Transferable interatomic potential for aluminum from ambient conditions to warm dense matter
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36 MATERIALS SCIENCE↗
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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A marching method for calculating line and continuum radiation in high energy flow fields
A method is presented for calculating nongrey radiative fluxes and intensities in a highly ionized, low temperature plasma with extreme line broadening. The method was developed to study radiative heating phenomena in the mass-injected hypersonic shock-layer environments characteristic of outer planet atmospheric entry, although it is not limited to such studies. The radiative properties model assumed local thermodynamic equilibrium and used standard continuum and molecular band models. The atomic line model, however, used a frequency-marching method for the frequency integration, which not only accounted completely for line overlapping (reabsorption) effects, but compared favorably in economy with the best equivalent-width methods. An assessment of hydrogen line-far-wing treatments, with recommendations for engineering models, is also presented.
Bolz, C. W., Jr.↗
Protein structure, electron transfer and evolution of prokaryotic photosynthetic reaction centers
Photosynthetic reaction centers from a variety of organisms have been isolated and characterized. The groups of prokaryotic photosynthetic organisms include the purple bacteria, the filamentous green bacteria, the green sulfur bacteria and the heliobacteria as anoxygenic representatives as well as the cyanobacteria and prochlorophytes as oxygenic representatives. This review focuses on structural and functional comparisons of the various groups of photosynthetic reaction centers and considers possible evolutionary scenarios to explain the diversity of existing photosynthetic organisms.
NASA Discipline Exobiology↗
Fragment-based determination of a proteinase K structure from MicroED data using ARCIMBOLDO_SHREDDER
Structure determination of novel biological macromolecules by X-ray crystallography can be facilitated by the use of small structural fragments, some of only a few residues in length, as effective search models for molecular replacement to overcome the phase problem. Independence from the need for a complete pre-existing model with sequence similarity to the crystallized molecule is the primary appeal of ARCIMBOLDO , a suite of programs which employs this ab initio algorithm for phase determination. Here, the use of ARCIMBOLDO is investigated to overcome the phase problem with the electron cryomicroscopy (cryoEM) method known as microcrystal electron diffraction (MicroED). The results support the use of the ARCIMBOLDO_SHREDDER pipeline to provide phasing solutions for a structure of proteinase K from 1.6 Å resolution data using model fragments derived from the structures of proteins sharing a sequence identity of as low as 20%. ARCIMBOLDO_SHREDDER identified the most accurate polyalanine fragments from a set of distantly related sequence homologues. Alternatively, such templates were extracted in spherical volumes and given internal degrees of freedom to refine towards the target structure. Both modes relied on the rotation function in Phaser to identify or refine fragment models and its translation function to place them. Model completion from the placed fragments proceeded through phase combination of partial solutions and/or density modification and main-chain autotracing using SHELXE . The combined set of fragments was sufficient to arrive at a solution that resembled that determined by conventional molecular replacement using the known target structure as a search model. This approach obviates the need for a single, complete and highly accurate search model when phasing MicroED data, and permits the evaluation of large fragment libraries for this purpose.
59 BASIC BIOLOGICAL SCIENCES↗
$\mathrm{DRAGON}$: A multi-GPU orbital-free density functional theory molecular dynamics simulation package for modeling of warm dense matter
As progress in electronic structure theoretical methods is made, ab initio molecular dynamics (MD) based on orbital-free density functional theory (OF-DFT) is becoming increasingly more successful at substituting the traditional, very accurate but computationally costly Kohn–Sham (KS) approach for simulations of matter at the challenging warm dense matter (WDM) regime. However, despite the significant cost alleviation of eliminating the dependence on the KS orbitals, OF-DFT MD runs require ~10 2 to 10 3 CPU cores running for days, or even weeks, for simulations of systems comprised of 10 2 to 10 3 atoms, depending on thermodynamic conditions. Here we present DRAGON, a multi-GPU OF-DFT MD code for fast and efficient simulations of WDM. With a relatively small allocation of resources (4 to 8 GPU devices) it can provide an order of magnitude speedup for simulations containing $\mathscr{O}$(10 4 ) atoms and target systems composed of $\mathscr{O}$(10 5 ) atoms at conditions within the WDM regime, which is currently outside the capabilities of CPU codes.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Molecular Beam Epitaxy (MBE) Growth of Model Cathodes to Study Interfacial Ion Diffusion
Lithium-ion batteries (LIBs) have been the focus of research for decades owing to their superior energy storage potential and wide range of applications. However, long-term stability issues still persist in LIB cathodes as the result of the formation of a solid electrolyte interface (SEI), structural transformations, or the loss of active cathode materials. In nanoscale cathodes, it is often impossible to isolate, let alone mitigate the causes of the observed capacity loss. Herein, a novel approach is presented to synthesizing LIB cathode model systems using thin-film molecular beam epitaxy (MBE). Specifically, 100 nm thick LiMn 2 O 4 (LMO) thin-film cathodes are grown on SrRuO 3 /SrTiO 3 (100) single-crystal substrates and characterized in their pristine and cycled states. The pristine thin films exhibit the electro-chemical cycling behavior and structural evolution previously seen in bulk LMO cathodes. The formation of surface-layer rocksalt MnO and spinel Mn 3 O 4 along with the mass-loss associated with the corrosion of active Mn ions is also reported. It is, therefore, demonstrated that these MBE-grown model systems can be used for detailed studies of their surface structures and the electrode/electrolyte interfacial evolution in LIB cathodes, leading to the development of materials for rechargeable batteries with higher capacity and better stability.
25 ENERGY STORAGE↗
AlphaFold -assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography
Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.
molecular replacement↗
A 1-D Model of the 4 Bed Molecular Sieve of the Carbon Dioxide Removal Assembly
Developments to improve system efficiency and reliability for water and carbon dioxide separation systems on crewed vehicles combine sub-scale systems testing and multi-physics simulations. This paper describes the development of COMSOL simulations in support of the Life Support Systems (LSS) project within NASA's Advanced Exploration Systems (AES) program. Specifically, we model the 4 Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) operating on the International Space Station (ISS).
Coker, Robert↗
A model for including thermal conduction in molecular dynamics simulations
A technique is introduced for including thermal conduction in molecular dynamics simulations for solids. A model is developed to allow energy flow between the computational cell and the bulk of the solid when periodic boundary conditions cannot be used. Thermal conduction is achieved by scaling the velocities of atoms in a transitional boundary layer. The scaling factor is obtained from the thermal diffusivity, and the results show good agreement with the solution for a continuous medium at long times. The effects of different temperature and size of the system, and of variations in strength parameter, atomic mass, and thermal diffusivity were investigated. In all cases, no significant change in simulation results has been found.
Wu, Yue↗
A lignin-specific peroxidase in tobacco whose antisense suppression leads to vascular tissue modification
A tobacco peroxidase isoenzyme (TP60) was down-regulated in tobacco using an antisense strategy, this affording transformants with lignin reductions of up to 40-50% of wild type (control) plants. Significantly, both guaiacyl and syringyl levels decreased in essentially a linear manner with the reductions in lignin amounts, as determined by both thioacidolysis and nitrobenzene oxidative analyses. These data provisionally suggest that a feedback mechanism is operative in lignifying cells, which prevents build-up of monolignols should oxidative capacity for their subsequent metabolism be reduced. Prior to this study, the only known rate-limiting processes in the monolignol/lignin pathways involved that of Phe supply and the relative activities of cinnamate-4-hydroxylase/p-coumarate-3-hydroxylase, respectively. These transformants thus provide an additional experimental means in which to further dissect and delineate the factors involved in monolignol targeting to precise regions in the cell wall, and of subsequent lignin assembly. Interestingly, the lignin down-regulated tobacco phenotypes displayed no readily observable differences in overall growth and development profiles, although the vascular apparatus was modified.
NASA Program Fundamental Space Biology↗
The gating mechanism of the large mechanosensitive channel MscL
The mechanosensitive channel of large conductance, MscL, is a ubiquitous membrane-embedded valve involved in turgor regulation in bacteria. The crystal structure of MscL from Mycobacterium tuberculosis provides a starting point for analysing molecular mechanisms of tension-dependent channel gating. Here we develop structural models in which a cytoplasmic gate is formed by a bundle of five amino-terminal helices (S1), previously unresolved in the crystal structure. When membrane tension is applied, the transmembrane barrel expands and pulls the gate apart through the S1-M1 linker. We tested these models by substituting cysteines for residues predicted to be near each other only in either the closed or open conformation. Our results demonstrate that S1 segments form the bundle when the channel is closed, and crosslinking between S1 segments prevents opening. S1 segments interact with M2 when the channel is open, and crosslinking of S1 to M2 impedes channel closing. Gating is affected by the length of the S1-M1 linker in a manner consistent with the model, revealing critical spatial relationships between the domains that transmit force from the lipid bilayer to the channel gate.
Non-NASA Center↗
Predicting permeation of compounds across the outer membrane of P. aeruginosa using molecular descriptors
The ability Gram-negative pathogens have at adapting and protecting themselves against antibiotics has increasingly become a public health threat. Data-driven models identifying molecular properties that correlate with outer membrane (OM) permeation and growth inhibition while avoiding efflux could guide the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa. The descriptors are derived from traditional approaches quantifying the compounds’ intrinsic physicochemical properties, together with, bacterium-specific from ensemble docking of compounds targeting specific MexB binding pockets, and all-atom molecular dynamics simulations in different subregions of the OM model. Using these descriptors and the measured inhibitory concentrations, we design a statistical protocol to identify predictors of OM permeation/inhibition. We find consistent rules across most of our data highlighting the role of the interaction between the compounds and the OM. An implementation of the rules uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Our analysis sheds new light on the key properties drug candidates need to effectively permeate/inhibit P. aeruginosa, and opens the gate to similar data-driven studies in other Gram-negative pathogens.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Molecular Sieve Bench Testing and Computer Modeling
The design of an efficient four-bed molecular sieve (4BMS) CO2 removal system for the International Space Station depends on many mission parameters, such as duration, crew size, cost of power, volume, fluid interface properties, etc. A need for space vehicle CO2 removal system models capable of accurately performing extrapolated hardware predictions is inevitable due to the change of the parameters which influences the CO2 removal system capacity. The purpose is to investigate the mathematical techniques required for a model capable of accurate extrapolated performance predictions and to obtain test data required to estimate mass transfer coefficients and verify the computer model. Models have been developed to demonstrate that the finite difference technique can be successfully applied to sorbents and conditions used in spacecraft CO2 removal systems. The nonisothermal, axially dispersed, plug flow model with linear driving force for 5X sorbent and pore diffusion for silica gel are then applied to test data. A more complex model, a non-darcian model (two dimensional), has also been developed for simulation of the test data. This model takes into account the channeling effect on column breakthrough. Four FORTRAN computer programs are presented: a two-dimensional model of flow adsorption/desorption in a packed bed; a one-dimensional model of flow adsorption/desorption in a packed bed; a model of thermal vacuum desorption; and a model of a tri-sectional packed bed with two different sorbent materials. The programs are capable of simulating up to four gas constituents for each process, which can be increased with a few minor changes.
Mohamadinejad, Habib↗
Stockmayer fluid simulations for viscosity and glass transition temperature of ionic liquids
We develop a Stockmayer fluid model for molecular dynamics simulations of ionic liquids that captures molecular polarization, ionic conductivity, viscosity, and glass transition temperature, using ethylammonium nitrate (EAN) as an example. The ions in EAN are treated as spheres interacting via the Lennard-Jones potential with an embedded point charge and a permanent dipole moment. We show that our simulation results for EAN are consistent with experimental data and then explore the effects of the molecular parameters on the viscosity of ionic liquids. Our results indicate that viscosity monotonically increases with ionic charge and dipole moment but non-monotonically changes with ionic diameter (or molar volume). This non-monotonic trend arises from the competition among the electrostatic interactions, molecular packing, and size asymmetry between the cation and anion. In conclusion, our model also shows that long-lived ion pairs result in higher viscosities.
Coarse-grained simulations↗
Kinetics of solid–liquid interface motion in molecular dynamics and phase-field models: crystallization of chromium and silicon
The results of molecular dynamics (MD) simulations of the crystallization process in one-component materials and solid solution alloys reveal a complex temperature dependence of the velocity of the crystal–liquid interface featuring an increase up to a maximum at 10–30% undercooling below the equilibrium melting temperature followed by a gradual decrease of the velocity at deeper levels of undercooling. At the qualitative level, such non-monotonous behaviour of the crystallization front velocity is consistent with the diffusion-controlled crystallization process described by the Wilson–Frenkel model, where the almost linear increase of the interface velocity in the vicinity of melting temperature is defined by the growth of the thermodynamic driving force for the phase transformation, while the decrease in atomic mobility with further increase of the undercooling drives the velocity through the maximum and into a gradual decrease at lower temperatures. At the quantitative level, however, the diffusional model fails to describe the results of MD simulations in the whole range of temperatures with a single set of parameters for some of the model materials. The limited ability of the existing theoretical models to adequately describe the MD results is illustrated in the present work for two materials, chromium and silicon. It is also demonstrated that the MD results can be well described by the solution following from the hodograph equation, previously found from the kinetic phase-field model (kinetic PFM) in the sharp interface limit. The ability of the hodograph equation to describe the predictions of MD simulation in the whole range of temperatures is related to the introduction of slow (phase field) and fast (gradient flow) variables into the original kinetic PFM from which the hodograph equation is obtained. The slow phase-field variable is responsible for the description of data at small undercoolings and the fast gradient flow variable accounts for local non-equilibrium effects at high undercoolings. The introduction of these two types of variables makes the solution of the hodograph equation sufficiently flexible for a reliable description of all nonlinearities of the kinetic curves predicted in MD simulations of Cr and Si. This article is part of the theme issue ‘Transport phenomena in complex systems (part 1)’.
Science & Technology - Other Topics↗
Advancing molecular machine learning representations with stereoelectronics-infused molecular graphs
Molecular representation is a critical element in our understanding of the physical world and the foundation for modern molecular machine learning. Previous molecular machine learning models have used strings, fingerprints, global features and simple molecular graphs that are inherently information-sparse representations. However, as the complexity of prediction tasks increases, the molecular representation needs to encode higher fidelity information. This work introduces a new approach to infusing quantum-chemical-rich information into molecular graphs via stereoelectronic effects, enhancing expressivity and interpretability. Learning to predict the stereoelectronics-infused representation with a tailored double graph neural network workflow enables its application to any downstream molecular machine learning task without expensive quantum-chemical calculations. We show that the explicit addition of stereoelectronic information substantially improves the performance of message-passing two-dimensional machine learning models for molecular property prediction. We show that the learned representations trained on small molecules can accurately extrapolate to much larger molecular structures, yielding chemical insight into orbital interactions for previously intractable systems, such as entire proteins, opening new avenues of molecular design. Finally, we have developed a web application (simg.cheme.cmu.edu) where users can rapidly explore stereoelectronic information for their own molecular systems.
Boiko, Daniil A↗
PSCF+: An Extended and Improved Open-Source Software Package for Polymer Self-Consistent Field Calculations
This work introduces PSCF+, a freely available open‑source software tool for modeling how block copolymers self‑assemble into ordered nanoscale structures. The software allows researchers to study a wide range of polymer models and interaction types, making it possible to directly compare theoretical predictions with molecular and simulation‑based studies in a consistent way. PSCF+ incorporates several recently developed numerical methods that significantly reduce computer memory requirements and speed up calculations, enabling efficient use of modern GPU hardware. Here, it also provides automated tools to calculate free‑energy landscapes and phase boundaries, which are essential for understanding and predicting material behavior. Together, these advances make PSCF+ a powerful and flexible platform for studying polymer self‑assembly and support the design of new polymeric materials for scientific and technological applications.
Chemical calculations↗
Modeling gas–shell mixing in ICF with separated reactants
Mixing between fuel and shell materials in ICF implosions can affect implosion dynamics and even prevent ignition. We use data from a series of separated reactant experiments on the National Ignition Facility to calibrate and test the predictive power of gas–shell mix models. Two models are used to estimate fuel–shell mix: a Reynolds-averaged turbulence model and molecular diffusion. Minor uncertainties in capsule manufacture, experimental conditions, and values for mix model parameters produce significant variation in simulation results. Using input/output pairs from 1D simulations, we train Gaussian process surrogate models to predict experimental quantities of interest. The surrogates are used to construct posteriors for mix model parameters by marginalizing over uncertainties in capsule manufacture and experimental conditions. Mix models are calibrated with a subset of experimental data (neutron yields, ion temperature, and bang time) and tested using the remaining data. In general, both the diffusion and turbulence model correctly predict experimental DT and TT neutron yields. Despite having more free parameters, the turbulence model underpredicts ion temperature at high convergence ratio. Furthermore, the simpler diffusion model correctly predicts these temperatures, suggesting nonhydrodynamic gas–shell mix. The computational model consistently overpredicts DD neutron yield, indicating possible shortcomings outside of the mix model.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗