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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Exploring the Structural, Dynamic, and Functional Properties of Metal–Organic Frameworks through Molecular Modeling

This review spotlights the role of atomic-level modeling in research on metal-organic frameworks (MOFs), especially the key methodologies of density functional theory (DFT), Monte Carlo (MC) simulations, and molecular dynamics (MD) simulations. The discussion focuses on how periodic and cluster-based DFT calculations can provide novel insights into MOF properties, with a focus on predicting structural transformations, understanding thermodynamic properties and catalysis, and providing information or properties that are fed into classical simulations such as force field parameters or partial charges. Classical simulation methods, highlighting force field selection, databases of MOFs for high-throughput screening, and the synergistic nature of MC and MD simulations, are described. By predicting equilibrium thermodynamic and dynamic properties, these methods offer a wide perspective on MOF behavior and mechanisms. Additionally, the incorporation of machine learning (ML) techniques into quantum and classical simulations is discussed. These methods can enhance accuracy, expedite simulation setup, reduce computational costs, as well as predict key parameters, optimize geometries, and estimate MOF stability. By charting the growth and promise of computational research in the MOF field, the aim is to provide insights and recommendations to facilitate the incorporation of computational modeling more broadly into MOF research.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure–function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Finally, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Building a DFT+U machine learning interatomic potential for uranium dioxide

Despite uranium dioxide (UO 2 ) being a widely used nuclear fuel, fuel performance models rely extensively on empirical correlations of material behavior, leveraging the historical operating experience of UO 2 . Mechanistic models that consider an atomistic understanding of the processes governing fuel performance (such as fission gas release and creep) will enable a better description of fuel behavior under non-prototypical conditions such as in new reactor concepts or for modified UO 2 fuel compositions. To this end, molecular dynamics simulation is a powerful tool for rapidly predicting physical properties of proposed fuel candidates. However, the reliability of these simulations depends largely on the accuracy of the atomic forces. Traditionally, these forces are computed using either a classical force field (FF) or density functional theory (DFT). While DFT is relatively accurate, the computational cost is burdensome, especially for f-electron elements, such as actinides. By contrast, classical FFs are computationally efficient but are less accurate. For these reasons, we report a new accurate machine learning interatomic potential (MLIP) for UO 2 that provides high-fidelity reproduction of DFT forces at a similar low cost to classical FFs. We employ an active learning approach that autonomously augments the DFT training data set to iteratively refine the MLIP. To further improve the quality of our predictions, we utilize transfer learning to retrain our MLIP to higher-accuracy DFT+U data. We validate our MLIPs by comparing predicted physical properties (e.g., thermal expansion and elastic properties) with those from existing classical FFs and DFT/DFT+U calculations, as well as with experimental data when available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Release dynamics of nanodiamonds created by laser-driven shock-compression of polyethylene terephthalate

Laser-driven dynamic compression experiments of plastic materials have found surprisingly fast formation of nanodiamonds (ND) via X-ray probing. This mechanism is relevant for planetary models, but could also open efficient synthesis routes for tailored NDs. We investigate the release mechanics of compressed NDs by molecular dynamics simulation of the isotropic expansion of finite size diamond from different P-T states. Analysing the structural integrity along different release paths via molecular dynamic simulations, we found substantial disintegration rates upon shock release, increasing with the on-Hugnoiot shock temperature. We also find that recrystallization can occur after the expansion and hence during the release, depending on subsequent cooling mechanisms. Our study suggests higher ND recovery rates from off-Hugoniot states, e.g., via double-shocks, due to faster cooling. Laser-driven shock compression experiments of polyethylene terephthalate (PET) samples with in situ X-ray probing at the simulated conditions found diamond signal that persists up to 11 ns after breakout. In the diffraction pattern, we observed peak shifts, which we attribute to thermal expansion of the NDs and thus a total release of pressure, which indicates the stability of the released NDs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Scale and rate in CdS pressure-induced phase transition

Here, we describe recent efforts to improve our predictive modeling of rate-dependent behavior at, or near, a phase transition using molecular dynamics simulations. Cadmium sulfide (CdS) is a well-studied material that undergoes a solid-solid phase transition from wurtzite to rock salt structures between 3 and 9 GPa. Atomistic simulations are used to investigate the dominant transition mechanisms as a function of orientation, size and rate. We found that the final rock salt orientations were determined relative to the initial wurtzite orientation, and that these orientations were different for the two orientations and two pressure regimes studied. The CdS solid-solid phase transition is studied, for both a bulk single crystal and for polymer-encapsulated spherical nanoparticles of various sizes.

42 ENGINEERING↗
DOE OSTI2022

A mini-TGA protein modulates gene expression through heterogeneous association with transcription factors

Abstract TGA (TGACG-binding) transcription factors, which bind their target DNA through a conserved basic region leucine zipper (bZIP) domain, are vital regulators of gene expression in salicylic acid (SA)-mediated plant immunity. Here, we investigated the role of StTGA2.1, a potato (Solanum tuberosum) TGA lacking the full bZIP, which we named a mini-TGA. Such truncated proteins have been widely assigned as loss-of-function mutants. We, however, confirmed that StTGA2.1 overexpression compensates for SA-deficiency, indicating a distinct mechanism of action compared with model plant species. To understand the underlying mechanisms, we showed that StTGA2.1 can physically interact with StTGA2.2 and StTGA2.3, while its interaction with DNA was not detected. We investigated the changes in transcriptional regulation due to StTGA2.1 overexpression, identifying direct and indirect target genes. Using in planta transactivation assays, we confirmed that StTGA2.1 interacts with StTGA2.3 to activate StPRX07, a member of class III peroxidases (StPRX), which are known to play role in immune response. Finally, via structural modeling and molecular dynamics simulations, we hypothesized that the compact molecular architecture of StTGA2.1 distorts DNA conformation upon heterodimer binding to enable transcriptional activation. This study demonstrates how protein truncation can lead to distinct functions and that such events should be studied carefully in other protein families.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

PySpawn: Software for Nonadiabatic Quantum Molecular Dynamics

The ab initio multiple spawning (AIMS) method enables nonadiabatic quantum molecular dynamics simulations in an arbitrary number of dimensions, with potential energy surfaces provided by electronic structure calculations performed on-the-fly. However, the intricacy of the AIMS algorithm complicates software development, deployment on modern shared computer resources, and post-simulation data analysis. PySpawn is a nonadiabatic molecular dynamics software package that addresses these issues. Here, the program is designed to be easily interfaced with electronic structure software, and an interface to the TeraChem software package is described here. PySpawn introduces a task-based reorganization of the AIMS algorithm, allowing fine-grained restart capability and setting the stage for efficient parallelization in a future release. PySpawn includes a user-friendly and interactive Python analysis module that will enable novice users to painlessly adopt AIMS. As a demonstration of PySpawn’s simulation capability and analysis module, we report complete active space self-consistent field–based AIMS simulations of the 1,2- dithienyl-1,2-dicyanoethene molecule, a promising molecular photoswitch.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Structure and Dynamics of CO 2 at the Air–Water Interface from Classical and Neural Network Potentials

The accurate description of the structure and dynamics of CO 2 at the instantaneous air–water interface, along with the effects of surface fluctuations on the CO 2 -transport processes, is essential for the development of negative emission technologies aimed at minimizing climate change. In this study, we performed molecular dynamics simulations of CO 2 at the air–water interface using neural network potentials (NNPs) trained on ab initio data generated through density-functional-theory-based molecular dynamics simulations. We compared these results with classical force fields to assess their performance in modeling interfacial CO 2 behavior. Our findings revealed that the asymmetric interactions, coupled with thermal surface fluctuations at the air–water interface, significantly influence CO 2 transport into the aqueous phase. The simulations demonstrate that classical force fields underestimate both the free energy of CO 2 transport and the strength of its interactions at the interface compared with the neural network potentials. In conclusion, the free energy and the interfacial dynamics of CO 2 are primarily influenced by the distribution of water within the instantaneous interfacial water layer, responsible for creating an asymmetric intermolecular interaction environment within the interfacial region.

Ab initio molecular dynamics↗
DOE OSTI2020

Damage initiation and evolution in Al-Si layered microstructures under shock loading conditions at atomic scales

Designing materials with microstructural features like multiphase interfaces have shown significant promise for usage in the next generation defense and nuclear applications. The dynamic response of these interfaces in extreme environments is observed to vary with the deformability of individual phases, which could subsequently alter the favored damage nucleation sites related to spall failure. Here, we investigate the role of spacing of interfaces in a nanocrystalline layered Aluminum-Silicon system on the shock wave propagation behavior, and microstructural and defect evolution using classical molecular dynamics simulations. The simulations are carried out with different hypothetical Al/Si microstructures including variations in the distribution of Si grains as layers in a nanocrystalline Al matrix. The molecular dynamics simulations suggest that spall failure is preferentially initiated at Al/Si interfaces. In addition, for the same system volume and same concentration of Si, a higher number of layers is marked by an increase in shock wave velocity and reduced resistance to spall failure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Structural determinants of protocadherin-15 mechanics and function in hearing and balance perception

The vertebrate inner ear, responsible for hearing and balance, is able to sense minute mechanical stimuli originating from an extraordinarily broad range of sound frequencies and intensities or from head movements. Integral to these processes is the tip-link protein complex, which conveys force to open the inner-ear transduction channels that mediate sensory perception. Protocadherin-15 and cadherin-23, two atypically large cadherins with 11 and 27 extracellular cadherin (EC) repeats, are involved in deafness and balance disorders and assemble as parallel homodimers that interact to form the tip link. Here we report the X-ray crystal structure of a protocadherin-15 + cadherin-23 heterotetrameric complex at 2.9-Å resolution, depicting a parallel homodimer of protocadherin-15 EC1-3 molecules forming an antiparallel complex with two cadherin-23 EC1-2 molecules. In addition, we report structures for 10 protocadherin-15 fragments used to build complete high-resolution models of the monomeric protocadherin-15 ectodomain. Molecular dynamics simulations and validated crystal contacts are used to propose models for the complete extracellular protocadherin-15 parallel homodimer and the tip-link bond. Steered molecular dynamics simulations of these models suggest conditions in which a structurally diverse and multimodal protocadherin-15 ectodomain can act as a stiff or soft gating spring. These results reveal the structural determinants of tip-link–mediated inner-ear sensory perception and elucidate protocadherin-15’s structural and adhesive properties relevant in disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Long timescale solvation dynamics and confinement: The case of non-ionic deep eutectic solvents of lauric acid and N-methylacetamide

Microscopic segregation and molecular heterogeneities in complex liquids are the result of the interplay between different intermolecular forces, all of which contribute to the energy landscape of the system. A consequence of the intricate energy landscape is the nontrivial effect on the solvation dynamics. Here, the impact of molecular heterogeneities on the solvation dynamics is studied using infrared spectroscopies and molecular dynamics simulations. In particular, this study focuses on the dynamical effect of nanoscopic heterogeneities present in deep eutectic solvents (DESs) composed of lauric acid (LA) and N-methylacetamide (NMA). To this end, a molecular probe containing a carbon triple bond is used as an infrared reporter. The results show that the vibrational probe is likely to be located in the NMA polar domains. Furthermore, the probe solvation dynamics derived from the 2DIR spectra presents a slowdown of its timescale with increasing LA concentration in the DES. Kubo modeling of the probe solvation dynamics shows a correlation between the amplitude of its long time component and the presence of molecular heterogeneities in the sample. Semiclassical modeling of the vibrational line shape of the triple bond stretch demonstrates that the heterogeneities affect the whole solvation dynamics of the system through the amplitudes of the frequency fluctuations. Molecular dynamics simulations confirm the experimental results and their interpretation by showing a slowdown of the solvation dynamics when the LA heterogeneities are present. Overall, the study presents a molecular framework to explain the effect of confinement created by nanoscopic LA heterogeneities on the solvation dynamics of the system.

Chemical compounds↗
DOE OSTI2023

Machine learning predictions of diffusion in bulk and confined ionic liquids using simple descriptors

Ionic liquids have many intriguing properties and widespread applications such as separations and energy storage. However, ionic liquids are complex fluids and predicting their behavior is difficult, particularly in confined environments. We introduce fast and computationally efficient machine learning (ML) models that can predict diffusion coefficients and ionic conductivity of bulk and nanoconfined ionic liquids over a wide temperature range (350–500 K). The ML models are trained on molecular dynamics simulation data for 29 unique ionic liquids as bulk fluids and confined in graphite slit pores. This model is based on simple physical descriptors of the cations and anions such as molecular weight and surface area. Here, we also demonstrate that accurate results can be obtained using only descriptors derived from SMILES (simplified molecular-input line-entry system) codes for the ions with minimal computational effort. This offers a fast and efficient method for estimating diffusion and conductivity of nanoconfined ionic liquids at various temperatures without the need for expensive molecular dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Mean force kinetic theory applied to self-diffusion in supercritical Lennard-Jones fluids

A new kinetic-theory-based calculation of the self-diffusion coefficient for dense supercritical Lennard-Jones fluids is presented. The mean force kinetic theory, which was recently developed for transport in dense plasmas, is applied for the calculation of diffusion in dense neutral fluids. The calculation only requires the pair distribution function, a quantity that is readily calculable from equilibrium statistical mechanics for many systems, including the Lennard-Jones fluid. The self-diffusion coefficients are compared with calculations from molecular dynamics simulations, and good agreement at high density is demonstrated, even in the vicinity of the solid–fluid coexistence line. A comparison of different kinetic models with molecular dynamics simulations demonstrates that the transport coefficients have important contributions due to particle interaction via a potential of mean force and local correlations, which increase the collision rate. The new calculations compare well to those from free-volume theory and overcome a limitation of this theory that prevents its use in systems that interact via long range monotonic potentials. It is expected that this approach will also apply to other systems, including neutral-plasma and neutral-electrolyte mixtures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Ion-gated carbon molecular sieve gas separation membranes

Membrane technology lies at the heart of many industrial gas separation processes and applications. Molecular sieving membranes that break the Robeson limit are desirable for energy-efficient gas separation. In this paper, we report a facile strategy of directly integrating ionic liquids (ILs) into porous membranes. Particularly, the ILs form an ultra-thin layer on the carbon molecular sieve (CMS) membranes rather than penetrating into the pores, acting as a smart gate for gas entry to boost the selectivity. The hybrid membrane exhibits CO 2 permeability >600 barrer and enhanced CO 2 /N 2 selectivity >50, which surpasses the Robeson limit and shows potential in CO 2 /N 2 separation process. Molecular dynamics simulations confirm the gating effect of the IL layer of molecular thickness. In conclusion, this work demonstrates a universal strategy to improve CMS membrane performance by creating an IL-membrane interface and tuning the ion-pore interaction.

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

Effect of Grain Boundary Misorientation on Spall Strength in Ta via Shock-Free Simulations with Relatively Few Atoms

A suite of 37 molecular dynamics simulations is conducted at two system sizes to systematically characterize the role of grain boundary (GB) misorientation on spall strength in pure BCC tantalum (Ta). The systems studied consist of bicrystals with a single [110] symmetric tilt grain boundary. Two loading conditions are compared: (i) homogeneous extension under uniaxial strain simulated in this study and (ii) piston/flyer impact of sample, which induces heterogeneous deformation via shockwave propagation along the length of the sample. The piston/flyer impact is taken from the literature and run on the same set of GB misorientation angles using LAMMPS. The major finding here is that both methods result in similar spall strength predictions, but the homogeneous extension method generally requires two to three orders of magnitude fewer atoms and similar reductions in computational costs. Spall strength results systematically overpredict using this method, by about 10% for the dataset three orders of magnitude smaller than piston/flyer simulations, and 5% for the dataset two orders of magnitude smaller. Lastly, the effect of system size and pre-compression magnitude on spall strength is systematically characterized.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Anisotropic interactions for continuum modeling of protein–membrane systems

In this work, a model for anisotropic interactions between proteins and cellular membranes is proposed for large-scale continuum simulations. The framework of the model is based on dynamic density functional theory, which provides a formalism to describe the lipid densities within the membrane as continuum fields while still maintaining the fidelity of the underlying molecular interactions. Within this framework, we extend recent results to include the anisotropic effects of protein–lipid interactions. As applications, we consider two membrane proteins of biological interest: a RAS–RAF complex tethered to the membrane and a membrane embedded G protein-coupled receptor. A strong qualitative and quantitative agreement is found between the numerical results and the corresponding molecular dynamics simulations. Combining the scope of continuum level simulations with the details from molecular level particle simulations enables research into protein–membrane behaviors at a more biologically relevant scale, which crucially can also be accessed via experiment.

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

Ab initio molecular dynamics with enhanced sampling in heterogeneous catalysis

Ab initio molecular dynamics simulations combined with enhanced sampling techniques are becoming widespread methods to investigate chemical phenomena in catalytic systems. These techniques automatically include finite temperature effects, anharmonicity, and collective dynamics in their robust description of enthalpic and entropic contributions, which can have significant impact on reaction free energy landscapes. This contrasts with standard ab initio static approaches that are based on assessing reaction free energies from various coarse-grained descriptions of the reaction potential energy surface. Enhanced sampling ab initio molecular dynamics opens the way to first principles simulations of systems of increasing complexity like solid/liquid catalytic interfaces. Here, we aim at guiding the reader through the basis of these techniques, summarizing their fundamental theoretical and practical aspects, and reviewing the relevant literature in the field. After a brief introduction to the problem, we will illustrate the advantage of using molecular simulations to include finite temperature effects, examine the most common ab initio techniques currently in use, describe their application to solid state heterogeneous catalysts, and finally critically review the most popular enhanced sampling techniques used in computational catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Calculation of Non-Bonded Forces Due to Sliding of Bundled Carbon Nanotubes

An important consideration for load transfer in bundles of single-walled carbon nanotubes is the nonbonded (van der Waals) forces between the nanotubes and their effect on axial sliding of the nanotubes relative to each other. In this research, the non-bonded forces in a bundle of seven hexagonally packed (10,10) single-walled carbon nanotubes are represented as an axial force applied to the central nanotube. A simple model, based on momentum balance, is developed to describe the velocity response of the central nanotube to the applied force. The model is verified by comparing its velocity predictions with molecular dynamics simulations that were performed on the bundle with different force histories applied to the central nanotube. The model was found to quantitatively predict the nanotube velocities obtained from the molecular dynamics simulations. Both the model and the simulations predict a threshold force at which the nanotube releases from the bundle. This force converts to a shear yield strength of 10.5-11.0 MPa for (10,10) nanotubes in a bundle.

Frankland, S. J. V.↗