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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Preparation of Actinide Targets at Oregon State University

In this paper, we describe the preparation of actinide targets at Oregon State University. The preparation of the actinide fluorides is done by an aqueous precipitation procedure with yields of greater than 90%. A dual glove box system is used for the preparation of the fluorides of the high specific activity actinides and the subsequent vapor deposition. We compare and contrast targets made by vapor deposition and molecular plating. We discuss some new data on the structure of actinide targets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as “omics”) data allow researchers to find biomarkers or molecular targets, or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data is multi-dimensional and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries don’t allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to effortlessly sort and filter plots by categorical or numerical variables. MODE allows users to build and share these displays with several options for plot design and meta selection. In conclusion, the MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

lipidomics↗
DOE OSTI2025

Iodine recombination in xenon solvent: Clusters in the gas to liquid-like state transition

Supercritical fluids (SCFs) have attracted significant attention as solvents for chemical reactions due to their unique properties, such as high diffusivity, low viscosity, and tunable solvation properties. These properties profoundly influence reaction kinetics and are often attributed to the formation of molecular clusters within SCFs. To study the effect of supercritical solvent on chemical reactivity and dynamics of reactions, one needs to understand the dynamics of clusters in supercritical fluid. Extensive experiments on the photodissociation and recombination of iodine in supercritical fluids served as a model system for understanding these effects. Experimental studies have been complemented by theoretical and computational investigations, which mostly employ Monte Carlo or empirical molecular dynamics simulations. However, computational studies using non-reactive force fields and ab initio approaches present challenges in capturing reactive processes at larger scales within supercritical fluids. Here, in this work, we developed the ReaxFF parameters by training against quantum mechanics data. ReaxFF reactive force field based molecular dynamics simulations were performed, studying the dynamics of a xenon solvent and cage effect at different thermodynamic conditions for the iodine recombination reaction. We show that the conditions near the critical point are the optimal conditions to study the cage effect. We show that the average lifetime of xenon clusters ranging between 5 and 11 ps is comparable to iodine geminate recombination. Our simulation results of iodine recombination in xenon solvent demonstrate the higher probability of iodine molecule formation in the presence of xenon clusters. Finally, we show that the supercritical condition exhibits the highest recombination rate for iodine atoms.

Cage effect↗
DOE OSTI2020

PySpawn: Software for Nonadiabatic Quantum Molecular Dynamics

The ab initio multiple spawning (AIMS) method enables nonadiabatic quantum molecular dynamics simulations in an arbitrary number of dimensions, with potential energy surfaces provided by electronic structure calculations performed on-the-fly. However, the intricacy of the AIMS algorithm complicates software development, deployment on modern shared computer resources, and post-simulation data analysis. PySpawn is a nonadiabatic molecular dynamics software package that addresses these issues. Here, the program is designed to be easily interfaced with electronic structure software, and an interface to the TeraChem software package is described here. PySpawn introduces a task-based reorganization of the AIMS algorithm, allowing fine-grained restart capability and setting the stage for efficient parallelization in a future release. PySpawn includes a user-friendly and interactive Python analysis module that will enable novice users to painlessly adopt AIMS. As a demonstration of PySpawn’s simulation capability and analysis module, we report complete active space self-consistent field–based AIMS simulations of the 1,2- dithienyl-1,2-dicyanoethene molecule, a promising molecular photoswitch.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Decoding the Pair Distribution Function of Uranium in Molten Fluoride Salts from X-Ray Absorption Spectroscopy Data by Machine Learning

Thermal properties of actinides in molten salts are linked to the strongly disordered local environment of actinide ions. Here, we illustrate both the limitations of the commonly used fitting method for analysis of extended X-ray absorption fine structure (EXAFS) spectra in molten UF 4 and a possible solution using an "objective neural network - EXAFS" (ONNE) method. ONNE provides both extraction of the pair distribution function, as validated by its application to the EXAFS spectra calculated on molecular dynamics trajectory, and the EXAFS data reconstruction. The ONNE analysis of the molten UF4 has revealed reduction of the first nearest neighbor U-F coordination number, expansion of the U-F bond length and smaller contribution to the second shell compared to its crystalline counterpart. This method is therefore an attractive alternative to conventional EXAFS analysis and molecular dynamics simulations for studies of disordered environment of actinides in molten salts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1989

Star formation and the interstellar medium in two peculiar, nonspiral galaxies - NGC 1569 and NGC 3593

This paper discusses far-IR and optical observations aimed at investigating the far-IR energy distribution of two peculiar galaxies without spiral arms which are actively forming stars: NGC 1569, a Magellanic irregular galaxy, and NGC 3593, a dusty S0/a galaxy. The data are used to determine the characteristic temperatures of the dust and to infer dust and molecular gas masses which are combined with other data to explore the characteristics of the interstellar media. Visual-wavelength continuum and H-alpha images are presented and used to estimate current and past star formation rates and the efficiency of stellar creation.

Hunter, Deidre A.↗
NASA NTRS1997

An Investigation of the Cold Interstellar Medium of the Outer Galaxy

The primary objective of this proposal was to determine the relationship between the molecular gas and dust components of the interstellar medium of the Outer Galaxy. It made use of the High Resolution IRAS Galaxy Atlas and the FCRAO CO Survey of the Outer Galaxy. These HIRES images greatly augment the spatial dynamic range of the IRAS Survey data and the ability to discriminate multiple point sources within a compact region. Additionally, the HIRES far infrared images allow for more direct comparisons with molecular line data observed at 45 sec resolution. From funding of this proposal, we have completed two papers for publication in a refereed journal.

Heyer, Mark H.↗
NASA NTRSDate not supplied

Analysis of nonequilibrium molecular nitrogen ultraviolet radiation in pure N2 shockwaves

An analysis of data previously reported from a test series in the Electric Arc Shock Tube Facility for incident shocks composed of pure Nitrogen was performed. The present work focuses on the lowest velocity measured in the test (approximately 7 km/s) where molecular radiation is significant. Analysis of the spectral data with the NEQAIR radiative transport code obtains post-shock trends in temperature and number densities of the states of N2. The results suggest that chemical, and possibly thermal, equilibrium has not been obtained within the distance/time measured (about 5 cm/120 ms). In the nonequilibrium region of the shock, differences between rotational temperatures of different species are observed, as well as differences between rotational and vibrational temperatures. Population of rotational states above the dissociation limit is observed to occur over a distance of several cm. Finally, these data suggest that predissociation strongly affects the C^3 Π_u state of N2, leading to a lower measured radiation than predicted. An effective average pre-dissociation rate is shown to produce reasonable agreement under quasi-steady state approximation.

Augustin Tibere-Inglesse↗
NASA NTRS1984

A theoretical model for calculation of molecular stopping power

A modified local plasma model is established. The Gordon-Kim's molecular charged density model is employed to obtain a formula to evaluate the stopping power of many useful molecular systems. The stopping power of H2 and He gas was calculated for incident proton energy ranging from 100 keV to 2.5 MeV. The stopping power of O2, N2, and water vapor was also calculated for incident proton energy ranging from 40 keV. to 2.5 MeV. Good agreement with experimental data was obtained. A discussion of molecular effects leading to department from Bragg's rule is presented. The equipartition rule and the effect of nuclear momentum recoiling in stopping power are also discussed.

Xu, Y. J.↗
DOE OSTI2021

CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method

Background: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. Results: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. Conclusion: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1989

Far-infrared emission in the Rho Ophiuchi region - A comparison with molecular gas emission and visual extinction

The dust characteristics of a 40 arcmin x 40 arcmin section of the Rho Ophiuchi molecular clouds complex revealed by the IRAS satellite are compared with both molecular line and deep star count data for the region. The data reveal the cloud to be clearly visible at 12 and 25 microns, as well as at 60 and 100 microns. Modeling the infrared emission from the cloud as being due to two populations of dust grains, the short-wavelength emission is found not to reflect the internal structure of the molecular cloud. The 60 micron opacity determined using a single grain emission model correlates reasonably well with (C-13)O column density and visual extinction up to roughly 5 mag. The cloud edges appear to be heated by the interstellar radiation field. The far-infrared luminosity to mass ratio for the region is determined to be 0.9 solar luminosity/solar mass, a value much smaller than the average ratio for the inner Galaxy.

Jarrett, T. H.↗
NASA NTRS1977

The galactic distribution (in radius and Z) of interstellar molecular hydrogen

Observations of the galactic longitude and latitude distributions of lambda = 2.6 mm CO emission are presented. Analysis of these spectral-line data yields the large-scale distribution of molecular clouds in the galactic disk and their z-distribution out of the disk. Strong maxima in the number of molecular clouds occur in the galactic nucleus and at galactic radii 4 to 8 kpc. The peak at 4 to 8 kpc correlates well with a region of enhanced 100-MeV gamma-ray emissivity. This correlation strongly supports the conclusion that the gamma-rays are produced as a result of cosmic ray interactions in molecular H2 clouds rather than in H(I). The width of the cloud layer perpendicular to the galactic plane between half-density points is 105 plus or minus 15 pc near the 5.5-kpc peak. The total mass of molecular gas in the interior of the galaxy exceeds that of atomic hydrogen and is 30 to the 9th power solar mass based on these observations.

Scoville, N. Z.↗
DOE OSTI2025

When more data hurts: Optimizing data coverage while mitigating diversity-induced underfitting in an ultrafast machine-learned potential

Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parametrize the MLIPs remains a significant challenge. This is because MLIPs can fail when encountering local environments too different from those present in the training data. The difficulty of determining a priori the environments that will be encountered during molecular dynamics simulation necessitates diverse, high-quality training data. Here, this study investigates how training data diversity affects the performance of MLIPs using the Ultra-Fast force field (UF 3 ) to model amorphous silicon nitride. We employ expert and autonomously generated data to create the training data and fit four force field variants to subsets of the data. Our findings reveal a critical balance in training data diversity: insufficient diversity hinders generalization, while excessive diversity can exceed the MLIP's learning capacity, reducing simulation accuracy. Specifically, we found that the UF 3 variant trained on a subset of the training data, in which nitrogen-rich structures were removed, offered vastly better prediction and simulation accuracy than any other variant. By comparing these UF 3 variants, we highlight the nuanced requirements for creating accurate MLIPs, emphasizing the importance of application-specific training data to achieve optimal performance in modeling complex material behaviors.

ab initio molecular dynamics↗
DOE OSTI2023

Computational optimal transport for molecular spectra: The fully continuous case

Computational optimal transport is used to analyze the difference between pairs of continuous molecular spectra. It is demonstrated that transport distances which are derived from this approach may be a more appropriate measure of the difference between two continuous spectra than more familiar measures of distance under many common circumstances. Associated with the transport distances is the transport map which provides a detailed analysis of the difference between two molecular spectra and is a key component of our study of quantitative differences between two continuous spectra. The use of optimal transport for comparing molecular spectra is developed in detail here with a set of model spectra, so that the discussion is self-contained. The difference between the transport distance and more common definitions of distance is elucidated for some well-chosen examples and it is shown where transport distances may be very useful alternatives to standard definitions of distance. The transport distance between a theoretical and experimental electronic absorption spectrum for SO 2 is studied and it is shown how the theoretical spectrum can be modified to fit the experimental spectrum better adjusting the theoretical band origin and the resolution of the theoretical spectrum. In conclusion, this analysis includes the calculation of transport maps between the theoretical and experimental spectra suggesting future applications of the methodology.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

FiXR : a framework to reconstruct fiber cross-sections from X-ray fiber diffraction experiments

Ab initio reconstruction methods have revolutionized the capabilities of small-angle X-ray scattering (SAXS), allowing the data-driven discovery of previously unknown molecular conformations, exploiting optimization heuristics and assumptions behind the composition of globular molecules. While these methods have been successful for the analysis of small particles, their impact on fibrillar assemblies has been more limited. The micrometre-range size of these assemblies and the complex interaction of their periodicities in their scattering profiles indicate that the discovery of fibril structures from SAXS measurements requires novel approaches beyond extending existing tools for molecular discovery. In this work, it is proposed to use SAXS measurements, together with diffraction theory, to infer the electron distribution of the average cross-section of a fiber. This cross-section is modeled as a discrete electron density with continuous support, allowing representations beyond binary distributions. Additional constraints, such as non-negativity or smoothness/connectedness, can also be added to the framework. The proposed approach is tested using simulated SAXS data from amyloid β fibril models and using measured data of Tobacco mosaic virus from SAXS experiments, recovering the geometry and density of the cross-sections in all cases. The approach is further tested by analyzing SAXS data from different amyloid β fibril assemblies, with results that are in agreement with previously proposed models from cryo-EM measurements. The limitations of the proposed method, together with an analysis of the robustness of the method and the combination with different experimental sources, are also discussed.

Biochemistry & Molecular Biology↗
DOE OSTI2026

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture

Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological processes in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. Results Herein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method, and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. Conclusions The 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visualization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

3D Genome Browser↗
DOE OSTI2025

Assessing the Impact of Measurement Precision on Metabolite Identification Probability in Multidimensional Mass Spectrometry-Based, Reference-Free Metabolomics

Identification of compounds with minimal ambiguity remains a central challenge in mass spectrometry-based metabolomics. Conventional compound identification relies on comparing analytical signatures (e.g., mass-to-charge ratio, collision cross section, tandem mass spectra) against reference data obtained from measurements of authentic chemical standards. The breadth of annotatable compounds using this approach is necessarily limited by availability of authentic standards, analytical throughput, and resolving power of the separations that underly the measurements. The maturation of computational methods, both theory-driven and artificial intelligence/machine learning-based, for prediction of various molecular properties relevant to multidimensional mass spectrometry measurements has opened the door to a new “reference-free” paradigm of compound annotation. Through augmenting existing reference data for molecular properties with computational predictions, the universe of identifiable chemical species can be expanded significantly beyond its current limits. An unexplored aspect of this novel approach is understanding how to gauge confidence in resulting annotations, especially as the compound search space is expanded. Intuitively, the confidence of a compound annotation is related to the inherent discriminatory power of the molecular properties used for identification, as well as the precision with which the properties are measured or predicted. In this work, we characterize this relationship between measurement precision and identification probability in a systematic and quantitative fashion for a defined region of chemical space that includes organic small molecule metabolites. Importantly, this work establishes a framework for conducting metabolite identification probability analysis that enables others to quantify this relationship for their own compounds and properties of interest.

Metabolite Identification↗
NASA NTRS1985

Spectral identification/elimination of molecular species in spacecraft glow

Computer models of molecular electronic and vibrational emission intensities were developed. Known radiative emission rates (Einstein coefficients) permit the determination of relative excited state densities from spectral intensities. These codes were applied to the published spectra of glow above shuttle surface and to the Spacelab 1 results of Torr and Torr. The theoretical high-resolution spectra were convolved with the appropriate instrumental slit functions to allow accurate comparison with data. The published spacelab spectrum is complex but N2+ Meinel emission can be clearly identified in the ram spectrum. M2 First Positive emission does not correlate well with observed features, nor does the CN Red System. Spectral overlay comparisons are presented. The spectrum of glow above shuttle surfaces, in contrast to the ISO data, is not highly structured. Diatomic molecular emission was matched to the observed spectral shape. Source excitation mechanisms such as (oxygen atom)-(surface species) reaction product chemiluminescence, surface recombination, or resonance fluorescent re-emission will be discussed for each tentative assignment. These assignments are the necessary first analytical step toward mechanism identification. Different glow mechanisms will occur above surfaces under different orbital conditions.

Green, B. D.↗