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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Effect of molecular weight on polyphenylquinoxaline properties

A series of polyphenyl quinoxalines with different molecular weight and end-groups were prepared by varying monomer stoichiometry. Thus, 4,4'-oxydibenzil and 3,3'-diaminobenzidine were reacted in a 50/50 mixture of m-cresol and xylenes. Reaction concentration, temperature, and stir rate were studied and found to have an effect on polymer properties. Number and weight average molecular weights were determined and correlated well with viscosity data. Glass transition temperatures were determined and found to vary with molecular weight and end-groups. Mechanical properties of films from polymers with different molecular weights were essentially identical at room temperature but showed significant differences at 232 C. Diamine terminated polymers were found to be much less thermooxidatively stable than benzil terminated polymers when aged at 316 C even though dynamic thermogravimetric analysis revealed only slight differences. Lower molecular weight polymers exhibited better processability than higher molecular weight polymers.

Jensen, Brian J.↗
NASA NTRS1991

A 99 percent purity molecular sieve oxygen generator

Molecular sieve oxygen generating systems (MSOGS) have become the accepted method for the production of breathable oxygen on military aircraft. These systems separate oxygen for aircraft engine bleed air by application of pressure swing adsorption (PSA) technology. Oxygen is concentrated by preferential adsorption in nitrogen in a zeolite molecular sieve. However, the inability of current zeolite molecular sieves to discriminate between oxygen and argon results in an oxygen purity limitations of 93-95 percent (both oxygen and argon concentrate). The goal was to develop a new PSA process capable of exceeding the present oxygen purity limitations. A novel molecular sieve oxygen concentrator was developed which is capable of generating oxygen concentrations of up to 99.7 percent directly from air. The process is comprised of four absorbent beds, two containing a zeolite molecular sieve and two containing a carbon molecular sieve. This new process may find use in aircraft and medical breathing systems, and industrial air separation systems. The commercial potential of the process is currently being evaluated.

Miller, G. W.↗
NASA NTRS1992

The molecular interstellar medium in two giant H II regions in M33 - NGC 604 and NGC 595

This study reports single-dish and interferometric CO observations for the two largest H II regions in M33, NGC 604, and NGC 595. Six individual molecular clouds are identified in the H II regions. Molecular and virial masses for three resolved clouds in NGC 604 agree very well, from which it is inferred that the CO-to-H2 conversion factor in this region is the same as it is in the inner disk of M33 and in the Galaxy, despite a metallicity in NGC 604 that is three times below solar. The total gas mass of the molecular complex associated with NGC 604 estimated from single-dish data is dissimilar to those of molecular complexes in the inner disk of M33, while the molecular gas mass of NGC 505 is roughly an order or magnitude smaller. Both regions contain a large mass fraction of atomic hydrogen, which suggests that photodissociation of molecular hydrogen is an important process in these energetic H II regions.

Wilson, Christine D.↗
NASA NTRS1993

The molecular matching problem

Molecular chemistry contains many difficult optimization problems that have begun to attract the attention of optimizers in the Operations Research community. Problems including protein folding, molecular conformation, molecular similarity, and molecular matching have been addressed. Minimum energy conformations for simple molecular structures such as water clusters, Lennard-Jones microclusters, and short polypeptides have dominated the literature to date. However, a variety of interesting problems exist and we focus here on a molecular structure matching (MSM) problem.

Kincaid, Rex K.↗
NASA NTRS1992

158 micrometers (CII) mapping of the Orion molecular cloud

Data from the inner regions of the Orion nebula in the 157.7409 micrometers (CII) fine structure line is investigated. Large scale strip maps in (CII) across the face of the Orion molecular cloud, and CO spectra at selected positions in the Orion HII region/molecular cloud interface were obtained. The total (CII) luminosity from the Orion molecular cloud is estimated to be approximately 1500 of the solar luminosity or 0.3 of the far infrared luminosity. The overall properties of the Orion molecular cloud deduced are: the photodissociated gas to molecular gas mass fraction, the (CII) line to far infrared continuum intensity ratio and the (CII)/CO(12) (1 to 0) line intensity ratio are the same for the Orion molecular cloud and the nuclei of non-starburst galaxies. The observations provide an important link between (CII) emission from galactic molecular clouds and the nuclei of external galaxies.

Stacey, G. J.↗
NASA NTRS1994

Multiple outflows in the bipolar planetary nebula M1-16: A molecular line study

Extensive observations of the molecular gas in the young, compact planetary nebula M1-16 have been made, using the Swedish-ESO-Submillimeter Telescope. A map of the CO J = 2-1 emission shows that the molecular envelope contains both a slow and a fast outflow with expansion velocities of 19 km/s and greater than 34 km/s, respectively. The slow outflow is mildly elliptical, while the fast molecular outflow is bipolar. This fast outflow is roughly aligned with the very fast outflows recently found in the optical, while the long axis of the slow elliptical outflow is roughly orthogonal to the optical outflow axis. The kinematic timescales for the CO fast outflow and the optical very fast outflow agree closely, supporting the view that the former represents material in the slow outflow accelerated by the very fast outflow. The kinematic signature of a disk expanding with about 15.5 km/s can also be seen in the CO J = 2-1 data. The mass-loss rate (a) for the slow outflow is greater than or equal to 2.8 x 10(exp -5) solar mass/yr and possibly as large as 9 x 10(exp -5) solar mass/yr, (b) for the fast outflow is greater than or equal to 5 x 10(exp -6) solar mass/yr, and (c) for the very fast optically visible outflow is approximately equal 5 x 10(exp -7) solar mass/yr. The disk mass is approximately equal 6 x 10(exp -3) solar mass. Grain photoelectric heating results in temperatures of 20-70 K in molecular gas of the slow outflow. The (13)C/(12)C abundance ratio in M1-16 is found to be 0.33, quite possibly the highest found for any evolved object. Upper limits for the (18)O/(16)O and (17)O/(16)O ratios were found to be consistent with the values found in AGB stars. A search for other molecular species in M1-16 resulted in the detection of the high-excitation species HCN, CN, (13)CN, HCO(+), and H(13)CO(+) and possibly N2H(+). Both the HCO(+)/HCN and CN/HCN line-intensity ratios are enhanced, the former by a very large factor, over the values found in the envelopes of AGB stars, probably as a result of enhancement of the CN and HCO(+) abundances due to photochemistry induced by the stellar UV. The CS J = 2-1, SiO J = 2-1 (v = 0), and SiS J = 6-5 lines were not detected to low levels. For the high-excitation molecules, adequate collisional excitation of rotational levels and survival against photodissociation by the UV radiation requires significant clumping of the molecular gas into clumps with H2 densities approximately 10(exp 5)/cu cm. The IRAS fluxes of M1-16, assuming negligible contribution from line emission, imply the presence of about (1.7-0.4) x 10(exp -3) solar mass of cool dust (temperature around 50 K) and a smaller quantity, (2.7-3.1) x 10(exp -6) solar mass, of warmer dust (temperature around 125 K) for a power-law emissivity index p = 1-2. The evolutionary nature of M1-16 cannot be explained by existing single-star models of post-AGB evolution. The very high (13)C/(12)C abundance ratio in M1-16 suggests a possible evolutionary connection between M1-16 and the rare class of J-type silicate-carbon stars which also have high (13)C/(12)C ratios and are thought to be binary systems with accretion disks.

Sahai, Raghvendra↗
NASA NTRS1997

To-date spacecraft applications and demonstration testing results, and future product development for new molecular adsorber technologies

The use of molecular adsorbers, in order to aid in the reduction of the spacecraft contamination levels, is discussed. Molecular adsorbers are characterized by an extremely large surface area, molecularly-porous substructure, and processing charged sites capable of retaining molecular contaminant species. Molecular adsorbers were applied on two Hubble Space Telescope servicing missions, as well as on the tropical rainfall measuring mission. The use of molecular adsorbers carries the potential for low cost, easy fabrication and integration of reliable means for reducing the contamination level around spacecraft.

Thomson, Shaun↗
NASA NTRS2000

Update on N2O4 Molecular Sieving with 3A Material at NASA/KSC

During its operational life, the Shuttle Program has experienced numerous failures in the Nitrogen Tetroxide (N2O4) portion of Reaction Control System (RCS), many of which were attributed to iron-nitrate contamination. Since the mid-1980's, N2O4 has been processed through a molecular sieve at the N2O4 manufacturer's facility which results in an iron content typically less than 0.5 parts-per-million-by-weight (ppmw). In February 1995, a Tiger Team was formed to attempt to resolve the iron nitrate problem. Eighteen specific actions were recommended as possibly reducing system failures. Those recommended actions include additional N2O4 molecular sieving at the Shuttle launch site. Testing at NASA White Sands Test Facility (WSTF) determined an alternative molecular sieve material could also reduce the water-equivalent content (free water and HNO3) and thereby further reduce the natural production of iron nitrate in N2O4 while stored in iron-alloy storage tanks. Since April '96, NASA Kennedy Space Center (KSC) has been processing N2O4 through the alternative molecular sieve material prior to delivery to Shuttle launch pad N2O4 storage tanks. A new, much larger capacity molecular sieve unit has also been used. This paper will evaluate the effectiveness of N2O4 molecular sieving on a large-scale basis and attempt to determine if the resultant lower-iron and lower-water content N2O4 maintains this new purity level in pad storage tanks and shuttle flight systems.

Davis, Chuck↗
NASA NTRS2004

Workshop on Molecular Evolution

Molecular evolution has become the nexus of many areas of biological research. It both brings together and enriches such areas as biochemistry, molecular biology, microbiology, population genetics, systematics, developmental biology, genomics, bioinformatics, in vitro evolution, and molecular ecology. The Workshop provides an important contribution to these fields in that it promotes interdisciplinary research and interaction, and thus provides a glue that sticks together disparate fields. Due to the wide range of fields addressed by the study of molecular evolution, it is difficult to offer a comprehensive course in a university setting. It is rare for a single institution to maintain expertise in all necessary areas. In contrast, the Workshop is uniquely able to provide necessary breadth and depth by utilizing a large number of faculty with appropriate expertise. Furthermore, the flexible nature of the Workshop allows for rapid adaptation to changes in the dynamic field of molecular evolution. For example, the 2003 Workshop included recently emergent research areas of molecular evolution of development and genomics.

Cummings, Michael P.↗
NASA NTRS2005

Warm Molecular Gas Traced with CO J = 7 --> 6 in the Galaxy's Central 2 Parsecs: Dynamical Heating of the Circumnuclear Disks

We present an 11" resolution map of the central 2 pc of the Galaxy in the CO J = 7 --> 6 rotational transition. The CO emission shows rotation about Sgr A* but also evidence for noncircular turbulent motion and a clumpy morphology. We combine our data set with available CO measurements to model the physical conditions in the disk. We find that the molecular gas in the region is both warm and dense, with T approx. 200-300 K and n(sub H2) approx. (5-7) x 10(exp 4) cm(exp -3). The mass of warm molecular gas we measure in the central 2 pc is at least 2000 M(solar), about 20 times the UV-excited atomic gas mass, ruling out a UV heating scenario for the molecular material. We compare the available spectral tracers with theoretical models and conclude that molecular gas is heated with magnetohydrodynamic shocks with v approx. 10-20 km s(exp -1) and B approx. 0.3- 0.5 mG. Using the conditions derived with the CO analysis, we include the other important coolants, neutral oxygen and molecular hydrogen, to estimate the total cooling budget of the molecular material. We derive a mass-to-luminosity ratio of approx. 2-3 M(solar)(L(solar)exp -1), which is consistent with the total power dissipated via turbulent decay in 0.1 pc cells with v(sub rms) approx. 15 kilometers per second. These size and velocity scales are comparable to the observed clumping scale and the velocity dispersion. At this rate, the material near Sgr A* is dissipating its orbital energy on an orbital timescale and cannot last for more than a few orbits. Our conclusions support a scenario in which the features near Sgr A* such as the circumnuclear disk and northern arm are generated by infalling clouds with low specific angular momentum.

galatic nuclei↗
DOE OSTI2024

Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis

Molecular design is a critical aspect of various scientific and industrial fields, where the properties of molecules hold significant importance. In this study, a 3-fold methodology design is presented that leverages the power of generative artificial intelligence (AI), predictive modeling, and reinforcement learning to create tailored molecules with desired properties. This model synergistically combines deep learning techniques with Self-Referencing Embedded Strings (SELFIES) molecular representation to build a generative model that generates valid molecules and a graphical neural network model that accurately forecasts molecular properties. The Variational Autoencoder (VAE) coupled with reinforcement learning helps refine molecule generation based on targeted attributes. Data from an experimental study involving surfactants were used to test the framework. A validation of the structural integrity of the molecules generated was conducted, and Tanimoto similarities were used to quantify the similarity and diversity between the original and generated molecular structures. Also, saliency maps for the generated surfactants were produced to identify the features explaining the property values. Lastly, molecular dynamics simulations were used to validate the stability of the generated molecules. The results showed that the proposed framework can effectively produce valid molecules within the set property threshold value.

36 MATERIALS SCIENCE↗
DOE OSTI2025

RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design

Inverse molecular design faces significant challenges due to vast chemical space and complex property requirements. While language models show promise for molecular generation, they struggle with validity, multi-property optimization, and structural constraints. This work presents RLMolLM, a reinforcement learning framework combining Proximal Policy Optimization (PPO) with genetic algorithms to address these limitations. Our approach optimizes multiple user-specified properties including quantitative estimates of drug-likeness (QED), synthetic accessibility (SA), and ADMET (absorption, distribution, metabolism, excretion, and toxicity) endpoints without requiring complete model retraining, while maintaining capability for scaffold-constrained generation where specific substructures must be preserved. We outperform state-of-the-art methods for molecular optimization, achieving best QED scores across GDB13, Moses, and Zinc datasets with up to 31% improvement over previous methods while maintaining excellent validity, uniqueness, and novelty metrics. For simultaneous multi-property optimization, our framework achieves substantial improvements in ADMET properties including 4.5-fold reduction in hERG toxicity and enhanced Caco-2 permeability compared to Moses dataset. Under structural constraints, the framework significantly improves molecular validity while preserving scaffolds and effectively optimizing properties. In conclusion, this versatile solution advances pharmaceutical and materials molecular design through effective integration of reinforcement learning and genetic algorithms with multi-property optimization and scaffold preservation.

Genetic algorithms↗
DOE OSTI2024

Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data

Orthogonal separations of data from high-resolution mass spectrometry can provide insight into sample composition and address challenges of complete annotation of molecules in untargeted metabolomics. “Molecular networks” (MNs), as used in the Global Natural Products Social Molecular Networking platform, are a prominent strategy for exploring and visualizing molecular relationships and improving annotation. MNs are mathematical graphs showing the relationships between measured multidimensional data features. MNs also show promise for using network science algorithms to automatically identify targets for annotation candidates and to dereplicate features associated with a single molecular identity. Here, this paper introduces “molecular hypernetworks” (MHNs) as more complex MN models able to natively represent multiway relationships among observations. Compared to MNs, MHNs can more parsimoniously represent the inherent complexity present among groups of observations, initially supporting improved exploratory data analysis and visualization. MHNs also promise to increase confidence in annotation propagation, for both human and analytical processing. We first illustrate MHNs with simple examples, and build them from liquid chromatography- and ion mobility spectrometry-separated MS data. We then describe a method to construct MHNs directly from existing MNs as their “clique reconstructions”, demonstrating their utility by comparing examples of previously published graph-based MNs to their respective MHNs.

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

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Shadow molecular dynamics for flexible multipole models

Shadow molecular dynamics provide an efficient and stable atomistic simulation framework for flexible charge models with long-range electrostatic interactions. Shadow molecular dynamics simulations are driven by approximate “shadow” Born–Oppenheimer potentials for which the exact charges and forces are directly accessible without relying on costly (and approximate) iterative solvers. While previous implementations have been limited to atomic monopole charge distributions, we extend this approach to flexible multipole models. We derive detailed expressions for the shadow energy functions, potentials, and force terms, explicitly incorporating monopole–monopole, dipole–monopole, and dipole–dipole interactions. In our formulation, both atomic monopoles and atomic dipoles are treated as extended dynamical variables alongside the propagation of the nuclear degrees of freedom. We demonstrate that introducing the additional dipole degrees of freedom preserves the stability and accuracy previously seen in monopole-only shadow molecular dynamics simulations. In addition, we present a shadow molecular dynamics scheme where the monopole charges are held fixed while the dipoles remain flexible. Our extended shadow dynamics provide a framework for stable, computationally efficient, and versatile molecular dynamics simulations involving long-range interactions between flexible multipoles. This is of particular current interest in combination with machine-learned interatomic potentials, including long-range electrostatic interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Data Science in Chemical Engineering: Applications to Molecular Science

Chemical engineering is being rapidly transformed by the tools of data science. On the horizon, artificial intelligence (AI) applications will impact a huge swath of our work, ranging from the discovery and design of new molecules to operations and manufacturing and many areas in between. Early adoption of data science, machine learning, and early examples of AI in chemical engineering has been rich with examples of molecular data science—the application tools for molecular discovery and property optimization at the atomic scale. Here, we summarize key advances in this nascent subfield while introducing molecular data science for a broad chemical engineering readership. We introduce the field through the concept of a molecular data science life cycle and discuss relevant aspects of five distinct phases of this process: creation of curated data sets, molecular representations, data-driven property prediction, generation of new molecules, and feasibility and synthesizability considerations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2023

The Mid-Infrared Molecular Inventory Towards Orion IRc2

We present the first high spectral resolution mid-infrared survey in the Orion BN/KL region, covering 7.2 to 28.3μm. With SOFIA/EXES we target the enigmatic source Orion IRc2. While this is in the most prolifically studied massive star-forming region, longer wavelengths and molecular emission lines dominated previous spectral surveys. The mid-infrared observations in this work access different components and molecular species in unprecedented detail. We unambiguously identify two new kinematic components, both chemically rich with multiple molecular absorption lines. The “blue clump” has ν LSR = −7.1 ± 0.7 km s −1 and the “red clump” 1.4 ± 0.5 km s −1 . While the blue and red clump shave similar temperatures and line widths, molecular species in the blue clump have higher column densities. They are both likely linked to pure rotational H 2 emission also covered by this survey. This work provides evidence for the scenario that the blue and red clumps are distinct components unrelated to the classic components in the Orion BN/KL region. Comparison to spectroscopic surveys towards other infrared targets in the region show that the blue clump is clearly extended. We analyze, compare, and present in depth findings on the physical conditions of C 2 H 2 , 13 CCH 2 , CH 4 , CS, H 2 O, HCN, H 13 CN, HNC, NH 3 , and SO 2 absorption lines and an H 2 emission line associated with the blue and red clumps. We also provide limited analysis of H 2 O and SiO molecular emission lines towards Orion IRc2 and the atomic forbidden transitions [FeII], [SI], [SIII], and [NeII].

Atomic spectroscopy↗
DOE OSTI2024

Molecular origin of viscoelasticity and influence of methylation in mesophase pitch

The viscoelastic and thermomechanical properties of pitches are responsible for their melt-spinning behavior, which is a critical step for manufacturing high-performance pitch-based carbon fibers. Here, we systematically explore the impact of methyl group modifications on the viscoelastic and thermal properties of mesophase pitches. We employ a range of atomistic modeling approaches, including Density Functional Theory (DFT), Density Functional Tight Binding (DFTB), and Classical Molecular Mechanics (MM), to provide detailed insights into the molecular interactions and structural changes. Further, our results revealed the molecular mechanisms that promote layered structures leading to the anisotropic nature of the viscoelastic behavior of mesophase pitch. Furthermore, we propose a modified molecular representation of naphthalene-based mesophase pitch based on the analysis of x-ray diffraction measurements. This study provides fundamental insights into the molecular structures of mesophase pitch and the role of methyl groups controlling its viscosity, which offer valuable insights into mesophase-based carbon fiber production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗