ANALYSIS OF A SKIMMER FOR A HIGH-INTENSITY MOLECULAR BEAM USING A THREE-FLUID MODEL
High energy, high intensity molecular beam flow is analyzed, using a skimmer which is a small inlet where the beam is separated from the core flow
SKIMMER↗
SEARCH · Engineering Papers
Results for “molecular modelling”
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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Folding and translocation of the undecamer of poly-L-leucine across the water-hexane interface. A molecular dynamics study
The undecamer of poly-L-leucine at the water-hexane interface is studied by molecular dynamics simulations. This represents a simple model relevant to folding and insertion of hydrophobic peptides into membranes. The peptide, initially placed in a random coil conformation on the aqueous side of the system, rapidly translocates toward the hexane phase and undergoes interfacial folding into an alpha-helix in the subsequent 36 ns. Folding is nonsequential and highly dynamic. The initially formed helical segment at the N-terminus of the undecamer becomes transiently broken and, subsequently, reforms before the remainder of the peptide folds from the C-terminus. The formation of intramolecular hydrogen bonds during the folding of the peptide is preceded by a dehydration of the participating polar groups, as they become immersed in hexane. Folding proceeds through a short-lived intermediate, a 3(10)-helix, which rapidly interconverts to an alpha-helix. Both helices contribute to the equilibrium ensemble of folded structures. The helical peptide is largely buried in hexane, yet remains adsorbed at the interface. Its preferred orientation is parallel to the interface, although the perpendicular arrangement with the N-terminus immersed in hexane is only slightly less favorable. In contrast, the reversed orientation is highly unfavorable, because it would require dehydration of C-terminus carbonyl groups that do not participate in intramolecular hydrogen bonding. For the same reason, the transfer of the undecamer from the interface to the bulk hexane is also unfavorable. The results suggest that hydrophobic peptides fold in the interfacial region and, simultaneously, translocate into the nonpolar side of the interface. It is further implied that peptide insertion into the membrane is accomplished by rotating from the parallel to the perpendicular orientation, most likely in such a way that the N-terminus penetrates the bilayer.
NASA Discipline Exobiology↗
Can a shock-induced phonon up-pumping model relate to impact sensitivity of molecular crystals, polymorphs and cocrystals?
Impact sensitivity engineering of high-energy molecular crystals requires accurate predictive models. For this purpose, the promising multi-phonon based approach is selected, assessing a bit more its strengths and weaknesses. Presently used with high-quality phonon calculations of 22 molecular crystals, using a physics-based criterion to determine the phonon bath extent, the resulting intrinsic shock sensitivity index (SSI) is compared to the most common marker of impact sensitivity, h 50 , as determined from drop-weight impact tests. Selecting a data subset from experiments performed under very similar conditions (2.5 kg hammer with grit and 30–40 mg samples), the model can predict h 50 values for mono-molecular crystals with very good accuracy, including the ability to discriminate the polymorphs of HMX and CL20. This very good agreement validates an initial indirect up-pumping mechanism occurring under these conditions, where the doorway modes also interact with the phonon bath. However, the phonon bath criterion for mono-molecular crystals does not transfer well to cocrystals. Owing to the vibrational coupling of the co-molecules, it seems a broader phonon bath should be considered. Additionally recalling experimental uncertainty and various experimental factors affecting h 50 values for a given compounds, we recommend that the density of the sample, granularity and morphology be systematically considered and reported along with measurements, which will in turn allow for more systematic data and predictive capabilities for sensitivity models.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Trapped-ion quantum simulation of electron transfer models with tunable dissipation
Electron transfer is at the heart of many fundamental physical, chemical, and biochemical processes essential for life. The exact simulation of these reactions is often hindered by the large number of degrees of freedom and by the essential role of quantum effects. Here, we experimentally simulate a paradigmatic model of molecular electron transfer using a multispecies trapped-ion crystal, where the donor-acceptor gap, the electronic and vibronic couplings, and the bath relaxation dynamics can all be controlled independently. By manipulating both the ground-state and optical qubits, we observe the real-time dynamics of the spin excitation, measuring the transfer rate in several regimes of adiabaticity and relaxation dynamics. Our results provide a testing ground for increasingly rich models of molecular excitation transfer processes that are relevant for molecular electronics and light-harvesting systems.
Science & Technology - Other Topics↗
Protein C-GeM: A Coarse-Grained Electron Model for Fast and Accurate Protein Electrostatics Prediction
The electrostatic potential (ESP) is a powerful property for understanding and predicting electrostatic charge distributions that drive interactions between molecules. In this study, we compare various charge partitioning schemes including fitted charges, density-based quantum mechanical (QM) partitioning schemes, charge equilibration methods, and our recently introduced coarse-grained electron model, C-GeM, to describe the ESP for protein systems. Furthermore, when benchmarked against high quality density functional theory calculations of the ESP for tripeptides and the crambin protein, we find that the C-GeM model is of comparable accuracy to ab initio charge partitioning methods, but with orders of magnitude improvement in computational efficiency since it does not require either the electron density or the electrostatic potential as input.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Warm neutral halos around molecular clouds. VI - Physical and chemical modeling
A combined physical and chemical modeling of the halos around molecular clouds is presented, with special emphasis on the H-to-H2 transition. On the basis of H I 21 cm observations, it is shown that the halos are extended. A physical model is employed in conjunction with a chemistry code to provide a self-consistent description of the gas. The radiative transfer code provides a check with H I, CO, and OH observations. It is concluded that the warm neutral halos are not gravitationally bound to the underlying molecular clouds and are isobaric. It is inferred from the observed extent of the H I envelopes and the large observed abundance of OH in them that the generally accepted rate for H2 information on grains is too large by a factor of two to three.
Andersson, B.-G.↗
An application of a statistical model for the calculation of the logarithmic mean excitation energy of molecules Molecular hydrogen
A statistical model, the local plasma approximation, is considered for the calculation of the logarithmic mean excitation energy for stopping power of chemically bound particles by taking into consideration chemical bonding. This statistical model is applied to molecular hydrogen and leads to results that suggest a value for the logarithmic mean excitation energy of molecular hydrogen that is larger than the accepted experimental and theoretical values.
Kamaratos, E.↗
High-excitation lines of molecular hydrogen: A discriminant between shock models
The results of column densities of molecular hydrogen, calculated from nineteen infrared line intensities, are discussed. They were measured at peak 1 of the outflow of the Orion molecular cloud OMC-1. The 1-0 O(7) and 0-0 S(13) lines of H2, at 3.8 microns, are mapped over the source. Their intensity ratio is found to be independent of position in the outflow. These observations are well fitted by a simple cooling-flow model of the line emitting region, but seem to be at variance with predictions of C-shocks current in the literature.
Burton, M.↗
A systematic method for selecting molecular descriptors as features when training models for predicting physiochemical properties
Machine learning has proven to be a powerful tool for accelerating biofuel development. Although numerous models are available to predict a range of properties using chemical descriptors, there is a trade-off between interpretability and performance. Neural networks provide predictive models with high accuracy at the expense of some interpretability, while simpler models such as linear regression often lack in accuracy. In addition to model architecture, feature selection is also critical for developing interpretable and accurate predictive models. We present a method for systematically selecting molecular descriptor features and developing interpretable machine learning models without sacrificing accuracy. Our method simplifies the process of selecting features by reducing feature multicollinearity and enables discoveries of new relationships between global properties and molecular descriptors. To demonstrate our approach, we developed models for predicting melting point, boiling point, flash point, yield sooting index, and net heat of combustion with the help of the Tree-based Pipeline Optimization Tool (TPOT). For training, we used publicly available experimental data for up to 8351 molecules. Our models accurately predict various molecular properties for organic molecules (mean absolute percent error (MAPE) ranges from 3.3% to 10.5%) and provide a set of features that are well-correlated to the property. This method enables researchers to explore sets of features that significantly contribute to the prediction of the property, offering new scientific insights. To help accelerate early stage biofuel research and development, we also integrated the data and models into a open-source, interactive web tool.
09 BIOMASS FUELS↗
Amino Acid Residues Controlling Domain Interaction and Interdomain Electron Transfer in Cellobiose Dehydrogenase
The function of cellobiose dehydrogenase (CDH) in biosensors, biofuel cells, and as a physiological redox partner of lytic polysaccharide monooxygenase (LPMO) is based on its role as an electron donor. Before donating electrons to LPMO or electrodes, an interdomain electron transfer from the catalytic FAD-containing dehydrogenase domain to the electron shuttling cytochrome domain of CDH is required. This study investigates the role of two crucial amino acids located at the dehydrogenase domain on domain interaction and interdomain electron transfer by structure-based engineering. The electron transfer kinetics of wild-type Myriococcum thermophilum CDH and its variants M309A, R698S, and M309A/R698S were analyzed by stopped-flow spectrophotometry and structural effects were studied by small-angle X-ray scattering. The data show that R698 is essential to pull the cytochrome domain close to the dehydrogenase domain and orient the heme propionate group towards the FAD, while M309 is an integral part of the electron transfer pathway – its mutation reducing the interdomain electron transfer 10-fold. Structural models and molecular dynamics simulations pinpoint the action of these two residues on the domain interaction and interdomain electron transfer.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The inclusion of the MT_CKD water vapor continuum model in the HITRAN molecular spectroscopic database
Not Available
Mlawer, E. J. (ORCID:0000000179624307)↗
Solving the puzzle of Fe homeostasis by integrating molecular, mathematical, and societal models
To ensure optimal utilization and bioavailability, iron uptake, transport, subcellular localization, and assimilation are tightly regulated in plants. In this work, we examine recent advances in our understanding of cellular responses to Fe deficiency. We then use intracellular mechanisms of Fe homeostasis to discuss how formalizing cell biology knowledge via a mathematical model can advance discovery even when quantitative data is limited. Using simulation-based inference to identify plausible systems mechanisms that conform to known emergent phenotypes can yield novel, testable hypotheses to guide targeted experiments. However, this approach relies on the accurate encoding of domain-expert knowledge in exploratory mathematical models. We argue that this would be facilitated by fostering more “systems thinking” life scientists and that diversifying your research team may be a practical path to achieve that goal.
59 BASIC BIOLOGICAL SCIENCES↗
Solvent and Temperature Effects on Photoinduced Proton-Coupled Electron Transfer in the Marcus Inverted Region
Concerted proton-coupled electron transfer (PCET) in the Marcus inverted region was recently demonstrated. Understanding the requirements for such reactivity is fundamentally important and holds promise as a design principle for solar energy conversion systems. Herein, we investigate the solvent polarity and temperature dependence of photoinduced proton-coupled charge separation (CS) and charge recombination (CR) in anthracene–phenol–pyridine triads: 1 (10-(4-hydroxy-3-(4-methylpyridin-2-yl)benzyl)anthracene-9-carbonitrile) and 2 (10-(4-hydroxy-3-(4-methoxypyridin-2-yl)benzyl)anthracene-9-carbonitrile). Both the CS and CR rate constants increased with increasing polarity in acetonitrile:n-butyronitrile mixtures. The kinetics were semi-quantitatively analyzed where changes in dielectric and refractive index, and thus consequently changes in driving force (–ΔG°) and reorganization energy (λ), were accounted for. The results were further validated by fitting the temperature dependence, from 180 to 298 K, in n-butyronitrile. The analyses support previous computational work where transitions to proton vibrational excited states dominate the CR reaction with a distinct activation free energy (ΔG* CR ~ 140 meV). However, the solvent continuum model fails to accurately describe the changes in ΔG° and λ with temperature via changes in dielectric constant and refractive index. Satisfactory modeling was obtained using the results of a molecular solvent model, which predicts that λ decreases with temperature, opposite to that of the continuum model. To further assess the solvent polarity control in the inverted region, the reactions were studied in toluene. Nonpolar solvents decrease both ΔG° CR and λ, slowing CR into the nanosecond time regime for 2 in toluene at 298 K. This demonstrates how PCET in the inverted region may be controlled to potentially use proton-coupled CS states for efficient solar fuel production and photoredox catalysis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Bayesian Calibration Framework with Embedded Model Error for Model Diagnostics
We study the utility and performance of a Bayesian model error embedding construction in the context of molecular dynamics modeling of metallic alloys, where we embed model error terms in existing interatomic potential model parameters. To alleviate the computational burden of this approach, we propose a framework combining likelihood approximation and Gaussian process surrogates. Here we leverage sparse Gaussian process techniques to construct a hierarchy of increasingly accurate but more expensive surrogate models. This hierarchy is then exploited by multilevel Markov chain Monte Carlo methods to efficiently sample from the target posterior distribution. We illustrate the utility of this approach by calibrating an interatomic potential model for a family of gold-copper alloys. In particular, this case study highlights effective means for dealing with computational challenges with Bayesian model error embedding in large-scale physical models, and the utility of embedded model error for model diagnostics.
Bayesian inference↗
Data-driven Magnetic Materials Modeling; Advances in Classical Molecular Dynamics.
Abstract not provided.
Nikolov, Svetoslav↗
Modeling Infection on a Molecular Level: Human Immunodeficiency Virus and Arenaviruses
Explore the source record for details and available documents.
Biological Science↗
Project: Molecular Coarse-Grained Modeling of Block Copolymer Mixtures [Slides]
Abstract not provided.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Model calculations of the molecular composition of interstellar grain mantles
A chemical reaction scheme comprising gas phase as well as grain surface reactions is used for the numerical calculation of the chemical composition of mantles accreting on interstellar grains. The composition of the growing grain mantle is determined on the basis of the relative accretion rates of the gas phase molecules and diffusion-controlled surface reactions. Results show that grain mantles generally consist of the molecules H2O, H2CO, N2, O2, CO, CO2, H2O2, and NH3. A detailed examination of the formation of H2 on grain surfaces leads to the conclusion that it proceeds through hydrogen abstraction from such molecules as H2CO, H2S, N2H2, and N2H4. The IR characteristics of the calculated grain mantles are discussed with emphasis on the observed ice band at the 3250/cm wavelength.
Tielens, A. G. G. M.↗