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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Statistical Classification of Biosignature Information: Combining Elemental, Molecular, Reflectance, and Raman Data to Increase Life Detection Confidence

Planetary exploration missions seeking past or present signs of life carry not just a single instrument, but a suite. There is a need to study how these multiple data types can be combined to create “composite” biosignatures [1]. Algorithmic methods using existing data on living and non-living systems, though limited by the n = 1 of Earth, can nonetheless be informative. We assembled a database of 1277 measurements spanning 16 representative systems either indicative or non-indicative of life. Five classification (machine learning) methods were used on each individual data type, then on the entire set. This abstract summarizes the results; the data is described in more detail in [2], and methods in [3].

Biosignatures↗

MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations

The MBX software provides an advanced platform for molecular dynamics simulations, leveraging state-of-the-art MB-pol and MB-nrg data-driven many-body potential energy functions. Developed over the past decade, these potential energy functions integrate physics-based and machine-learned many-body terms trained on electronic structure data calculated at the "gold standard" coupled-cluster level of theory. Recent advancements in MBX have focused on optimizing its performance, resulting in the release of MBX v1.2. While the inherently many-body nature of MB-pol and MB-nrg ensures high accuracy, it poses computational challenges. MBX v1.2 addresses these challenges with significant performance improvements, including enhanced parallelism that fully harnesses the power of modern multicore CPUs. In conclusion, these advancements enable simulations on nanosecond time scales for condensed-phase systems, significantly expanding the scope of high-accuracy, predictive simulations of complex molecular systems powered by data-driven many-body potential energy functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computer program for calculation of ideal gas thermodynamic data

Computer program calculates ideal gas thermodynamic properties for any species for which molecular constant data is available. Partial functions and derivatives from formulas based on statistical mechanics are provided by the program which is written in FORTRAN 4 and MAP.

Gordon, S.↗

Properties And Coefficient Program For The Calculation Of Thermodynamic Data (PAC2)

Program calculates ideal gas thermodynamic properties for any species for which molecular constant data available, and offers user choice of methodologies for performing thermodynamic calculations. PAC2 updated to PAC4. Improvements include increased user friendliness and ability to extrapolate thermodynamic properties for gases to higher temperatures using Wilhoit's formulas.

Mcbride, B. J.↗

Emergent Nanostructure and Ion Transport in Polyzwitterion/Polyanion Blends

We investigated blends of poly(1-(3-sulfonatopropyl)-2-vinylpyridinium) (P2VPPS) and poly(lithium (trifluoromethane)sulfonimide methacrylate) (poly(MTFSI)Li) at varying molar ratios to gain a mechanistic understanding of ionic conductivity in a miscible polyzwitterion/polyanion system. This dataset contains the raw numerical data corresponding to the figures in the manuscript. The data files include the following information: (1) Experimental Data – includes X-ray and neutron scattering measurements, broadband dielectric spectroscopy (BDS) data, extracted DC conductivity values, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) results, extracted glass transition temperatures, etc. (2) CGMD Data – includes molecular dynamics (MD) trajectory files and computed structural correlations. All data files are organized/named according to the figure numbers in the manuscript.

36 MATERIALS SCIENCE↗

FTP-Server for exchange, interpretation, and database-search of ion mobility spectra, literature, preprints and software

To assist current discussion in the field of ion mobility spectrometry, at the Institut fur Spectrochemie und angewandte Spektroskopie, Dortmund, start with 4th of December, 1994 work of an FTP-Server, available for all research groups at univerisities, institutes and research worker in industry. We support the exchange, interpretation, and database-search of ion mobility spectra through data format JCAMP-DS (Joint Committee on Atomic and Molecular Physical Data) as well as literature retrieval, pre-print, notice, and discussion board. We describe in general lines the entrance conditions, local addresses, and main code words. For further details, a monthly news report will be prepared for all common users. Internet email address for subscribing is included in document.

Baumbach, J. I.↗

The Evolution of Sulfide Tolerance in the Cyanobacteria

Understanding how the function of extant microorganisms has recorded both their evolutionary histories and their past interactions with the environment is a stated goal of astrobiology. We are taking a multidisciplinary approach to investigate the diversification of sulfide tolerance mechanisms in the cyanobacteria, which vary both in their degree of exposure to sulfide and in their capacity to tolerate this inhibitor of photosynthetic electron transport. Since conditions were very reducing during the first part of Earth's history and detrital sulfides have been found in Archean sediments, mechanisms conferring sulfide tolerance may have been important for the evolutionary success of the ancestors of extant cyanobacteria. Two tolerance mechanisms have been identified in this group: (1) resistance of photosystem II, the principal target of sulfide toxicity; and (2) maintenance of the ability to fix carbon despite photosystem II inhibition by utilizing sulfide as an electron donor in photosystem I - dependent, anoxygenic photosynthesis. We are presently collecting comparative data on aspects of sulfide physiology for laboratory clones isolated from a variety of habitats. These data will be analyzed within a phylogenetic framework inferred from molecular sequence data collected for these clones to test how frequently different mechanisms of tolerance have evolved and which tolerance mechanism evolved first. In addition, by analyzing these physiological data together with environmental sulfide data collected from our research sites using microelectrodes, we can also test whether the breadth of an organism's sulfide tolerance can be predicted from the magnitude of variation in environmental sulfide concentration it has experienced in its recent evolutionary past and whether greater average sulfide concentration and/or temporal variability in sulfide favors the evolution of a particular mechanism of sulfide tolerance.

Miller, Scott R.↗

Molecular and particulate contaminants - A contamination data base within ENVIRONET

The Space Transportation System contamination environment appears in the ENVIRONET data base in two parallel chapters, Molecular Contamination and Particulate Environment. The design objectives and a description of the content of this contamination data base are presented. A treatment of the use of the data base is intended to interest the reader in accessing and browsing these chapters. Future plans are discussed briefly, with the emphasis on the approach to providing a dynamic data base.

Barengoltz, Jack↗

Data Needs for Stellar Atmosphere and Spectrum Modeling

The main data need for stellar atmosphere and spectrum modeling remains atomic and molecular transition data, particularly energy levels and transition cross-sections. We emphasize that data is needed for bound-free (b - f) as well as bound-bound (b - b), and collisional as well as radiative transitions. Data is now needed for polyatomic molecules as well as atoms, ions, and diatomic molecules. In addition, data for the formation of, and extinction due to, liquid and solid phase dust grains is needed. A prioritization of species and data types is presented, and gives emphasis to Fe group elements, and elements important for the investigation of nucleosynthesis and Galactic chemical evolution, such as the -elements and n-capture elements. Special data needs for topical problems in the modeling of cool stars and brown dwarfs are described.

Short, C. I.↗

Can machine learning predict fuel properties accurately?

High-potential molecules derived from biomass sources may suitably replace or supplement traditional nonrenewable hydrocarbon fuels to reduce pollution and fuel processing cost. Experimental property testing of these bioproducts is usually conducted years after initial bench-scale experiments, due to high experimental costs and/or high volume requirements. However, neglecting to conduct property testing early in the pathway development cycle can lead to investments spent on scaling-up production of bioproducts and biofuels that do not perform as expected. Instead, machine-learning techniques can be used to develop quantitative structure–property relationships for molecules using a relatively large training set of molecular descriptor data. For this study, we compiled measured properties, IR spectra, and molecular descriptors of bio-based molecules from databases and published studies for training models of bioproduct properties. We trained regression models with molecular descriptors and will compare results of different estimators. This study describes the first steps towards a performance prediction tool for bio-based alternative fuels. Keywords: Machine learning, biofuels, jet fuels, fuel properties

Mayer, Morgan A.↗

Reconstruction of effective potential from statistical analysis of dynamic trajectories

The broad incorporation of microscopic methods is yielding a wealth of information on the atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here, we develop a method for the stochastic reconstruction of effective local potentials solely from observed structural data collected from molecular dynamics simulations (i.e., data analogous to those obtained via atomically resolved microscopies). Using the silicon vacancy defect in graphene as a model, we apply the statistical framework presented herein to reconstruct the free energy landscape from the calculated atomic displacements. Evidence of consistency between the reconstructed local potential and the trajectory data from which it was produced is presented, along with a quantitative assessment of the uncertainty in the inferred parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗

Leiomodin creates a leaky cap at the pointed end of actin-thin filaments

Improper lengths of actin-thin filaments are associated with altered contractile activity and lethal myopathies. Leiomodin, a member of the tropomodulin family of proteins, is critical in thin filament assembly and maintenance; however, its role is under dispute. Using nuclear magnetic resonance data and molecular dynamics simulations, we generated the first atomic structural model of the binding interface between the tropomyosin-binding site of cardiac leiomodin and the N-terminus of striated muscle tropomyosin. Our structural data indicate that the leiomodin/tropomyosin complex only forms at the pointed end of thin filaments, where the tropomyosin N-terminus is not blocked by an adjacent tropomyosin protomer. This discovery provides evidence supporting the debated mechanism where leiomodin and tropomodulin regulate thin filament lengths by competing for thin filament binding. Data from experiments performed in cardiomyocytes provide additional support for the competition model; specifically, expression of a leiomodin mutant that is unable to interact with tropomyosin fails to displace tropomodulin at thin filament pointed ends and fails to elongate thin filaments. Together with previous structural and biochemical data, we now propose a molecular mechanism of actin polymerization at the pointed end in the presence of bound leiomodin. In the proposed model, the N-terminal actin-binding site of leiomodin can act as a “swinging gate” allowing limited actin polymerization, thus making leiomodin a leaky pointed-end cap. Results presented in this work answer long-standing questions about the role of leiomodin in thin filament length regulation and maintenance.

2D-NMR↗

Biomembrane Structure and Material Properties Studied With Neutron Scattering

Cell membranes and their associated structures are dynamical supramolecular structures where different physiological processes take place. Detailed knowledge of their static and dynamic structures is therefore needed, to better understand membrane biology. The structure–function relationship is a basic tenet in biology and has been pursued using a range of different experimental approaches. In this review, we will discuss one approach, namely the use of neutron scattering techniques as applied, primarily, to model membrane systems composed of lipid bilayers. An advantage of neutron scattering, compared to other scattering techniques, is the differential sensitivity of neutrons to isotopes of hydrogen and, as a result, the relative ease of altering sample contrast by substituting protium for deuterium. This property makes neutrons an ideal probe for the study of hydrogen-rich materials, such as biomembranes. In this review article, we describe isotopic labeling studies of model and viable membranes, and discuss novel applications of neutron contrast variation in order to gain unique insights into the structure, dynamics, and molecular interactions of biological membranes. We specifically focus on how small-angle neutron scattering data is modeled using different contrast data and molecular dynamics simulations. We also briefly discuss neutron reflectometry and present a few recent advances that have taken place in neutron spin echo spectroscopy studies and the unique membrane mechanical data that can be derived from them, primarily due to new models used to fit the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adsorption space for microporous polymers with diverse adsorbate species

Abstract The enormous number of combinations of adsorbing molecules and porous materials that exist is known as adsorption space. The adsorption space for microporous polymers has not yet been systematically explored, especially when compared with efforts for crystalline adsorbents. We report molecular simulation data for the adsorptive and structural properties of polymers of intrinsic microporosity with a diverse set of adsorbate species with 345 distinct adsorption isotherms and over 240,000 fresh and swollen structures. These structures and isotherms were obtained using a sorption-relaxation technique that accounts for the critical role of flexibility of the polymeric adsorbents. This enables us to introduce a set of correlations that can estimate adsorbent swelling and fractional free volume dilation as a function of adsorbate uptake based on readily characterized properties. The separation selectivity of the 276 distinct binary molecular pairs in our data is reported and high-performing adsorbent systems are identified.

36 MATERIALS SCIENCE↗

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Archaeal phylogeny: reexamination of the phylogenetic position of Archaeoglobus fulgidus in light of certain composition-induced artifacts

A major and too little recognized source of artifact in phylogenetic analysis of molecular sequence data is compositional difference among sequences. The problem becomes particularly acute when alignments contain ribosomal RNAs from both mesophilic and thermophilic species. Among prokaryotes the latter are considerably higher in G + C content than the former, which often results in artificial clustering of thermophilic lineages and their being placed artificially deep in phylogenetic trees. In this communication we review archaeal phylogeny in the light of this consideration, focusing in particular on the phylogenetic position of the sulfate reducing species Archaeoglobus fulgidus, using both 16S rRNA and 23S rRNA sequences. The analysis shows clearly that the previously reported deep branching of the A. fulgidus lineage (very near the base of the euryarchaeal side of the archaeal tree) is incorrect, and that the lineage actually groups with a previously recognized unit that comprises the Methanomicrobiales and extreme halophiles.

NASA Discipline Exobiology↗