine (CH2NH) has been convincingly detected for the first time outside the Galactic center as part of a study of the hydrogenation of interstellar molecules. We have observed transitions from energy levels up to about 100 K above the ground state in the giant molecular clouds W51, Orion KL and G34.3 + 0.15. In addition, CH2NH was found at the " radical-ion peak" on the quiescent ridge of material in the Orion molecular cloud. The abundance ratio CH2NH/HCN at the radical-ion peak agrees with the predictions of recent gas-phase chemical models. This ratio is an order of magnitude higher in the warmer cloud cores, suggesting additional production pathways for CH2NH, probably on interstellar grains.

Non-NASA Center↗
NASA NTRS2005

Prediction of Mechanical Properties of Polymers With Various Force Fields

The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.

Odegard, Gregory M.↗
NASA NTRS2019

Life's Requirements

Life on Earth is molecular in nature, with its lifelike attributes- e.g., information processing and catalysis- emerging as a result of both the specific properties of those molecules and the interactions among them. If this is a general model for life, then life must require (i) a source of energy, with which to build and sustain molecular complexity and information processing; (ii) elemental raw materials, from which to construct molecules having specific properties and reactivity; (iii)a solvent that supports the synthesis of the full range of molecules required by life and properly mediates the full range of necessary interactions among those molecules; and (iv) physicochemical conditions in which life's molecules can be synthesized, are appropriately stable, and can interact as needed for lifelike function. For life on Earth, these general requirements, respectively, take the specific form: (i) light energy in visible-to-near-infrared wavelengths or chemical energy as provided by oxidation–reduction disequilibrium, (ii) the "biogenic "elements (carbon, hydrogen, oxygen, nitrogen, phosphorus, and sulfur) (iii)liquid water, and (iv) specific ranges in temperature, pH, salinity, pressure, and other environmental factors. Our knowledge of these factors relates to cellula rlife as we observe it now or can infer from the fossil or molecular records. Life's origin may be constrained by a more stringent set of requirements that are, as yet,not fully understood.

Habitability↗
DOE OSTI2021

Deciphering the non-linear impact of Al on chemical durability of silicate glass

The role of Al in aluminosilicate glasses remains somewhat a mystery: at low concentrations, it increases the resistance to hydrolysis of the glass, whereas at high concentrations an opposite effect is observed. To understand the origin of the phenomenon on a fundamental atomistic scale, we performed 577 MD simulations and applied potential mean force (PMF) calculations to estimate the activation barriers for hydrolysis and to statistically correlate them with local structural features of the glass. Models of pure silicate and aluminosilicate glasses are constructed and investigated. PMF simulation results are further validated by the experimental measurements and revealed that Al is very easy to dissociate, but it also increases the glass chemical durability through significantly increasing both the strength of Si and network connectivity of the glass. In contrast, at high Al concentration, preferential dissolution of Al weakens the silicate network, which it supposes to strengthen, and so the glass resistance becomes poor. Through PMF calculations, we evaluated the activation barriers for dissociating bonds around Al as 0.49 eV, which is less than a half of the energy to dissociate bonds around Si in pure silicate (1.22 eV) and around Si in aluminosilicate glass (1.34 eV), all these energy differences being statistically significant. Molecular structural level investigation revealed that Si with Al as a second neighbor in the glass network has a significantly higher activation energy for dissociation than Si in pure silicate glass. Furthermore, the proposed approach opens the way to the development of quantitative predictive models of glass durability.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Modern chemical graph theory

Abstract Graph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Molecular Structures

Leite, Leonardo S. G.↗
DOE OSTI2025

Proton radiation effects in indium oxide using cascade molecular dynamics simulations

Metal oxide (MO) semiconductors, characterized by their wide band gaps and notable charge transport properties, are promising candidates for electronic applications in extreme environments, including near-Earth space. However, atomistic simulations of radiation–matter interactions in MOs remain challenging due to the limitations of existing interatomic potentials, which often fail to capture both the short-range repulsive forces essential for radiation damage modeling and the long-range electrostatic effects governing defect evolution. In this work, we develop a customized interatomic potential tailored for radiation damage simulations in indium oxide (In 2 O 3 ) as a model system, a representative MO material. Our potential integrates the Ziegler-Biersack-Littmark potential to accurately describe short-range interactions with Buckingham and Coulombic potentials to account for long-range forces. We perform molecular dynamics simulations of low-energy proton irradiation using this custom potential. We employ the primary knock-on atom (PKA) cascade method to study atomic displacements and primary defect formation. Simulations were conducted for 1 keV proton irradiation in four randomly chosen directions, and PKA-driven defect analyses at 5, 10, and 15 keV to examine the effects of direction and energy level on damage generation. Our results provide insight into the impact of irradiation direction and energy level on the cascade evolution and defect formation mechanisms.

Atomistic simulations↗
NASA NTRS1999

Design Through Simulation of a Molecular Sieve Column for Treatment of MON-3

The presence of water in propellant-grade MON-3 is a concern in the Aerospace Industry. NASA Johnson Space Center (JSC), White Sands Test Facility (WSTF) Propulsion Department has evaluated many types of molecular sieves for control of iron, the corrosion product of water in Mixed Oxides of Nitrogen (MON-3). In 1995, WSTF initiated laboratory and pilot-scale testing of molecular sieve type 3A for removal of water and iron. These tests showed sufficient promise that a series of continuous recycle tests were conducted at WSTF. Periodic samples of the circulating MON-3 solution were analyzed for water (wt %) and iron (ppm, wt). This test column was modeled as a series of transfer units; i. e., each unit represented the height equivalent of a theoretical plate. Such a model assumes there is equilibrium between the adsorbent material and the effluent stream from the unit. Operational and design parameters were derived based on the simulation results. These parameters were used to predict the design characteristics of a proposed molecular sieve column for removal of water and iron from MON-3 at the NASA Kennedy Space Center (KSC). In addition, these parameters were used to simulate a small, single-pass operation column at KSC currently used for treating MON-3. The results of this work indicated that molecular sieve type 3A in 1/16 in. diameter pellets, in a column 2.5 ft. in diameter, 18 ft. in height, and operated at 25 gpm is adequate for the required removal of water and iron from MON-3.

Swartz, A. Ben↗
NASA NTRS2002

Computational Nanomechanics of Carbon Nanotubes and Composites

Nanomechanics of individual carbon and boron-nitride nanotubes and their application as reinforcing fibers in polymer composites has been reviewed with interplay of theoretical modeling, computer simulations and experimental observations. The emphasis in this work is on elucidating the multi-length scales of the problems involved, and of different simulation techniques that are needed to address specific characteristics of individual nanotubes and nanotube polymer-matrix interfaces. Classical molecular dynamics simulations are shown to be sufficient to describe the generic behavior such as strength and stiffness modulus but are inadequate to describe elastic limit and nature of plastic buckling at large strength. Quantum molecular dynamics simulations are shown to bring out explicit atomic nature dependent behavior of these nanoscale materials objects that are not accessible either via continuum mechanics based descriptions or through classical molecular dynamics based simulations. As examples, we discus local plastic collapse of carbon nanotubes under axial compression and anisotropic plastic buckling of boron-nitride nanotubes. Dependence of the yield strain on the strain rate is addressed through temperature dependent simulations, a transition-state-theory based model of the strain as a function of strain rate and simulation temperature is presented, and in all cases extensive comparisons are made with experimental observations. Mechanical properties of nanotube-polymer composite materials are simulated with diverse nanotube-polymer interface structures (with van der Waals interaction). The atomistic mechanisms of the interface toughening for optimal load transfer through recycling, high-thermal expansion and diffusion coefficient composite formation above glass transition temperature, and enhancement of Young's modulus on addition of nanotubes to polymer are discussed and compared with experimental observations.

Srivastava, Deepak↗
NASA NTRS1995

A three-dimensional model of the Orion Nebula

We have constructed a geometric model for the Orion Nebula exploiting the fact that most of the radiation arises from a relatively thin layer of ionized material near the ionization front on the near side of the giant molecular cloud OMC-1. As a first step, an extinction corrected surface brightness map of H alpha emission was combined with point by point determinations of the electron density to determine the thickness of the emitting layer across the nebula. The second step involved calculation of the geometry that would satisfy the derived emitting layer thickness constraint, the surface brightness in H alpha, and the assumption that all of the ionizing radiation comes from a single star, theta(sup 1) Ori C. This was done both for the case of a constant gas density along a line of sight and the more realistic case of an exponentially decreasing density. The resulting models show that M42 is a highly irregular object, with regions in the ionization front where the local slope in the geometry is steeper producing higher surface brightnesses. This model also explains local ionization variations near the Bright Bar and the brightest region about 40 sec southwest of theta(sup 1) Ori C.

Wen, Zheng↗
NASA NTRS2011

Models of Isotopic Fractionation in Prestellar Cores

Anomalously fractionated isotopic material is found in many primitive Solar System objects, such as meteorites and comets. It is thought, in some cases, to trace interstellar matter that was incorporated into the Solar Nebula without undergoing significant processing. We will present the results of models of the nitrogen, oxygen, and carbon fractionation chemistry in dense molecular clouds, particularly in cores where substantial freeze-out of molecules on to dust has occurred. The range of fractionation ratios expected in different interstellar molecules will be discussed and compared to the ratios measured in molecular clouds, comets and meteoritic material. These studies make several predictions that can be tested in the near future by high-resolution molecular line observations with ALMA.

Charnley, Steven B.↗