Direct molecular gas dynamics simulations of re-entry vehicles via the Boltzmann equation
Explore the source record for details and available documents.
Engineering - Aeronautics, Mathematics and Computi↗
SEARCH · Engineering Papers
Results for “molecular simulation”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
CHARMM-GUI Nanomaterial Modeler for Modeling and Simulation of Nanomaterial Systems
Molecular modeling and simulation are invaluable tools for nanoscience that predict mechanical, physicochemical, and thermodynamic properties of nanomaterials and provide molecular-level insight into underlying mechanisms. However, building nanomaterial-containing systems remains challenging due to the lack of reliable and integrated cyberinfrastructures. Here we present Nanomaterial Modeler in CHARMM-GUI, a web-based cyberinfrastructure that provides an automated process to generate various nanomaterial models, associated topologies, and configuration files to perform state-of- the-art molecular dynamics simulations using most simulation packages. The nanomaterial models are based on the interface force field, one of the most reliable force fields (FFs). The transferability of nanomaterial models among the simulation programs was assessed by single-point energy calculations, which yielded 0.01% relative absolute energy differences for various surface models and equilibrium nanoparticle shapes. Three widely used Lennard-Jones (LJ) cutoff methods are employed to evaluate the compatibility of nanomaterial models with respect to conventional biomolecular FFs: simple truncation at r = 12 Å (12 cutoff), force-based switching over 10 to 12 Å (10-12 fsw), and LJ particle mesh Ewald with no cutoff (LJPME). The FF parameters with these LJ cutoff methods are extensively validated by reproducing structural, interfacial, and mechanical properties. As a result, we find that the computed density and surface energies are in good agreement with reported experimental results, although the simulation results increase in the following order: 10-12 fsw <12 cutoff < LJPME. Nanomaterials in which LJ interactions are a major component show relatively higher deviations (up to 4% in density and 8% in surface energy differences) compared with the experiment. Nanomaterial Modeler's capability is also demonstrated by generating complex systems of nanomaterial-biomolecule and nanomaterial-polymer interfaces with a combination of existing CHARMM-GUI modules. We hope that Nanomaterial Modeler can be used to carry out innovative nanomaterial modeling and simulations to acquire insight into the structure, dynamics, and underlying mechanisms of complex nanomaterial-containing systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations
We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.
59 BASIC BIOLOGICAL SCIENCES↗
PYSEQM
PYSEQM is a package for performing semi-empirical quantum mechanical (SEQM) simulations on molecular systems utilizing PyTorch. SEQM simulations determine molecular properties (energy, electron density, dipole moment, ect.) by solving an approximate Schrödinger equation for the motions of electrons in a molecule. The use of PyTorch provides three specific advantages. First, it allows the calculations to be offloaded to GPU accelerators, giving an order of magnitude increase in speed. Second, back propagation is used to get atomic forces (derivative of the total energy with respect to atomic position) at the same computational cost as the energy calculation itself. Finally, the use of PyTorch makes for a natural interface to modern machine learning methods, which can be used to adjust the semi-empirical parameters build into SEQM methods. Additionally, PYSEQM implements various other optimizations for performing quantum mechanics based molecular dynamics, including SP2 for rapid GPU based solution of the self-consistent field algorithm, and the extended Lagrangian method for rapid QM-MD.
Nebgen, Benjamin↗
A Molecular Description of Hydrogel Forming Polymers for Cement-Based Printing Paste Applications
This research endeavors to link the physical and chemical characteristics of select polymer hydrogels to differences in printability when used as printing aids in cement-based printing pastes. A variety of experimental probes including differential scanning calorimetry (DSC), NMR-diffusion ordered spectroscopy (DOSY), quasi-elastic neutron scattering (QENS) using neutron backscattering spectroscopy, and X-ray powder diffraction (XRD), along with molecular dynamic simulations, were used. Conjectures based on objective measures of printability and physical and chemical-molecular characteristics of the polymer gels are emerging that should help target printing aid selection and design, and mix formulation. Molecular simulations were shown to link higher hydrogen bond probability and larger radius of gyration to higher viscosity gels. Furthermore, the higher viscosity gels also produced higher elastic properties, as measured by neutron backscattering spectroscopy.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
On the Statistical Mechanics of Mass Accommodation at Liquid–Vapor Interfaces
Here we propose a framework for describing the dynamics associated with the adsorption of small molecules to liquid-vapor interfaces using an intermediate resolution between traditional continuum theories that are bereft of molecular detail and molecular dynamics simulations that are replete with them. In particular, we develop an effective single particle equation of motion capable of describing the physical processes that determine thermal and mass accommodation probabilities. The effective equation is parametrized with quantities that vary through space away from the liquid-vapor interface. Of particular importance in describing the early time dynamics is the spatially dependent friction, for which we propose a numerical scheme to evaluate from molecular simulation. Taken together with potentials of mean force computable with importance sampling methods, we illustrate how to compute the mass accommodation coefficient and residence time distribution. Throughout, we highlight the case of ozone adsorption in aqueous solutions and its dependence on electrolyte composition.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A spline-based method to obtain spatially dependent viscosity in confined flows
Coupling chemical physics to continuum theories is a critical step to understanding multi-scale phenomena. This paper will connect non-equilibrium molecular dynamics simulations to a continuum-based Navier-Stokes equation that has relaxed the assumption of spatial uniformity in viscosity. Using a form for viscosity based on spline interpolation, viscosity as a function of position is obtained from the least squares fit of the velocity profile measured from molecular simulations of flow in a nanochannel. Viscosity can vary widely, particularly near the channel boundaries, indicating that uniform viscosity is no longer appropriate. Variations of the viscosity near the channel surfaces imply that considering solution and surface chemistry could be necessary to rigorously understand molecular-scale flows in nanochannels.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
In-Silico Design of Next Generation Cellulose-Derived Packaging Materials (CRADA Final Report)
Developing sustainable solutions for single-use packaging is an important objective to combat the environmental crisis of plastics pollution. Most embodiments of cellulose-based packaging materials, including CellophaneTM, are completely biodegradable in both terrestrial and marine environments. However, petroleum-derived alternatives offer some performance advantages for metrics such as moisture barriers and mechanical properties. This project leverages molecular dynamics simulation to investigate how molecular modifications to cellulose-based polymer assemblies impact their material properties. An important performance criterion for the modified materials was to retain biodegradability; thus, modifications by naturally occurring, biodegradable additives were the focus of this study. Specifically, we developed models with xylan and lignin of varying monomeric compositions into the cellulose matrix. The mechanical properties were investigated by performing stress-strain simulations, and the water barrier and hydrophobicity were investigated by simulating the water contact angle. Our findings indicate that the incorporation of xylan into the cellulose matrix tends to increase the mechanical properties with an optimal loading of ~27 wt%. We also predict that orienting the nanoscale directionality of the xylan chains such that they are perpendicular to the cellulose fibrils will dramatically increase mechanical strength. In contrast, the incorporation of lignin tends to weaken the composite at all loadings investigated. Simulations of water contact angle predicted that coating polymers on the surface of the cellulose assembly creates a more hydrophobic surface than incorporating them throughout the matrix. Of the coatings investigated, lignin resulted in the most hydrophobic surface, followed by pectin and keratin, which both imparted modest increases in hydrophobicity. Future experimental work done by Futamura will focus on designing material prototypes to capitalize on the predictions of performance enhancement obtained from molecular modeling. While substantial progress was made by the simulations performed in this project, there still exists a vast parameter space that we were unable to investigate, including branching, functional group decoration, and degree of polymerization of polymer additives. However, the methods developed in this initial investigation will facilitate more rapid evaluation of the impact of molecular characteristics on the performance of biopolymer composite materials and thereby accelerate future materials discovery efforts in this area.
36 MATERIALS SCIENCE↗
Self-Healing Ceramics and Mechanical Metamaterials
We performed large scale molecular dynamics (MD) simulations and reactive & quantum molecular dynamics simulations to investigate: (1) faceting, grain growth, and crack healing in ceramics; (2) stress-release mechanism and healing in fibers; and (3) mechanical properties of two-dimensional metamaterials. We also designed highly accurate interatomic potentials and forces using artificial neural networks (ANN) and first-principles molecular dynamics simulation data for use in our MD and reactive MD simulations. We demonstrated the efficacy of modeling quantum materials atomistic simulation data using unsupervised deep learning approaches on a quantum computer. These achievements are elaborated in the following sections.
36 MATERIALS SCIENCE↗
Concentration Dependent Interfacial Chemistry of the NaOH(aq):Gibbsite Interface
Caustic conditions are often employed for dissolution of a wide variety of minerals, where ion sorption, surface diffusion, and interfacial organization impact surface reactivity. In the case of gibbsite, gamma-Al(OH)3, the chemistry at the NaOH(aq) interface is deeply intertwined with industrial processing of aluminum, including metal production and the disposition of Al-containing wastes. To date, little is known about the structure, speciation, and dynamic behavior of gibbsite interfaces (and that of many other minerals) with NaOH(aq)—particularly as a function of ionic strength. Yet concentration-dependent interfacial organization and dynamics are a critical starting point to develop a fundamental understanding of the factors that influence dissolution. This work reports equilibrium molecular dynamics simulations of the gamma-Al(OH)3:NaOH(aq) interface, revealing the sorption behavior and speciation of ions from 0.5–10 M [NaOH]. As inner-sphere complexes, Na+ primarily coordinates to the side of the gibbsite hexagonal cavities, while OH accepts hydrogen-bonding from the surface-OH groups. The mobility of inner-sphere Na+ and OH ions is significantly reduced due to a strong surface affinity in comparison to previous reports of NaCl, CaCl2, or BaCl2 electrolytes. At high [NaOH], contact ion pairing that is observed in the bulk solution is partially disrupted upon sorption to the gibbsite surface by the individual ion–surface interactions. The molecular-scale changes to surface speciation and competition between ion–surface vs. ion–ion interactions influence surface characterization of gibbsite and potential dissolution processes, providing a valuable baseline for starting conditions needed within future reactive molecular simulations.
alkaline solutions, IDREAM, gibbsite, molecular dy↗
The symmetric quasi-classical model using on-the-fly time-dependent density functional theory within the Tamm–Dancoff approximation
The primary computational challenge when simulating nonadiabatic ab initio molecular dynamics is the unfavourable compute costs of electronic structure calculations with molecular size. Simple electronic structure theories, like time-dependent density functional theory within the Tamm–Dancoff approximation (TDDFT/TDA), alleviate this cost for moderately sized molecular systems simulated on realistic time scales. Although TDDFT/TDA does have some limitations in accuracy, an appealing feature is that, in addition to including electron correlation through the use of a density functional, the cost of calculating analytic nuclear gradients and nonadiabatic coupling vectors is often computationally feasible even for moderately sized basis sets. Here in this work, some of the benefits and limitations of TDDFT/TDA are discussed and analysed with regard to its applicability as a ‘back-end’ electronic structure method for the symmetric quasi-classical Meyer–Miller model (SQC/MM). In order to investigate the benefits and limitations of TDDFT/TDA, SQC/MM is employed to predict and analyse a prototypical example of excited-state hydrogen transfer in gas-phase malonaldehyde. Then, the ring-opening dynamics of selenophene are simulated, which highlight some of the deficiencies of TDDFT/TDA. Additionally, some new algorithms are proposed that speed up the calculation of analytic nuclear gradients and nonadiabatic coupling vectors for a set of excited electronic states.
molecular dynamics↗
Combined molecular and spin dynamics simulation of BCC iron with vacancy defects
Utilizing an atomistic computational model, which handles both translational and spin degrees of freedom, combined molecular and spin dynamics simulations have been performed to investigate the effect of vacancy defects on spin wave excitations in ferromagnetic iron. Fourier transforms of space- and time-displaced correlation functions yield the dynamic structure factor, providing characteristic frequencies and lifetimes of the spin wave modes. A comparison of the system with a 5% vacancy concentration with pure lattice data shows a decrease in frequency and a decrease in lifetime for all transverse spin wave excitations observed. In addition, the clearly defined transverse spin wave excitations are distorted with the introduction of vacancy defects, and we observe reduced excitation lifetimes due to increased magnon–magnon scattering. We observe further evidence of increased magnon–magnon scattering, as the peaks in the longitudinal spin wave spectrum become less distinct. Finally, similar impacts are observed in the vibrational subsystem, with a decrease in characteristic phonon frequency and flattening of lattice excitation signals due to vacancy defects.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Superhydrophilicity of $α$-alumina surfaces results from tight binding of interfacial waters to specific aluminols
Understanding the microscopic driving force of water wetting is challenging and important for design of materials. The relations between structure, dynamics and hydrogen bonds of interfacial water can be investigated using molecular dynamics simulations. Here, contact angles at the alumina (0001) and ($11\bar{2}0$) surfaces are studied using both classical molecular dynamics simulations and experiments. To test the superhydrophilicity, the free energy cost of removing waters near the interfaces are calculated using the density fluctuations method. The strength of hydrogen bonds is determined by their lifetime and geometry. Both surfaces are superhydrophilic and the (0001) surface is more hydrophilic. Interactions between surfaces and interfacial waters promote a templating effect whereby the latter are aligned in a pattern that follows the underlying lattice of the surfaces. Translational and rotational dynamics of interfacial water molecules are slower than in bulk water. Hydrogen bonds between water and both surfaces are asymmetric, water-to-aluminol ones are stronger than aluminol-to-water ones. Molecular dynamics simulations eliminate the impacts of surface contamination when measuring contact angles and the results reveal the microscopic origin of the macroscopic superhydrophilicity of alumina surfaces: strong water-to-aluminol hydrogen bonds.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Rare Earth and Transition Metal Containing Glasses
Transition metal (TM) and rare earth (RE) ions have been incorporated into many glass systems such as silicate, phosphate, and borosilicate-based oxide glasses, as well as in halide and chalcogenide glasses, that find applications ranging from optical, photonic, and magnetic devices, solid-state battery, to nuclear waste disposal. Understanding the structural role of RE and TM in these glasses can help to develop glass compositions for targeted applications with either high-optical emission efficiency, electrical conductivity, or chemical durability. In this chapter, we first provide a general introduction of the applications and structural features of RE and TM in glasses, then the critical aspects of molecular dynamics (MD) simulations of these glasses such as interatomic potentials, structural analysis tools to study RE and TM ions in glasses and their clustering behaviors, Quantitative Structure–Property Analysis (QSPR), diffusion and dynamic property calculations, and electronic structure calculations to understand electronic defects such as charge trapping and radiation effects are introduced. Three representative case studies are presented: the first one is on MD simulations of erbium- and europium-doped silica and silicate glasses, as well as cerium doped aluminophosphate glasses, that revealed the effect of glass composition on RE ion local structure and clustering behavior. Electronic structure calculations of cerium-doped glass show how the existence of multioxidation states help to mediate radiation-induced damages caused by excited electron–hole pairs was also discussed. The second one focuses on alkali vanadophosphate glasses where the existence of two vanadium oxidation states help to provide electronic conduction in the glasses while alkali ions provide ionic conduction. MD simulations were used to understand vanadium environments and other structural aspects in the phosphate glasses, as well as the ionic transport behaviors of alkali ions. The third case study is on zirconium-containing borosilicate and aluminosilicate glasses that find wide applications in nuclear waste disposal. MD simulations help to provide structural details of zirconium ions that are validated by diffraction and EXAFS spectra. The structural information was used to interpret changes of mechanical properties and chemical durability by using QSPR and other analyses-based MD-generated structure models.
Du, Jincheng↗
Computational methods in solution-based plastics purification
Plastic waste can be recycled into resins with near-virgin properties by solution-based purification processes that selectively dissolve polymers, remove contaminants, or detach printing residues. Here, in this review, we examine computational methods for predicting the behavior governing solution-based plastic purification, motivated by the vast polymer–solvent–contaminant compositional space. We discuss thermodynamic and machine learning methods for predicting polymer–solvent and polymer–contaminant interaction and review physics-based molecular dynamics simulations that resolve molecular-scale phenomena within polymer matrices inaccessible to screening methods. We highlight how these methods have informed experimental design for dissolution-based recycling and solvent-based contaminant removal. Finally, we discuss the prospective role of agentic AI in integrating these computational tools with real-time sorting data to adapt purification conditions to the compositional variability of real post-consumer feedstocks. This review charts a path toward computationally guided solution-based purification workflows that can respond to the complexity inherent in plastic waste streams.
Altamimi, Ali [Univ. of Wisconsin, Madison, WI (Un↗
Molecular-level understanding of gibbsite particle aggregation in water
Using molecular dynamics simulations, we investigate the molecular scale origin of crystal face selectivity when one gibbsite particle attaches to another in water. A comparison of the free energy per unit surface area of particle–particle attachment indicates that particle attachment through edge surfaces, where the edge surfaces are either (1 0 0) or (1 1 0) crystal faces, is more energetically favorable compared to attachment between two basal surfaces (i.e., (0 0 1) crystal faces) or between the basal surface of one particle and the edge surface of another. This result suggests that gibbsite crystals with low basal/edge surface area ratio will preferentially attach through edge surfaces, potentially helping the crystals grow laterally. However, for larger gibbsite particles (high basal/edge surface area ratio) the total free energy, not normalized by surface area, of particle attachment through the basal surfaces is lower (more negative) than attachment through the edge surfaces, indicating that larger gibbsite particles will preferentially aggregate through basal surface attachments. The short-range electrostatic interactions including the interparticle hydrogen bonds from surface –OH groups drive particle attachment, and the dominant contribution to the free energy minimum is enthalpic rather than entropic. However, the enthalpy of basal-edge attachment is significantly offset by the entropy leading to a higher free energy (less negative) compared to that of basal-basal attachment. Study of the free energy for a few imperfect attachments of two particles indicates a higher free energy (i.e., less negative, less stable), compared to a perfect attachment
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Free Energy and Flexibility Analysis of Autoinhibited Human BRAF
The RAF serine/threonine protein kinases function as direct effectors of RAS in the intracellular transmission of extracellular growth signals, and they are key targets for drug discovery, given the high incidence of oncogenic mutations in RAF and other components of this signaling pathway. In its inactive state, RAF is held in an autoinhibited conformation in the cytosol through a combination of intramolecular interactions and binding to a regulatory 14−3−3 protein dimer. Activation of RAF is initiated by its interaction with membrane-localized GTP-bound RAS, which induces conformational changes that release RAF from its autoinhibited state. However, the molecular mechanisms governing RAF activation remain incomplete, largely due to the challenges in experimentally capturing the intermediate conformational states in this process. To address this gap, we developed a comprehensive all-atom model of BRAF based on existing cryo-EM structures. Using this model, we performed extensive molecular dynamics simulations to evaluate the stability and free energy landscape of autoinhibited BRAF in solution. Our analysis reveals conformational flexibility within the autoinhibited complex, suggesting that this dynamic behavior may play a role in facilitating BRAF activation upon engagement with the membrane-bound RAS.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach
Abstract Although multiple oxide-based solid electrolyte materials with intrinsically high ionic conductivities have emerged, practical processing and synthesis routes introduce grain boundaries and other interfaces that can perturb primary conduction channels. To directly probe these effects, we demonstrate an efficient and general mesoscopic computational method capable of predicting effective ionic conductivity through a complex polycrystalline oxide-based solid electrolyte microstructure without relying on simplified equivalent circuit description. We parameterize the framework for Li 7- x La 3 Zr 2 O 12 (LLZO) garnet solid electrolyte by combining synthetic microstructures from phase-field simulations with diffusivities from molecular dynamics simulations of ordered and disordered systems. Systematically designed simulations reveal an interdependence between atomistic and mesoscopic microstructural impacts on the effective ionic conductivity of polycrystalline LLZO, quantified by newly defined metrics that characterize the complex ionic transport mechanism. Our results provide fundamental understanding of the physical origins of the reported variability in ionic conductivities based on an extensive analysis of literature data, while simultaneously outlining practical design guidance for achieving desired ionic transport properties based on conditions for which sensitivity to microstructural features is highest. Additional implications of our results are discussed, including a possible connection between ion conduction behavior and dendrite formation.
25 ENERGY STORAGE↗