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At least 1,009 records · Page 56

Compatibility of seasonal variations in mid-latitude thermospheric models at solar maximum and low geomagnetic activity

Satellite drag data, in situ mass spectrometer data, Fabry Perot interferometer data, and incoherent scatter data were used to produce models of the concentration of atomic oxygen and molecular nitrogen in the thermosphere and of the exospheric temperature. Incoherent scatter data from two stations near 45 deg N were used. The three techniques provide similar patterns for the annual variations of the atomic oxygen concentration at 400 km, and the mean annual temperatures are within 20 K of each other for five of the six models involved. Four of the models are in good agreement concerning the annual temperature variation. There is fair agreement between incoherent scatter models and mass spectrometer models for the N2 concentrations at 400 km but disagreement between these models and the satellite drag model. It is shown that most disagreements can be resolved by changing both the vertical temperature profile and the lower-thermosphere oxygen concentration in the direction indicated by previous incoherent scatter measurements.

Alcayde, D.↗

Spatial variation of the physical conditions of molecular gas in galaxies

Multi-line studies of CO-12, CO-13, C-18O, HCN, and HCO(+) at 3 mm, 1.3 mm, and 0.8 mm using the Institute for Radio Astronomy in the Millimeter range (IRAM) 30 m telescope, with the IRAM superconductor insulator superconductor (SIS) receivers and the Max Planck Institute for External Physics (MPE) 350 GHz SIS receiver, show that the densities and temperatures of molecular gas in external galaxies change significantly with position. CO-12 measures the densities and temperature of diffuse interclump molecular gas, but not the bulk of the molecular gas. Simple one-component models, with or without external heating, cannot account for the weakness of the CO-12 J = 3 to 2 line relative to J = 2 to 1 and J = 1 to 0. CO-12 does not trace the bulk of the molecular gas, and optical depth effects obviate a straightforward interpretation of CO-12 data. Instead, researchers turned to the optically thin CO isotopes and other molecular species. Isotopic CO lines measure the bulk of the molecular gas, and HCN and HCO(+) pick out denser regions. Researchers find a warm ridge of gas in IC 342 (Eckart et al. 1989), denser gas in the starburst nucleus of IC 342, and a possible hot-spot in NGC 2903. In IC 342, NGC 2146, and NGC 6764, the CO-13 J = 2 to 1 line is subthermally populated, implying gas densities less than or equal to 10(exp 4) cm(-3).

Jackson, James M.↗

Surface, Water, and Air Biocharacterization (SWAB) Flight Experiment

The determination of risk from infectious disease during spaceflight missions is composed of several factors including both the concentration and characteristics of the microorganisms to which the crew are exposed. Thus, having a good understanding of the microbial ecology aboard spacecraft provides the necessary information to mitigate health risks to the crew. While preventive measures are taken to minimize the presence of pathogens on spacecraft, medically significant organisms have been isolated from both the Mir and International Space Station (ISS). Historically, the method for isolation and identification of microorganisms from spacecraft environmental samples depended upon their growth on culture media. Unfortunately, only a fraction of the organisms may grow on a specific culture medium, potentially omitting those microorganisms whose nutritional and physical requirements for growth are not met. To address this bias in our understanding of the ISS environment, the Surface, Water, and Air Biocharacterization (SWAB) Flight Experiment was designed to investigate and develop monitoring technology to provide better microbial characterization. For the SWAB flight experiment, we hypothesized that environmental analysis using non-culture-based technologies would reveal microorganisms, allergens, and microbial toxins not previously reported in spacecraft, allowing for a more complete health assessment. Key findings during this experiment included: a) Generally, advanced molecular techniques were able to reveal a few organisms not recovered using culture-based methods; however, there is no indication that current monitoring is "missing" any medically significant bacteria or fungi. b) Molecular techniques have tremendous potential for microbial monitoring, however, sample preparation and data analysis present challenges for spaceflight hardware. c) Analytical results indicate that some molecular techniques, such as denaturing gradient gel electrophoresis (DGGE), can be much less sensitive than culture-based methods. d) More sensitive molecular techniques, such as quantitative polymerase chain reaction (QPCR), were able to identify viral DNA from ISS environments, suggesting potential transfer of the organism between crewmembers. In addition, the hardware selected for this experiment represented advances for next-generation sample collection. The advanced nature of this collection hardware was noted, when the Sartorius MD8 Air Port air sampler from the SWAB experiment remained on board ISS at the request of JAXA investigators, who intend to use it in completion of their microbial ecology experiment.

Castro, V. A.↗

Infrared Extinction and the Initial Conditions for Star and Planet Formation

This grant funded a research program to use infrared extinction measurements to probe the detailed structure of dark molecular clouds and investigate the physical conditions which give rise to star and planet formation. The goals of the this program were to: 1) acquire deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds, 2) reduce and analyze the data obtained in order to produce detailed extinction maps of the clouds, 3) use the results to measure and quantitatively describe the physical conditions of the dense gas and dust that produce stars and their accompanying planetary systems in molecular clouds. The goals of this project were met and exceeded as described below. 1) The infrared data for the project were obtained in a number of observing runs using the 3.5-meter NTT and 8-meter VLT telescopes of the European Southern Observatory in Chile and the 1.2-meter telescope of the Smithsonian Astrophysical Observatory in Arizona, the 1 0-meter Keck telescope in Hawaii, the 6.5-meter MMT of the Smithsonian Astrophysical Observatory in Arizona, and the NASA Hubble Space Telescope. The molecular-line data was obtained in three runs using the IRAM 30-meter telescope in Spain and one run with the ESO-15 meter millimeter-wave telescope in Chile. Millimeter-wave continuum measurements were obtained with the 15-meter JCMT in Hawaii. 2) Considerable effort was expended to reduce the infrared imaging observations including the development of custom software to produce high quality photometry and source astrometry. All the millimeter-line data was reduced using standard reduction routines. The highlights of the infrared analysis were the production of detailed extinction maps and the construction of profiles of the density structure of the B68, Coalsack, B335 and Lupus clouds. 3) The principal scientific accomplishments of this research program include the following: We were able to use our infrared observations to determine the density structure of the B68 cloud to an unprecedented level of precision. This lead to a major breakthrough in the study of molecular cloud structure. For the first time we have been able to characterize the structure of a dark cloud in a detail only exceeded by that known for a star. We determined that the cloud's structure is exquisitely well described by the equations of a Bonner-Ebert sphere (a pressure confined isothermal sphere). We were able to show that the cloud is very nearly in equilibrium with the internal thermal pressure of the cloud balancing gravity and the external pressure of the surrounding interstellar medium. We were able to determine for the first time the gas-to-dust ratio in a dense cloud core. We also demonstrated a new method to determine extremely precise distances to such clouds by combining knowledge of the properties of Bonner-Ebert Spheres with our infrared and millimeter-wave observations.

Lada, Charles J.↗

Modeling Contamination Migration on the Chandra X-ray Observatory - II

During its first 14 years of operation, the cold (about -60C) 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 have changed. This evolution has motivated further analysis of contamination migration 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 temperature data, and a refined model of the molecular transport.

O'Dell, Stephen L.↗

Analysis of ultraviolet spectrophotometric data from Copernicus

Ultraviolet spectral data from the OAO 3 satellite are being used to study interstellar absorption lines and stellar and circumstellar lines in hot stars. The interstellar data are beneficial in analyzing the depletions of heavy elements from the gas phase and in elucidating how these depletions depend on physical conditions. Abundances in separate velocity components were determined from line profiles. Observations were carried out for interstellar abundances, both atomic and molecular, towards a number of stars. The better quality data are being analyzed for profile information and the lesser data are being used in curve-of-growth analyses. Molecular observations were carried out as well, N2 was sought; interstellar C2 was detected and its rotational excitation utilized to establish limits in interstellar cloud temperatures. An extensive search for H2O resulted in a tentative identification which will produce new information on chemical reaction rates. Interstellar depletions and grain properties in the rho Ophiuchi cloud, stellar wind variability, and circumstellar lines are also under study.

Snow, T. P., Jr.↗

Machine learning prediction of glass transition temperature of conjugated polymers from chemical structure

Predicting the glass transition temperature (T g ) is of critical importance as it governs the thermomechanical performance of conjugated polymers (CPs). Here, we report a predictive modeling framework to predict T g of CPs through the integration of machine learning (ML), molecular dynamics (MD) simulations, and experiments. With 154 T g data collected, an ML model is developed by taking simplified “geometry” of six chemical building blocks as molecular features, where side-chain fraction, isolated rings, fused rings, and bridged rings features are identified as the dominant ones for T g . MD simulations further unravel the fundamental roles of those chemical building blocks in dynamical heterogeneity and local mobility of CPs at a molecular level. The developed ML model is demonstrated for its capability of predicting T g of several new high-performance solar cell materials to a good approximation. The established predictive framework facilitates the design and prediction of T g of complex CPs, paving the way for addressing device stability issues that have hampered the field from developing stable organic electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two datasets are better than one: method of double moments for 3D reconstruction in cryo-EM

Cryo-electron microscopy is a powerful imaging technique for reconstructing three-dimensional molecular structures from noisy tomographic projection images of randomly oriented particles. We introduce a new data fusion framework, termed the method of double moments, which reconstructs molecular structures from two instances of the second-order moment of projection images obtained under distinct orientation distributions: one uniform, the other non-uniform and unknown. We prove that these moments generically uniquely determine the underlying structure, up to a global rotation and reflection, and we develop a convex-relaxation-based algorithm that achieves accurate recovery using only second-order statistics. Our results demonstrate the advantage of collecting and modeling multiple datasets under different experimental conditions, illustrating that leveraging dataset diversity can substantially enhance reconstruction quality in computational imaging tasks.

Kam’s method↗

A new method for measuring the 3D turbulent velocity dispersion of molecular clouds

ABSTRACT The structure and star formation activity of a molecular cloud are fundamentally linked to its internal turbulence. However, accurately measuring the turbulent velocity dispersion is challenging due to projection effects and observational limitations, such as telescope resolution, particularly for clouds that include non-turbulent motions, such as large-scale rotation. Here, we develop a new method to recover the 3D turbulent velocity dispersion (σv,3D) from position–position–velocity (PPV) data. We simulate a rotating, turbulent, collapsing molecular cloud, and compare its intrinsic σv,3D with three different measures of the velocity dispersion accessible in PPV space: (1) the spatial mean of the 2nd-moment map, σi, (2) the standard deviation of the gradient/rotation-corrected 1st-moment map, σ(c − grad), and (3) a combination of (1) and (2), called the ‘gradient-corrected parent velocity dispersion’, $\sigma _{\mathrm{(p}-\mathrm{grad)}}=(\sigma _{\mathrm{i}}^2+\sigma _{(\mathrm{c}-\mathrm{grad)}}^2)^{1/2}$. We show that the gradient correction is crucial in order to recover purely turbulent motions of the cloud, independent of the orientation of the cloud with respect to the line of sight. We find that with a suitable correction factor and appropriate filters applied to the moment maps, all three statistics can be used to recover σv,3D, with method 3 being the most robust and reliable. We determine the correction factor as a function of the telescope beam size for different levels of cloud rotation, and find that for a beam full width at half-maximum f and cloud radius R, the 3D turbulent velocity dispersion can best be recovered from the gradient-corrected parent velocity dispersion via $\sigma _{v,\mathrm{3D}}= \left[(-0.29\pm 0.26)\, f/R + 1.93 \pm 0.15\right] \sigma _{\mathrm{(p}-\mathrm{grad)}}$ for f/R < 1, independent of the level of cloud rotation or LOS orientation.

Stewart, Madeleine↗

Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders

The molecular composition of the excitatory synapse is incompletely defined due to its dynamic nature across developmental stages and neuronal populations. To address this gap, we apply proteomic mass spectrometry to characterize the synapse in multiple biological models including the fetal human brain and hiPSC-derived neurons. To prioritize the identified proteins, we develop an orthogonal multi-omic screen of genomic, transcriptomic, interactomic, and structural data. This data-driven framework identifies proteins with key molecular features intrinsic to the synapse, including characteristic patterns of biophysical interactions and cross-tissue expression. The multi-omic analysis captures synaptic proteins across developmental stages and experimental systems, including 493 synaptic candidates supported by proteomics. We further investigate three such proteins that are associated with neurodevelopmental disorders – the CUL3 E3 ubiquitin ligase, the DDX3X and YBX1 nucleic-acid binding proteins – by mapping their networks of physically interacting synapse proteins or transcripts. Our study demonstrates the potential of an integrated multi-omic approach to systematically and more comprehensively resolve the synaptic architecture.

59 BASIC BIOLOGICAL SCIENCES↗

High velocity molecular emission in Orion - A case for stellar winds

On the basis of data from the literature and observations of both a variety of molecules in the high-velocity source of the Orion molecular cloud and high-velocity emissions in other molecular clouds, it is proposed that the high-velocity source consists of clumps of dense molecular gas which are accelerated by the high-velocity stellar wind of a pre-main sequence star. Some of the H2O maser emissions, and the H2 and Herbig-Haro-type emissions, are attributed to shocks associated with the breakup of the protostellar cocoon.

Kuiper, T. B. H.↗

Chemical Diversity of Oligomers in Biomass Fast Pyrolysis Oils, Part 2: Heavy Lignin-Derived Molecules and Highly Dehydrated Sugars from Dichloromethane-Insoluble Pyrolytic Lignin

Here, this paper, the second in a series, investigates the water-insoluble, dichloromethane (DCM)-insoluble residue of BTG pyrolysis oil, also known in the literature as high-molecular-weight pyrolytic lignin (HMW-PL). HMW-PL accounts for 9.2 wt % of the original bio-oil, which is known to increase upon aging and contribute to coke formation during bio-oil upgrading. Understanding its composition is crucial for managing pyrolysis oil during the processing. The HMW-PL was fractionated using a silica gel column with solvents of increasing polarity: ethyl acetate (EA), acetone (AC), isopropanol (ISO), and methanol (MeOH), yielding 49.2, 19.9, 8.2, and 8.1 wt %, respectively. Each subfraction was characterized by UV-fluorescence, FTIR, HSQC NMR, and (−)APCI-FT-Orbitrap MS. Analysis revealed that the EA subfraction primarily contained aromatic dimers (C 19 –C 20 ) and trimers (C 17 –C 13 ), while the MeOH subfraction was rich in oxygenated aliphatic monomers (C 8 –C 16 ) likely derived from sugar dehydration products. The resulting fractions were further separated via preparatory HPLC. Fifty-five candidate molecular structures were proposed based on the Orbitrap MS data, supported by UV-fluorescence, FTIR, and NMR results. This fractionation strategy defined four distinct subfractions, enabling the proposal of surrogate molecular structures and advancing the molecular-level understanding of the HMW-PL fraction in the pyrolysis bio-oil.

High-Molecular-Weight PL↗

Implementing a neural network interatomic model with performance portability for emerging exascale architectures

The two main thrusts of computational science are increasingly accurate predictions and faster calculations; to this end, the zeitgeist in molecular dynamics (MD) simulations is pursuing machine learned and data driven interatomic models, e.g. neural network potentials, and novel hardware architectures, e.g. GPUs. Current implementations of neural network potentials are orders of magnitude slower than traditional interatomic models and while looming exascale computing offers the ability to run large, accurate simulations with these models, achieving portable performance for MD with new and varied exascale hardware requires rethinking traditional algorithms, using novel data structures, and library solutions. We re-implement a neural network interatomic model in CabanaMD, an MD proxy application, built on libraries developed for performance portability. Our implementation shows significantly improved thread scaling in this complex kernel as compared to a current LAMMPS implementation, across both strong and weak scaling. Our single-source solution enables simulations up to 20 million atoms on a single CPU node and 4 million atoms with improved performance on a single GPU. Furthermore, we also explore parallelism and data layout choices (using flexible data structures called AoSoAs) and their effect on performance, seeing up to ~50% and ~5% improvements in performance on a GPU by choosing the right level of parallelism and data layout respectively.

97 MATHEMATICS AND COMPUTING↗

High-Resolution Temperature-Dependent Photoabsorption Cross Section Measurements of S2, with Application to HST UV Spectra of SL9/Jupiter

The Hubble Space Telescope (HST) UV spectra of Jupiter after the collision of Comet SL9 show predominantly molecular features of S2, CS2, NH3, and H2S in the 1800-3200 A region. The HST observations were made under various phases of impact conditions which gave temperatures higher than 1000 K. It is thus clear that temperature-dependent laboratory cross section data are required in order to determine the molecular abundances in Jupiter's atmosphere after the impact of Comet Shoemaker-Levy 9. The required high-resolution temperature dependent S2 absorption cross sections have not been directly measured in the laboratory. To provide the required data for modelers our objective is to accurately measure the high-resolution (FWHM = 0.003 A) and medium resolution (FWHM - 0.08 A) temperature dependent S2 in the 2450-3200 A region. Using the experimental setup we have obtained absorbtion spectra of S2 under various temperature conditions.

Wu, C. Y. Robert↗

ORNL_AISD_NiPt_108atoms

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 crystal structures with 108 atoms with 1,900 configurations. 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 a compressed zipped folders atoms108.zip. The zipped folder 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 atoms108.zip is 66,132. This dataset is an extension to the dataset ORNL_AISD_NiPt [5] that has been previously released with crystal structures of 256 atoms, 864 atoms, and 2,048 atoms, with the same methodology for data collection. 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 Büchner, 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 [5] M. Karabin, M. Lupo Pasini, and M. Eisenbach. ORNL_AISD_NiPt. United States: N. p., 2023. Web. doi:10.13139/OLCF/1958172.

36 MATERIALS SCIENCE↗

Data and scripts associated with “Non-random processes impacting organic matter chemistry are maximized in mid-order streams”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Non-random processes impacting organic matter chemistry are maximized in mid-order streams” submitted to Limnology and Oceanography (L&O) by Danczak et al. (in review). This package contains data and scripts used to investigate dissolved organic matter (DOM) molecular chemistry and diversification processes across 47 surface-water sampling sites in the Yakima River Basin, Washington, USA, during an August 2021 sampling campaign. The package contains analyses of ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), geochemical measurements, geospatial attributes, molecular diversity, and meta-metabolome ecological null models needed to reproduce the main manuscript results. The underlying field data were pulled from exising data packages at https://doi.org/10.15485/1892052 (Fulton et al., 2022) and https://doi.org/10.15485/1898914 (Grieger et al., 2022). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. We thank the following organizations for providing access to field locations for sample collection: the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, the Confederated Tribes and Bands of the Yakama Nation, and the Cowiche Canyon Conservatory. Research was conducted under Washington State Parks and Recreation Commission Scientific Research Permit #210901. We are grateful to the Yakama Nation Tribal Council and Yakama Nation Fisheries for their collaboration in facilitating sample collection and ensuring data usage aligns with their values and worldview. This data package contains an R-Markdown file for analyses and five folders: (1) Data, (2) Geospatial Data, (3) Supplemental_Files, (5) Figures_pdf, (4) and src. The Data folder contains tabular inputs and derived files used in the manuscript analysis. The Geospatial Data folder contains climate and water-balance, hydrologic, land-cover, population/regional water-use, stream, topographic, and stream-order attribute CSV files. The src folder contains scripts used to process data, run analyses, and generate figures. The Figures_pdf folder contains manuscript figure outputs. The Supplemental_Files folder contains supplemental analysis products. All files are .csv, .pdf, .html, .png, .R, .Rmd, .svg, or .tre. This data package is associated with the rcfsa-RC2-SPS_Null_Modeling repository found at https://github.com/river-corridors-sfa/rcfsa-RC2-SPS_Null_Modeling.

54 ENVIRONMENTAL SCIENCES↗

20 to 40 micron spectroscopy of the Orion Nebula

Attention is given to a moderate-resolution spectra of the Orion Nebula. Observational data are presented between 20 and 40 microns. Several models are shown that attempt to account for all of the observations from 20 microns to 1 mm. A model in which the dust within the molecular cloud has a clumpy distribution is given. Data show that the individual clumps have effective grain temperatures of 100 deg K and they are optically thick for wavelengths shorter than 400 microns.-

Houck, J. R.↗

Enabling robust offline active learning for machine learning potentials using simple physics-based priors

Abstract Machine learning surrogate models for quantum mechanical simulations have enabled the field to efficiently and accurately study material and molecular systems. Developed models typically rely on a substantial amount of data to make reliable predictions of the potential energy landscape or careful active learning (AL) and uncertainty estimates. When starting with small datasets, convergence of AL approaches is a major outstanding challenge which has limited most demonstrations to online AL. In this work we demonstrate a Δ-machine learning (ML) approach that enables stable convergence in offline AL strategies by avoiding unphysical configurations with initial datasets as little as a single data point. We demonstrate our framework’s capabilities on a structural relaxation, transition state calculation, and molecular dynamics simulation, with the number of first principle calculations being cut down anywhere from 70%–90%. The approach is incorporated and developed alongside AMP torch , an open-source ML potential package, along with interactive Google Colab notebook examples.

Shuaibi, Muhammed↗