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NASA NTRS1986

Numerical studies of collapsing interstellar clouds

Numerical simulation of the structure and evolution of interstellar clouds was initiated. Steps were taken toward an integrated treatment of the dynamical, thermal, and chemical processes entering model calculations. A detailed study was made of radiative transfer in molecular lines to allow model predictions to be tested against empirical data. The calculations have successfully reproduced and explained several observed cloud properties, including abundances of complex molecular species and the apparent depletion of CO in dense cores.

Bodenheimer, P. H.↗

DOE OSTI2024

A reactive molecular dynamics model for uranium/hydrogen containing systems

Uranium-based materials are valuable assets in the energy, medical, and military industries. However, understanding their sensitivity to hydrogen embrittlement is particularly challenging due to the toxicity of uranium and the computationally expensive nature of quantum-based methods generally required to study such processes. In this regard, we have developed a Chebyshev Interaction Model for Efficient Simulation (ChIMES) that can be employed to compute energies and forces of U and UH3 bulk structures with vacancies and hydrogen interstitials with accuracy similar to that of Density Functional Theory (DFT) while yielding linear scaling and orders of magnitude improvement in computational efficiency. Here, we show that the bulk structural parameters, uranium and hydrogen vacancy formation energies, and diffusion barriers predicted by the ChIMES potential are in strong agreement with the reference DFT data. We then use ChIMES to conduct molecular dynamics simulations of the temperature-dependent diffusion of a hydrogen interstitial and determine the corresponding diffusion activation energy. Our model has particular significance in studies of actinides and other high-Z materials, where there is a strong need for computationally efficient methods to bridge length and time scales between experiments and quantum theory.

36 MATERIALS SCIENCE↗

DOE OSTI2023

MLMOD: Machine Learning Methods for Data-Driven Modeling in LAMMPS

MLMOD is a software package for incorporating machine learning approaches and models into simulations of microscale mechanics and molecular dynamics in LAMMPS. Recent machine learning approaches provide promising data-driven approaches for learning representations for system behaviors from experimental data and high fidelity simulations. The package facilitates learning and using data-driven models for (i) dynamics of the system at larger spatial-temporal scales (ii) interactions between system components, (iii) features yielding coarser degrees of freedom, and (iv) features for new quantities of interest characterizing system behaviors. MLMOD provides hooks in LAMMPS for (i) modeling dynamics and time-step integration, (ii) modeling interactions, and (iii) computing quantities of interest characterizing system states. The package allows for use of machine learning methods with general model classes including Neural Networks, Gaussian Process Regression, Kernel Models, and other approaches. Here we discuss our prototype C++/Python package, aims, and example usage. For related papers, examples, updates, and additional information see https://github.com/atzberg/mlmod and http://atzberger.org/.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

ORNL_AISD_NiPt

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for three different sizes of the crystal structure: 256 atoms, 864 atoms, and 2,048 atoms, each of which contains 1900 configurations. For each size of the crystal structure, the data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in three compressed zipped folders: atoms256.zip, atoms864.zip, atoms2048.zip Each zipped folder contains the data that describes crystals of size 256 atoms, 864 atoms, and 2,048 atoms respectively. Each one of the three zipped folders contains the data structured in the following way: -Ni_ground_state.cfg --> atomic configuration for the pure nickel -Pt_ground_state.cfg --> atomic configuration for the pure platinum -Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder. Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms256.zip is 65,046. The total number of atomic configurations contained in atoms864.zip is 63,936. The total number of atomic configurations contained in atoms2048.zip is 61,997. The total number of atomic configurations spanned by the entire dataset is 190,979. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büccchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D

36 MATERIALS SCIENCE↗

DOE OSTI2025

Lattice structure and dynamics of sparse molecular crystals: OsO4 and RuO4

This dataset contains input and output files from DFT simulations used to reproduce the electronic and phonon calculations of bulk and molecular OsO₄ and RuO₄. The files include data from initial electronic structure and phonon calculations performed using different functionals: PBE, PBEsol, and vdW-DF-optB86b. The computed phonon frequencies are compared with Raman crystal and gas-phase frequencies from existing literature, while the calculated phonon density of states (PhDOS) is compared with experimental PhDOS data.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Recreating Giants Impacts in the Laboratory: Shock Compression of MgSiO 3 Bridgmanite to 14 Mbar

Understanding giant impacts requires accurate description of how extreme pressures and temperatures affect the physical properties of the constituent materials. Here, we report shock experiments on two polymorphs of MgSiO 3 : enstatite and bridgmanite (perovskite) crystals.We obtain pressure-density shock equation of state to 14 Mbar and more than 9 g/cm 3 , a 40% increase in density from previous data on MgSiO 3 . Density-functional-theory molecular dynamics (DFT-MD) simulations provide predictions for the shock Hugoniot curves for bridgmanite and enstatite and suggest that the Grüneisen parameter decreases with increasing density. The good agreement between the simulations and the experimental data, including for the shock temperature along the enstatite Hugoniot reveals that DFT-MD simulations reproduce well the behavior of dense fluid MgSiO 3 .We also reveal a high optical reflectance indicative of a metal-like electrical conductivity which supports the hypothesis that magma oceans may contribute to planetary magnetic field generation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1985

Solar pressure and molecular decay in cometary atmospheres

The effects of solar pressure and molecular decay on number density in cometary atmospheres are rigorously separated and scale lengths for each are determined from an analysis of observed brightness profiles in the solar and antisolar directions. It is found that the pressure scale length of CN is approximately 160,000 km and that of C2 is approximately 110,000 km. The scale length for molecular decay, heretofore incorrectly inferred from the observational data, is approximately 3 times as long as the pressure scale lengths. It is difficult to determine adequately from observations that extend no more than about 100,000 km from the comet nucleus. The scale length for molecular decay by photodissociation or whatever cause is found to be about 350,000 km for C2 and 500,000 km for CN.

Beard, D. B.↗

DOE OSTI2020

Employing Molecular Phylodynamic Methods to Identify and Forecast HIV Transmission Clusters in Public Health Settings: A Qualitative Study

Molecular HIV surveillance is a promising public health strategy for curbing the HIV epidemic. Clustering technologies used by health departments to date are limited in their ability to infer/forecast cluster growth trajectories. Resolution of the spatiotemporal dynamics of clusters, through phylodynamic and phylogeographic modelling, is one potential strategy to develop a forecasting tool; however, the projected utility of this approach needs assessment. Prior to incorporating novel phylodynamic-based molecular surveillance tools, we sought to identify possible issues related to their feasibility, acceptability, interpretation, and utility. Qualitative data were collected via focus groups among field experts (n = 17, 52.9% female) using semi-structured, open-ended questions. Data were coded using an iterative process, first through the development of provisional themes and subthemes, followed by independent line-by-line coding by two coders. Most participants routinely used molecular methods for HIV surveillance. All agreed that linking molecular sequences to epidemiological data is important for improving HIV surveillance. We found that, in addition to methodological challenges, a variety of implementation barriers are expected in relation to the uptake of phylodynamic methods for HIV surveillance. The participants identified several opportunities to enhance current methods, as well as increase the usability and utility of promising works-in-progress.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high‐resolution mass spectrometry data across a freshwater stream network

Abstract Advancing our understanding of dissolved organic matter (DOM) chemistry in aquatic systems necessitates the integration of data streams from multiple analytical platforms. Some measurements require pretreatment with solid phase extraction (SPE), while others are performed directly on whole water samples. Evidence has suggested that SPE will be biased against select DOM fractions, leading to concerns over the ability to establish data linkages across platforms with variable needs for SPE pretreatment, such as those from optical measurements and those that provide high‐resolution molecular information. Here, we directly addressed this concern by assessing the impact of SPE on DOM optical properties through excitation–emission matrices with parallel factor analysis (PARAFAC) for 47 samples across a stream network within a single watershed reflective of variable DOM sources. PARAFAC data was further paired with molecular information obtained by Fourier transform ion cyclotron resonance mass spectrometry (FTICR‐MS). A comparison of PARAFAC models first revealed no systematic qualitative differences in major components between whole water DOM and DOM isolated by SPE (SPE‐DOM); however, quantitative biases against select components were observed. Further linkages with FTICR‐MS data revealed that the molecular fingerprint associated with each PARAFAC component was consistent between the whole water DOM and SPE‐DOM. Our results suggest that bulk scale linkages across these analytical platforms could be inferred irrespective of the observed quantitative biases resulting from SPE for samples within this example watershed. This work represents a key step toward the systematic evaluation of linkages between optical and high‐resolution mass spectrometry datasets in freshwater lotic environments.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2006

Grain Surface Chemistry and the Composition of Interstellar Ices

Submicron sized dust grains are an important component of the interstellar medium. In particular they provide surface where active chemistry can take place. At the low temperatures (-10 K) of the interstellar medium, colliding gas phase species will stick, diffuse, react, and form an icy mantle on these dust grains. This talk will review the principles of grain surface chemistry and delineate important grain surface routes, focusing on reactions involving H, D, and O among each other and with molecules such as CO. Interstellar ice mantles can be studied through the fundamental vibrations of molecular species in the mid-infrared spectra of sources embedded in or located behind dense molecular clouds. Analysis of this type of data has provided a complex view of the composition of these ices and the processes involved. Specifically, besides grain surface chemistry, the composition of interstellar ices is also affected by thermal processing due to nearby newly formed stars. This leads to segregation between different ice components as well as outgassing. The latter results in the formation of a so-called Hot Core region with a gas phase composition dominated by evaporated mantle species. Studies of such regions provide thus a different view on the ice composition and the chemical processes involved. Interstellar ices can also be processed by FUV photons and high energy cosmic ray ions. Cosmic ray processing likely dominates the return of accreted species to the gas phase where further gas phase reactions can take place. These different chemical routes towards molecular complexity in molecular clouds and particularly regions of star formation will be discussed.

Tielens, A. G. G. M.↗

DOE OSTI2025

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗

DOE OSTI2022

A simple technique to classify diffraction data from dynamic proteins according to individual polymorphs

One often observes small but measurable differences in the diffraction data measured from different crystals of a single protein. These differences might reflect structural differences in the protein and may reveal the natural dynamism of the molecule in solution. Partitioning these mixed-state data into single-state clusters is a critical step that could extract information about the dynamic behavior of proteins from hundreds or thousands of single-crystal data sets. Mixed-state data can be obtained deliberately (through intentional perturbation) or inadvertently (while attempting to measure highly redundant single-crystal data). To the extent that different states adopt different molecular structures, one expects to observe differences in the crystals; each of the polystates will create a polymorph of the crystals. After mixed-state diffraction data have been measured, deliberately or inadvertently, the challenge is to sort the data into clusters that may represent relevant biological polystates. Here, this problem is addressed using a simple multi-factor clustering approach that classifies each data set using independent observables, thereby assigning each data set to the correct location in conformational space. This procedure is illustrated using two independent observables, unit-cell parameters and intensities, to cluster mixed-state data from chymotrypsinogen (ChTg) crystals. It is observed that the data populate an arc of the reaction trajectory as ChTg is converted into chymotrypsin.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Evaluation of cloud height, optical thickness, and phase retrievals from the CHROMA algorithm applied to Sentinel-3 OLCI data

We previously developed the Cloud Height Retrieval from O 2 Molecular Absorption (CHROMA) algorithm for the Ocean Color Instrument (OCI) on the new NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Here, we apply CHROMA to observations from the Ocean Land Colour Instrument (OLCI) to guide expectations for PACE, as it will take some time to obtain large-scale validation data for OCI. We use cloud top height (CTH), phase, and (for liquid clouds) cloud optical thickness (COT) data from the ground-based Atmospheric Radiation Measurement (ARM) network to evaluate the OLCI retrievals. We found that OLCI and Moderate Resolution Imaging Spectroradiometer (MODIS) CTH compare similarly well to the ARM reference. OLCI has a tendency to underestimate CTH as CTH increases, and algorithm assumptions about cloud geometric thickness may contribute to this. ARM COT from multifilter shadowband radiometers (MFRSR) and Sun photometers are well-correlated with one another, albeit with a roughly 30 % offset on average; OLCI and MODIS COT agree more closely with the MFRSR data. OLCI retrieval uncertainty estimates show skill at telling low-uncertainty cases from high-uncertainty ones, although CTH uncertainties are underestimated. Additionally, we compare the OLCI data to satellite retrievals based on thermal infrared measurements from MODIS and Sea and Land Surface Temperature Radiometer (SLSTR) data. Differences are broadly consistent with physical expectations based on the A-band vs. thermal techniques, although one key challenge in such aggregated comparisons is different cloud masking sensitivities and algorithm failure rates meaning additional sampling differences are introduced. We conclude by discussing the transition to and possible enhancements for PACE OCI.

Sayer, Andrew M. [Univ. of Maryland Baltimore Coun↗

NASA NTRS2010

The Composition of Titan's Lower Atmosphere and Simple Surface Volatiles as Measured by the Cassini-Huygens Probe Gas Chromatograph Mass Spectrometer Experiment

The Cassini-Huygens Probe Gas Chromatograph Mass Spectrometer (GCMS) determined the composition of the Titan atmosphere from ~140km altitude to the surface. After landing, it returned composition data of gases evaporated from the surface. Height profiles of molecular nitrogen (N2), methane (CH4) and molecular hydrogen (H2) were determined. Traces were detected on the surface of evaporating methane, ethane (C2H6), acetylene (C2H2), cyanogen (C2N2) and carbon dioxide (CO2). The methane data showed evidence that methane precipitation occurred recently. The methane mole fraction was (1.48+/-0.09) x 10(exp -2) in the lower stratosphere (139.8 km to 75.5 km) and (5.65+/-0.18) x 10(exp -2) near the surface (6.7 km to the surface). The molecular hydrogen mole fraction was (1.01+/-0.16) x 10(exp -3) in the atmosphere and (9.90+/-0.17) x 10(exp -4) on the surface. Isotope ratios were 167.7+/-0.6 for N-14/N-15 in molecular nitrogen, 91.1+/-1.4 for C-12/C-13 in methane and (1.35+/-0.30) x 10(exp -4) for D/H in molecular hydrogen. The mole fractions of Ar-36 and radiogenic Ar-40 are (2.1+/-0.8) x 10(exp -7) and (3.39 +/-0.12) x 10(exp -5) respectively. Ne-22 has been tentatively identified at a mole fraction of (2.8+/-2.1) x 10(exp -7) Krypton and xenon were below the detection threshold of 1 x 10(exp -8) mole fraction. Science data were not retrieved from the gas chromatograph subsystem as the abundance of the organic trace gases in the atmosphere and on the ground did not reach the detection threshold. Results previously published from the GCMS experiment are superseded by this publication.

Niemann, H. B.↗

NASA NTRS1999

Polyphasic taxonomy of the genus Shewanella and description of Shewanella oneidensis sp. nov

The genus Shewanella has been studied since 1931 with regard to a variety of topics of relevance to both applied and environmental microbiology. Recent years have seen the introduction of a large number of new Shewanella-like isolates, necessitating a coordinated review of the genus. In this work, the phylogenetic relationships among known shewanellae were examined using a battery of morphological, physiological, molecular and chemotaxonomic characterizations. This polyphasic taxonomy takes into account all available phenotypic and genotypic data and integrates them into a consensus classification. Based on information generated from this study and obtained from the literature, a scheme for the identification of Shewanella species has been compiled. Key phenotypic characteristics were sulfur reduction and halophilicity. Fatty acid and quinone profiling were used to impart an additional layer of information. Molecular characterizations employing small-subunit 16S rDNA sequences were at the limits of resolution for the differentiation of species in some cases. As a result, DNA-DNA hybridization and sequence analyses of a more rapidly evolving molecule (gyrB gene) were performed. Species-specific PCR probes were designed for the gyrB gene and used for the rapid screening of closely related strains. With this polyphasic approach, in addition to the ten described Shewanella species, two new species, Shewanella oneidensis and 'Shewanella pealeana', were recognized; Shewanella oneidensis sp. nov. is described here for the first time.

NASA Discipline Exobiology↗

NASA NTRS1983

Laboratory studies at high resolution of the infrared absorption spectra of a number of gases found in planetary atmospheres

The infrared absorption spectra of a number of gases found in planetary atmospheres were studied at high resolution. Absorption line measurements which can be of value for the interpretation of planetary spectra in terms of molecular abundances and conditions in the planetary atmospheres were provided. The high resolution spectra have yielded measurements of individual vibration rotation line parameters including positions, strengths, pressure broadened widths and, where assignments were unknown, the temperature sensitivity of the strengths. Such information allows the determinations of the absorption of a given molecular gas under planetary conditions of temperature and pressure and at the same time it provides the data necessary if the spectra are to be understood in terms of basic molecular theory. Thus this work has included spectral analysis in the form of line assignments as well as fitting of the data to Hamiltonian models. Such fitting is very useful in that it helps to confirm and extend the assignments.

Hunt, R. H.↗

NASA NTRS2013

Modeling Contamination Migration on the Chandra X-ray Observatory II

During its first 14 years of operation, the cold (about ‐60degC) optical blocking filter of the Advanced CCD Imaging Spectrometer (ACIS), aboard the Chandra X‐ray Observatory, has accumulated a growing layer of molecular contamination that attenuates low‐energy x rays. Over the past few years, the accumulation rate, spatial distribution, and composition may have changed, perhaps partially related to changes in the operating temperature of the ACIS housing. This evolution of the accumulation of the molecular contamination has motivated further analysis of contamination migration on the Chandra X‐ray Observatory, particularly within and near the ACIS cavity. To this end, the current study employs a higher‐fidelity geometric model of the ACIS cavity, detailed thermal modeling based upon monitored temperature data, and an accordingly refined model of the molecular transport.

O'Dell, Stephen L.↗

NASA NTRS2013

Modeling Contamination Migration on the Chandra X-ray Observatory II

O'Dell, Steve↗