Water-In-Salt LiTFSI Aqueous Electrolytes (2): Transport Properties and Li+ Dynamics Based on Molecular Dynamics Simulations
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Zhang, Yong↗
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Structure, Dynamics, and Hydrogen Transport in Amorphous Polymers: An Analysis of the Interplay between Free Volume Element Distribution and Local Segmental Dynamics from Molecular Dynamics Simulations
Polymers are attractive membrane materials owing to their mechanical robustness and relatively inexpensive fabrication. An important indicator of membrane performance are free volume elements (FVE): microporous void spaces created by the inefficient packing of bulky groups along the polymer chain. FVEs tend to degrade over time, as polymer chains reorganize irreversibly. While it is widely accepted that polymer flexibility has an impact on membrane transport properties, the molecular nature of this impact is still not well understood. By the establishment of a correlation between local chain dynamics and the distribution of free volume elements (FVEs), penetrant transport can be regulated more efficiently in amorphous polymer membranes. In this work, we implement all-atom molecular dynamics (MD) simulations to explore the relationship between chain dynamics and free volume in three polymers with different levels of backbone flexibility: polymethylpentene (PMP), polystyrene (PS), and HAB-6FDA thermally rearranged polymer (TRP). We construct these polymers at different temperatures and examine how temperature impacts the FVE distribution and segmental mobility. Our analysis shows that chain segments near FVEs have higher mobility compared with the atoms in the bulk; the extent of this difference increases with chain flexibility. Increasing the chain flexibility by increasing the temperature results in a broader FVE distribution. Rigid polymers such as TRP show the most robust FVE distribution and are not significantly affected by the temperature change. To capture penetrant diffusion through the polymer matrix, hydrogen is inserted and the diffusion is measured at different temperatures; hydrogen mobility is influenced by the FVE structure and overall mobility of polymer chains. Lastly, at low temperatures, hydrogen mobility is influenced by void distribution, while at high temperatures, polymer dynamics dictate hydrogen transport.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Modeling graphene sheet growth and dynamical matrix calculations using molecular dynamics
Molecular dynamics (MD) has been an incredibly useful tool to model physical processes that were synthesized experimentally but not fully understood. MD, through the use of semi-empirical inter-atomic potentials, has allowed understanding of different physical processes in materials science. Yet as well as providing useful insights into materials science, molecular dynamics has a wider range of usability. In this report, I will be detailing how MD can be used to study graphene formation from a carbon liquid which requires high temperatures and pressures. Beyond this, I will describe the usefulness of MD for understanding the physics for phonon transport quantum sensors. To do this, MD was employed to determine the dynamical matrix by treating atoms as coupled oscillators. An accurate understanding of the dynamical matrix of a system is required to calculate the non-equilibrium Green’s function used to describe the phonon transport within phonon wave-guides. I found that, across multiple pressures and temperatures, randomly placed carbon atoms will show evidence of pent-first formation with semi-empirical models. Density functional theory (DFT), on the other hand, was too computationally expensive to use for full scale MD simulations, but we have the possibility of training a machine learned interatomic potential to approximate DFT for carbon in the environments being studied for pent-first graphene sheet formation.
36 MATERIALS SCIENCE↗
Score Dynamics: Scaling Molecular Dynamics with Picoseconds Time Steps via Conditional Diffusion Model
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Cross-scale matching: Dislocation Dynamics vs Molecular Dynamics
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Materials science↗
Molecular Dynamical and Quantum Mechanical Exploration of the Site-Specific Dynamics of Cy3 Dimers Internally Linked to dsDNA
Performing spectroscopic measurements on biomolecules labeled with fluorescent probes is a powerful approach to locating the molecular behavior and dynamics of large systems at specific sites within their local environments. The indocarbocyanine dye Cy3 has emerged as one of the most commonly used chromophores. The incorporation of Cy3 dimers into DNA enhances experimental resolution owing to the spectral characteristics influenced by the geometric orientation of excitonically coupled monomeric units. Various theoretical models and simulations have been utilized to aid in the interpretation of the experimental spectra. In this study, we employ all-atom molecular dynamics simulations to study the structural dynamics of Cy3 dimers internally linked to the dsDNA backbone. We used quantum mechanical calculations to derive insights from both the linear absorption spectra and the circular dichroism data. Furthermore, we explore potential limitations within a commonly used force field for cyanine dyes. The molecular dynamics simulations suggest the presence of four possible Cy3 dimeric populations. The spectral simulations on the four populations show one of them to agree better with the experimental signatures, suggesting it to be the dominant population. Furthermore, the relative orientation of Cy3 in this population compares very well with previous predictions from the Holstein–Frenkel Hamiltonian model.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Probing Accuracy-Speedup Tradeoff in Machine Learning Surrogates for Molecular Dynamics Simulations
The performance promise of machine learning surrogates of molecular dynamics simulations of soft materials is significant but generally comes at the cost of acquiring large training datasets to learn the complex relationships between input soft material attributes and output properties. Under the constraint of limited high-performance computing resources, optimizing the size of the training datasets becomes paramount. Using an artificial neural network based surrogate for molecular dynamics simulations of confined electrolytes, we explore the tradeoff between surrogate accuracy and computational gains. Accuracy is assessed by computing the root-mean-square errors between the surrogate predictions and the ground truth results obtained via molecular dynamics simulations. The computational performance is judged by evaluating the speedup which incorporates the training dataset creation time. Improvement in accuracy occurs with a loss of speedup, which scales as the inverse of the training dataset size. Furthermore, the link between surrogate generalizability and the accuracy-speedup tradeoff is assessed by examining the errors incurred in surrogate predictions on unseen, interpolated input variables and developing a net speedup metric to capture the associated gains.
Anions↗
Rotational and translational diffusion of liquid n-hexane: EFP-based molecular dynamics analysis
Molecular Dynamics (MD) simulations based on the Effective Fragment Potential (EFP) method are utilized to provide a comprehensive assessment of diffusion in liquid n-hexane. We decompose translational diffusion into components along and orthogonal to the long axis of the molecule. Rotational diffusion is decomposed into tumbling and spinning motions about this axis. Our analysis yields four corresponding diffusion coefficients which are related to diagonal entries in the complete 6 × 6 diffusion tensor accounting for the three rotational and three translational degrees of freedom and for the potential coupling between them. However, coupling between different degrees of freedom is expected to be minimal for a natural choice of the molecular body-fixed axis, so then off-diagonal entries in the tensor are negligible. This expectation is supported by a hydrodynamic analysis of the diffusion tensor which treats the liquid surrounding the molecule being tracked as a viscous continuum. Thus, the EFP MD analysis provides a comprehensive characterization of diffusion and also reveals expected shortcomings of the hydrodynamic treatment, particularly for rotational diffusion, when applied to neat liquids.
74 ATOMIC AND MOLECULAR PHYSICS↗
Path Integrals for Nonadiabatic Dynamics: Multistate Ring Polymer Molecular Dynamics
This review focuses on a recent class of path-integral-based methods for the simulation of nonadiabatic dynamics in the condensed phase using only classical molecular dynamics trajectories in an extended phase space. Specifically, a semiclassical mapping protocol is used to derive an exact, continuous, Cartesian variable path-integral representation for the canonical partition function of a system in which multiple electronic states are coupled to nuclear degrees of freedom. Building on this exact statistical foundation, multistate ring polymer molecular dynamics methods are developed for the approximate calculation of real-time thermal correlation functions. As a result, the remarkable promise of these multistate ring polymer methods, their successful applications, and their limitations are discussed in detail.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Ab initio molecular dynamics simulation of Nd3+ incorporation in calcite
Trivalent rare-earth elements (REEs) readily incorporate in Ca-bearing minerals such as calcite (CaCO3), a phenomenon with important implications for the use of REEs as biogeochemical tracers as well as for environmental remediation. Despite substantial efforts, determining the incorporation modes of trivalent REEs in calcite has remained challenging due to their presence in multiple coordination environments. This is particularly problematic for the interpretation of extended X-ray absorption fine structure (EXAFS) spectroscopy. In this work, ab initio molecular dynamics (AIMD) simulations of Nd3+ incorporated in calcite were performed to resolve its incorporation modes. Nd3+ and Ca2+ have very similar ionic radii but the additional positive charge requires a charge compensation scheme (CCS). Five CCSs were considered in AIMD simulations, and the resulting atomic trajectories were then used to compute EXAFS spectra for direct fitting to a published experimental spectrum. The results of the fits indicated that Nd3+ incorporates at the Ca2+ site in calcite in a mixture of six- and seven-fold coordination environments and through three main incorporation modes: associated with a protonated nearest-neighbor Ca2+ vacancy, incorporated as NdOH2+, and charge compensated by a remote species (on the spatial scale probed by EXAFS). The incorporation of Nd3+ in calcite via multiple modes was consistent with previous work, but the AIMD-EXAFS approach allowed for resolving the nature, proportion, and structure of the different coordination environments.
Kerisit, Sebastien N.↗
Ab Initio Molecular Dynamics Simulations of Amorphous Calcium Carbonate: Interpretation of Pair Distribution Function and X-Ray Absorption Spectroscopy Data
The structure and transformation of hydrous amorphous calcium carbonate (ACC) are key to understanding biomineralization pathways and their relationship with the properties of the resulting material. Quantitative interpretation of scattering experiments aimed at elucidating the structure of ACC is challenging, due to the amorphous nature of this material, and, therefore, requires models for the structure and the scattering physics. Here, we generate physically realistic ensembles of hydrated ACC structures and their vibrational disorder from ab initio molecular dynamics (AIMD) simulations with an emphasis on enabling the consistent interpretation of the finer details of three complementary structural probes: neutron and x-ray pair distribution experiments and x-ray absorption spectroscopy (XAS). In each case, we simulate the signal directly in reciprocal space and then manipulate it into the real-space pair distribution function (PDF) or spectrum using the same procedures for the experimental and theoretical data. Good agreement with experiment was obtained across the three techniques with the simulations accounting well for all features in the spectra. Remaining small discrepancies pointed to differences between real samples and the idealized simulated systems such as deviations from the nominal CaCO3·nH2O stoichiometry. Additionally, the simulations offered a more accurate description of the local coordination environment of calcium than previous shell-by-shell fits to spectra of synthetic ACC and classical molecular dynamics simulations. This work demonstrates that AIMD is a powerful approach for extracting detailed structural information from neutron PDF, x-ray PDF, and XAS of amorphous carbonate phases.
Prange, Micah P.↗
Predicting the Dissolution Rate of Borosilicate Glasses using QSPR analysis based on molecular dynamics simulations
Quantitative Structure Property Relationship (QSPR) analysis based on molecular dynamics (MD) simulations is a promising approach for establishing the composition-property relationships of glass and other materials with complex structures. A series of 20 borosilicate and boroaluminosilicate glasses have been modeled by using MD simulations with recently developed effective potentials. Short- and medium-range structures of these glasses were analyzed and, based on these structural information, QSPR analysis of the initial dissolution rate (r0) was made and compared with measured r0 at 90°C and pH 9 using various structural descriptors such as percentage of bridging oxygen species, network connectivity and average ring size. The structural descriptors, Fnet, containing energetic information such as single bond strength and other structural information were also used. It was found that overall network connectivity, average ring size and Fnet give reasonable predictions of the r0 of studied glasses, given the conditions that the glasses are homogeneous and dissolve congruently. Modifying glass compositions to account preferential release of modifiers gives a better prediction for incongruently dissolving glasses. The results were compared with our recent work of predicting glass dissolution behavior from compositions using the topological-constraints-based models.
Du, Jincheng↗
Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture
Abstract Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li 7 P 3 S 11 , a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.
Chemistry↗
Atomic Diffusion, Segregation, and Grain Boundary Migration in Nickel-Based Alloys from Molecular Dynamics Simulations
Grain boundary diffusion and metal mobility in alloys control material performance in many applications and yet remain poorly understood at a mechanistic level. With advances in accessible time and length scales for computational molecular simulations, and recent force field developments, we now possess tools to help unravel those mechanisms. Using large-scale molecular dynamics simulations, here we examined vacancy-mediated diffusion processes in Ni-5Cr alloy with low and high-energy grain boundaries. We show that atomic diffusion inside the grain boundary plane is about four times higher than bulk diffusion, at any temperature, and exhibits a typical Arrhenius behavior with a very small energy barrier (0~.8 eV for Cr and 0.7 eV for Ni within 1300-1600 K). Additionally, the fastest diffusing species inverts; Cr diffusion was faster than Ni in the bulk but slower in the grain boundaries. This is attributed to the creation of high cohesive energy clusters of Cr at the grain boundary. Grain boundary migration was also observed to be temperature dependent and appears to be two times higher in the 5% Cr alloy than in pure Ni, highlighting the important role of the alloying element on grain boundary motion.
Simonnin, Pauline GN↗
Reactive Molecular Dynamics Simulations and Quantum Chemistry Calculations To Investigate Soot-Relevant Reaction Pathways for Hexylamine Isomers
Sooting tendencies of a series of nitrogen-containing hydrocarbons (NHCs) have been recently characterized experimentally using the yield sooting index (YSI) methodology. This work aims to identify soot-relevant reaction pathways for three selected C6H15N amines, namely, dipropylamine (DPA), diisopropylamine (DIPA), and 3,3-dimethylbutylamine (DMBA) using ReaxFF molecular dynamics (MD) simulations and quantum mechanical (QM) calculations and to interpret the experimentally observed trends. ReaxFF MD simulations are performed to determine the important intermediate species and radicals involved in the fuel decomposition and soot formation processes. QM calculations are employed to extensively search for chemical reactions involving these species and radicals based on the ReaxFF MD results and also to quantitatively characterize the potential energy surfaces. Specifically, ReaxFF simulations are carried out in the NVT ensemble at 1400, 1600, and 1800 K, where soot has been identified to form in the YSI experiment. These simulations account for the interactions among test fuel molecules and pre-existing radicals and intermediate species generated from rich methane combustion, using a recently proposed simulation framework. ReaxFF simulations predict that the reactivity of the amines decrease in the order DIPA > DPA > DMBA, independent of temperature. Both QM calculations and ReaxFF simulations predict that C2H4, C3H6, and C4H8 are the main nonaromatic soot precursors formed during the decomposition of DPA, DIPA, and DMBA, respectively, and the associated reaction pathways are identified for each amine. Both theoretical methods predict that sooting tendency increases in the order DPA, DIPA, and DMBA, consistent with the experimentally measured trend in YSI. This work demonstrates that sooting tendencies and soot-relevant reaction pathways of fuels with unknown chemical kinetics can be identified efficiently through combined ReaxFF and QM simulations. Overall, predictions from ReaxFF simulations and QM calculations are consistent, in terms of fuel reactivity, major intermediates, and major nonaromatic soot precursors.
fuel decomposition↗
InteraChem: Virtual Reality Visualizer for Reactive Interactive Molecular Dynamics
Interactive molecular dynamics in virtual reality (IMD-VR) simulations provide a digital molecular playground for students as an alternative or complement to traditional molecular modeling kits or 2D illustrations. Previous IMD-VR studies have used molecular mechanics to enable simulations of macromolecules such as proteins and nanostructures for the classroom setting with considerable success. Here, we present the InteraChem molecular visualizer, intended for reactive IMD-VR simulation using semiempirical and ab initio methods. InteraChem visualizes not only the molecular geometry but also (1) isosurfaces such as molecular orbitals and electrostatic potentials and (2) two-dimensional graphs of time-varying simulation quantities such as kinetic/potential energy, internal coordinates, and user-applied force. Additionally, InteraChem employs speech recognition to facilitate user interaction and introduces a novel “atom happiness” visualization using emojis to indicate the energetic feasibility of a particular bonding arrangement. Furthermore, we include a set of accompanying exercises that we have used to teach chemical reactivity in small molecular systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Integrating solvation shell structure in experimentally driven molecular dynamics using x-ray solution scattering data
In the past few decades, prediction of macromolecular structures beyond the native conformation has been aided by the development of molecular dynamics (MD) protocols aimed at exploration of the energetic landscape of proteins. Yet, the computed structures do not always agree with experimental observables, calling for further development of the MD strategies to bring the computations and experiments closer together. Here, we report a scalable, efficient MD simulation approach that incorporates an x-ray solution scattering signal as a driving force for the conformational search of stable structural configurations outside of the native basin. We further demonstrate the importance of inclusion of the hydration layer effect for a precise description of the processes involving large changes in the solvent exposed area, such as unfolding. Utilization of the graphics processing unit allows for an efficient all-atom calculation of scattering patterns on-the-fly, even for large biomolecules, resulting in a speed-up of the calculation of the associated driving force. The utility of the methodology is demonstrated on two model protein systems, the structural transition of lysine-, arginine-, ornithine-binding protein and the folding of deca-alanine. We discuss how the present approach will aid in the interpretation of dynamical scattering experiments on protein folding and association.
Hsu, Darren J.↗