Hybrid Molecular Dynamics Simulations Research Articles

In Situ Oxidation Studies of High-Entropy Alloy Nanoparticles.

Although high-entropy alloys (HEAs) have shown tremendous potential for elevated temperature, anticorrosion, and catalysis applications, little is known on how HEA materials behave under complex service environments. Herein, we studied the high-temperature oxidation behavior of Fe0.28Co0.21Ni0.20Cu0.08Pt0.23HEA nanoparticles (NPs) in an atmospheric pressure dry air environment by in situ gas-cell transmission electron microscopy. It is found that the oxidation of HEA NPs is governed by Kirkendall effects with logarithmic oxidation rates rather than parabolic as predicted by Wagner's theory. Further, the HEA NPs are found to oxidize at a significantly slower rate compared to monometallic NPs. The outward diffusion of transition metals and formation of disordered oxide layer are observed in real time and confirmed through analytical energy dispersive spectroscopy, and electron energy loss spectroscopy characterizations. Localized ordered lattices are identified in the oxide, suggesting the formation of Fe2O3, CoO, NiO, and CuO crystallites in an overall disordered matrix. Hybrid Monte Carlo and molecular dynamics simulations based on first-principles energies and forces support these findings and show that the oxidation drives surface segregation of Fe, Co, Ni, and Cu, while Pt stays in the core region. The present work offers key insights into how HEA NPs behave under high-temperature oxidizing environment and sheds light on future design of highly stable alloys under complex service conditions.

Genetic algorithm-guided deep learning of grain boundary diagrams: Addressing the challenge of five degrees of freedom

Grain boundaries (GBs) often control the processing and properties of polycrystalline materials. Here, potentially transformative research is represented by constructing GB property diagrams as functions of temperature and bulk composition, also called “complexion diagrams,” as a general materials science tool on par with phase diagrams. However, a GB has five macroscopic (crystallographic) degrees of freedom (DOFs). It is essentially a “mission impossible” to construct property diagrams for GBs as a function of five DOFs by either experiments or modeling. Herein, we combine isobaric semi-grand canonical ensemble hybrid Monte Carlo and molecular dynamics (hybrid MC/MD) simulations with a genetic algorithm (GA) and deep neural network (DNN) models to tackle this grand challenge. The DNN prediction is ∼108 faster than atomistic simulations, thereby enabling the construction of the property diagrams for millions of distinctly different GBs of five DOFs. Notably, excellent prediction accuracies have been achieved for not only symmetric-tilt and twist GBs, but also asymmetric-tilt and mixed tilt-twist GBs; the latter are more complex and much less understood, but they are ubiquitous and often limit the performance properties of real polycrystals as the weak links. The data-driven prediction of GB properties as function of temperature, bulk composition, and five crystallographic DOFs (i.e., in a 7D space) opens a new paradigm.

Structure and dynamics of amphiphilic Janus spheres and spherocylinders under shear.

We study the structure formation and flow properties of colloidal dispersions comprised of Janus spheres, Janus spherocylinders, and their mixtures, using hybrid molecular dynamics simulations that take into account hydrodynamic interactions. We systematically vary the Janus balance and the shape anisotropy of the particles, and explore a range of colloid volume fractions in the liquid regime of the phase diagram. At rest, Janus spheres with small hydrophobic patches form spherical micelles for all investigated colloid concentrations. In contrast, Janus spheres with an entirely hydrophobic hemisphere aggregate to larger worm-like micelles and network-like structures. Janus spherocylinders exhibit a similar self-assembly behavior. At small and intermediate shear, we observe deformation and rearrangement of the micelles, accompanied by a Newtonian-like rheology with slightly higher shear viscosity compared to homoparticle dispersions at the same concentration. As the shear rate is increased further, the micelles eventually break up into small dimers and free particles, causing a distinct shear-thinning of the dispersions. The network-like structures exhibit a similar flow behavior at high shear rates, but for weak shear we find an almost threefold increase of the shear viscosity and a distinct shear-thinning behavior due to the fracturing of the intertwined networks. In general, we identify a strong correlation between the size of the aggregates and the rheology of the dispersions, allowing for the determination of dynamic properties solely based on structural information.

First-order grain boundary transformations in Au-doped Si: Hybrid Monte Carlo and molecular dynamics simulations verified by first-principles calculations

Hybrid Monte Carlo and molecular dynamics simulations (hybrid MC/MD) reveal the occurrence of first-order phase-like adsorption transformations in Au-doped Si twist grain boundary (GB) at low temperatures, which become continuous at high temperatures above a GB critical point. The predicted first-order GB transformations from nominally “clean” GBs to bilayer adsorption of Au are supported by a prior experiment. The hexagonal Au adsorption pattern predicted by the hybrid MC/MD simulation is further verified by first-principles calculations. Differential charge density maps indicate that strong charge transfer at the Au-doped Si GB. A GB complexion (interfacial phase) diagram is computed.

First-Order Interfacial Transformations with a Critical Point: Breaking the Symmetry at a Symmetric Tilt Grain Boundary.

First-order interfacial phaselike transformations that break the mirror symmetry of the symmetric ∑5 (210) tilt grain boundary (GB) are discovered by combining a modified genetic algorithm with hybrid MonteCarlo and molecular dynamics simulations. Density functional theory calculations confirm this prediction. This first-order coupled structural and adsorption transformation, which produces two variants of asymmetric bilayers, vanishes at an interfacial critical point. A GB complexion (phase) diagram is constructed via semigrand canonical ensemble atomistic simulations for the first time.

Topology-Sensitive Microfluidic Filter for Polymers of Varying Stiffness.

The separation of polymers based on their size, rigidity, and topology is an essential but also highly challenging task for nanoscience and engineering. Using hybrid molecular dynamics simulations that correctly take into account hydrodynamics, we have designed microfluidic channels for separating linear from ring polymers in dilute solutions. We establish that the transport velocity of the polymers is independent of their topology and rigidity when the channel walls are smooth and repulsive. However, when the walls are decorated with attractive spots arranged on lines parallel to the flow, ring polymers exhibit an order of magnitude higher transport velocity compared to linear chains. The spots induce a homeotropic-like reorientation of ring polymers close to walls leading to a tank treading motion along them, whereas linear chains are immobilized upon adsorption. This mechanism becomes more enhanced with increasing polymer rigidity. The presented technique holds thus promise for reliably separating nanoparticles based on their topology.

Equilibrium Dynamics and Shear Rheology of Semiflexible Polymers in Solution

We study the structure and dynamics of semidilute solutions of semiflexible polymers at rest and under shear using hybrid molecular dynamics simulations that take hydrodynamic interactions into account. We show that the polymer center-of-mass diffusion coefficient significantly decreases with increasing chain stiffness at fixed monomer density. The zero-shear viscosity shows a corresponding increase due to the intermolecular interactions of stiffer chains. We apply steady shear flow to the polymer solutions and show that at high shear rates the flow properties become almost independent of polymer stiffness. We characterize the polymer conformations under shear and find that in this regime polymers are elongated and aligned along the flow direction, but semiflexible polymers surprisingly form an increased number of hairpin-like conformations due to increased tumbling.

Dimeric anthracene-based mechanophore for damage precursor detection in epoxy-based thermoset polymer matrix: Characterization and atomistic modeling

The mechanochemical response of a dimeric anthracene-based mechanophore (force-sensitive molecule), embedded within a thermoset polymer matrix, is studied through characterization and atomistic modeling. The dimeric anthracene-based mechanophore (dimeric 9-anthracene carboxylic acid, Di-AC) synthesized through ultraviolet dimerization was successfully incorporated into an epoxy-based thermoset polymer matrix to detect damage precursors. Mechanical loading tests showed that the Di-AC embedded epoxy polymer is capable of detecting damage precursors via fluorescence emission that occurs immediately before the yield point. The sensitivity of the Di-AC to external stress, which enables the damage precursor detection, is verified through a comparative study of bond dissociation energies of mechanophores using atomistic simulations. A hybrid molecular dynamics (MD) simulation methodology, integrating a classical force-field and a bond-order based force-field, is used to simulate epoxy curing, investigate elastic moduli and yield strength/strain, and capture mechanophore activation. Local work analysis within the hybrid MD simulation methodology is conducted to capture the critical strain representing the initiation of mechanophore activation due to the deformation of Di-AC embedded epoxy polymer. The capability to detect damage precursor is observed through MD simulations by comparing the yield strain and the critical strain. Furthermore, the experimentally observed variation in yield strength due to the inclusion of Di-AC is accurately reproduced by the comparative study between two systems: neat epoxy and 5wt% Di-AC epoxy polymer, thus, validating the computational framework.

RMPCDMD: Simulations of Colloids with Coarse-grained Hydrodynamics, Chemical Reactions and External Fields

The RMPCDMD software package performs hybrid Molecular Dynamics simulations, coupling Multiparticle Collision Dynamics to model the solvent and Molecular Dynamics to model suspended colloids, including hydrodynamics, thermal fluctuations, and chemically active solvent particles and catalytic colloids. The main usage of RMPCDMD is the simulation of chemically powered nanomotors, but other setups are considered: colloids in the presence of a thermal gradients or forced flows. RMPCDMD is developed in Fortran 2008 with OpenMP for multithreaded operation and uses the HDF5-based H5MD file format for storing data. RMPCDMD comes with documentation and a tutorial for the simulation of chemically powered nanomotors.

Grain Boundary Specific Segregation in Nanocrystalline Fe(Cr).

A cross-correlative precession electron diffraction – atom probe tomography investigation of Cr segregation in a Fe(Cr) nanocrystalline alloy was undertaken. Solute segregation was found to be dependent on grain boundary type. The results of which were compared to a hybrid Molecular Dynamics and Monte Carlo simulation that predicted the segregation for special character, low angle, and high angle grain boundaries, as well as the angle of inclination of the grain boundary. It was found that the highest segregation concentration was for the high angle grain boundaries and is explained in terms of clustering driven by the onset of phase separation. For special character boundaries, the highest Gibbsain interfacial excess was predicted at the incoherent ∑3 followed by ∑9 and ∑11 boundaries with negligible segregation to the twin and ∑5 boundaries. In addition, the low angle grain boundaries predicted negligible segregation. All of these trends matched well with the experiment. This solute-boundary segregation dependency for the special character grain boundaries is explained in terms of excess volume and the energetic distribution of the solute in the boundary.

Full molecular dynamics simulations of liquid water and carbon tetrachloride for two-dimensional Raman spectroscopy in the frequency domain

Frequency-domain two-dimensional (2D) Raman signals, which are equivalent to coherent two-dimensional Raman scattering (COTRAS) signals, for liquid water and carbon tetrachloride were calculated using an equilibrium–nonequilibrium hybrid molecular dynamics (MD) simulation algorithm. An appropriate representation of the 2D Raman spectrum obtained from MD simulations provides an easy-to-understand depiction of structural and dynamical properties. We elucidate mechanisms governing the 2D signal profiles involving anharmonic mode–mode coupling and the nonlinearities of the polarizability for the intermolecular and intramolecular vibrational modes. The predicted signal profiles and intensities can be utilized to analyze recently developed single-beam 2D spectra, whose signals are generated from a coherently controlled pulse, allowing the single-beam measurement to be carried out more efficiently. Moreover, the MD simulation results allow us to visualize the molecular structure and dynamics by comparing the accurately calculated spectrum with experimental result.

Atomistic modeling framework for a cyclobutane-based mechanophore-embedded nanocomposite for damage precursor detection

An atomistic modeling framework is developed to simulate mechanophore activation and evaluate the sensitivity of cyclobutane-based mechanophores. Mechanophores are force-responsive functional units, which when embedded in an epoxy-based thermoset polymer matrix provide self-sensing capability in polymeric composites. In the presence of damage or damage precursors, covalent bond dissociation of the mechanophore generates fluorescence, which is referred to as the mechanophore activation. A Tris-(Cinnamoyloxymethyl)-Ethane (TCE) monomer is used to synthesize the cyclobutane structure through ultra-violet (UV) dimerization; the synthesized cyclobutanes are incorporated into the thermoset polymer matrix. A hybrid molecular dynamics (MD) simulation framework is developed by integrating two force-fields: a classical force-field, Merck Molecular Force Field (MMFF) and a bond-order based force-field, Reactive Force Field (ReaxFF). The hybrid MD methodology enables construction of the molecular model of the cyclobutane-based mechanophore embedded nanocomposite and simulation of the mechanophore activation. The synthesis of epoxy network and cyclobutane structure is numerically simulated by a covalent bond generation method employing MMFF. Through this numerical synthesis, the physical entanglement between the epoxy network and cyclobutane chain is also captured, which determines the local force distribution within the novel nanocomposite. Covalent bond dissociation due to the applied local force on the mechanophore is simulated using ReaxFF and results from the virtual deformation tests show successful mechanophore activation. A local work analysis method is developed to evaluate the sensitivity of mechanophore. Results from the simulation framework show increment in the number of activated cyclobutanes during the deformation test. Good agreement is observed with experimental results: the intensity of fluorescence was found to be directly proportional to the deformation.

Sampling free energy surfaces as slices by combining umbrella sampling and metadynamics.

Metadynamics (MTD) is a very powerful technique to sample high-dimensional free energy landscapes, and due to its self-guiding property, the method has been successful in studying complex reactions and conformational changes. MTD sampling is based on filling the free energy basins by biasing potentials and thus for cases with flat, broad, and unbound free energy wells, the computational time to sample them becomes very large. To alleviate this problem, we combine the standard Umbrella Sampling (US) technique with MTD to sample orthogonal collective variables (CVs) in a simultaneous way. Within this scheme, we construct the equilibrium distribution of CVs from biased distributions obtained from independent MTD simulations with umbrella potentials. Reweighting is carried out by a procedure that combines US reweighting and Tiwary-Parrinello MTD reweighting within the Weighted Histogram Analysis Method (WHAM). The approach is ideal for a controlled sampling of a CV in a MTD simulation, making it computationally efficient in sampling flat, broad, and unbound free energy surfaces. This technique also allows for a distributed sampling of a high-dimensional free energy surface, further increasing the computational efficiency in sampling. We demonstrate the application of this technique in sampling high-dimensional surface for various chemical reactions using ab initio and QM/MM hybrid molecular dynamics simulations. Further, to carry out MTD bias reweighting for computing forward reaction barriers in ab initio or QM/MM simulations, we propose a computationally affordable approach that does not require recrossing trajectories. © 2016 Wiley Periodicals, Inc.

Simulated Solute Tempering in Fully Polarizable Hybrid QM/MM Molecular Dynamics Simulations.

We successfully apply a solute tempering approach, which substantially reduces the large number of temperature rungs required in conventional tempering methods by solvent charge scaling, to hybrid molecular dynamics simulations combining quantum mechanics with molecular mechanics (QM/MM). Specifically, we integrate a combination of density functional theory (DFT) and polarizable MM (PMM) force fields into the simulated solute tempering (SST) concept. We show that the required DFT/PMM-SST weight parameters can be obtained from inexpensive calculations and that for alanine dipeptide (DFT) in PMM water three rungs suffice to cover the temperature range from 300 to 550 K.

Viscoelastic properties of marginal networks in a solvent.

Polymer networks at the margins of mechanical stability are known to be highly sensitive to applied forces and fields and to exhibit an anomalously large resistance to deformation. In this paper, we study the effects of hydrodynamic interactions on the behavior of marginal networks using a hybrid molecular dynamics and multiparticle collision dynamics simulation technique. We examine how the filament and solvent properties affect the response of marginal networks to shear. We find that the stiffening of the network shows a stronger dependence on the shear frequency when hydrodynamic interactions are present than when they are not. The network shear modulus scales as G'∼ω(α(c)), with a critical stiffening exponent α(c) that can be controlled by varying the relative concentrations of the network and the solvent. Our results show that this arises due to the solvent aiding the relaxation of the network and suppressing the network nonaffinity, with the system deforming more affinely when hydrodynamic interactions are maximized.

Mesoscale Simulation of self-diffusiophoretic microrotor

Artificial micro-scale or nano-scale machines that are capable of converting energy to mechanical work, have long been pursued by science and engineering communities for their potential applications in microfluidics, biology and medicine. From a physics point of view, they are also ideal models to investigate fundamental statistical phenomena in non-equilibrium active matters. Inspired by bio-machines and bio-motors like ATP synthase and flagellum motors, we propose a simple design of rotary motors based on pure self-diffusiophoresis effects. The basic design of the rotor consists of three colloidal beads with different surface properties, which leads to different interactions between the beads and solvent molecules. Chemical reactions are imposed on the surface of one of the beads, which creates a source of one of the two solvent molecules and generates a local concentration gradient. The other two beads connected to the catalytic bead have different affinities to the solvent molecules, which leads to asymmetric diffusiophoretic forces on the two non-catalytic beads. A net torque is thus obtained from difference of the diffusiophoretic forces between the two non-catalytic beads. In our simulation, we employ hybrid molecular dynamics (MD) simulations and multi-particle collision dynamics (MPC) to investigate the motion of microrotors. The binary fluid is composed with A-type and B-type solvent particle whose interactions are described by multi-particle collision dynamics while beads-particle interactions are modeled by molecular dynamics. In MPC, all fluid particles execute alternating streaming and collision steps. During streaming steps, the solvents move ballistically. During collision steps, particles are sorted into square cells and only interact with particles in the same cell under a specific stochastic rotation rule. MPC algorithm locally conserves mass, linear momentum, angular momentum and energy, and properly captures thermal fluctuation, mass diffusion, dissipation and hydrodynamic interactions. In our simulation, standard MPC parameters are employed which correspond to a liquid-like behavior of fluid. In MD, beads-solvent interactions are described by Lennard-Jones(LJ) potential with different parameter combinations and the equations of motion is integrated by velocity-Verlet algorithm. To perform hybrid molecular dynamic simulations with multi-particle collision dynamics, between two MPC collision steps, 50 MD steps are implemented for the solvent particles that are in the interaction range of colloidal beads. We first investigate the solvent concentration distribution around static microrotor, and confirm that the catalytic bead generates a steady-state local concentration gradient. Net angular displacements are obtained when the rotor is allowed to rotate freely. The rotational direction and speed of the micorotor are determined by bead-solvent interactions, the rotor geometry, the solvent viscosity and the catalytic reaction ratio. We also study the scenario in which two rotors are placed in close vicinity to each other. We find that the coupling between the concentration fields around the rotors reduces the rotational speed of both rotors.

Hybrid Molecular and Spin Dynamics Simulations for Ensembles of Magnetic Nanoparticles for Magnetoresistive Systems.

The development of magnetoresistive sensors based on magnetic nanoparticles which are immersed in conductive gel matrices requires detailed information about the corresponding magnetoresistive properties in order to obtain optimal sensor sensitivities. Here, crucial parameters are the particle concentration, the viscosity of the gel matrix and the particle structure. Experimentally, it is not possible to obtain detailed information about the magnetic microstructure, i.e., orientations of the magnetic moments of the particles that define the magnetoresistive properties, however, by using numerical simulations one can study the magnetic microstructure theoretically, although this requires performing classical spin dynamics and molecular dynamics simulations simultaneously. Here, we present such an approach which allows us to calculate the orientation and the trajectory of every single magnetic nanoparticle. This enables us to study not only the static magnetic microstructure, but also the dynamics of the structuring process in the gel matrix itself. With our hybrid approach, arbitrary sensor configurations can be investigated and their magnetoresistive properties can be optimized.

Inertial and viscoelastic forces on rigid colloids in microfluidic channels.

We perform hybrid molecular dynamics simulations to study the flow behavior of rigid colloids dispersed in a dilute polymer solution. The underlying Newtonian solvent and the ensuing hydrodynamic interactions are incorporated through multiparticle collision dynamics, while the constituent polymers are modeled as bead-spring chains, maintaining a description consistent with the colloidal nature of our system. We study the cross-stream migration of the solute particles in slit-like channels for various polymer lengths and colloid sizes and find a distinct focusing onto the channel center under specific solvent and flow conditions. To better understand this phenomenon, we systematically measure the effective forces exerted on the colloids. We find that the migration originates from a competition between viscoelastic forces from the polymer solution and hydrodynamically induced inertial forces. Our simulations reveal a significantly stronger fluctuation of the lateral colloid position than expected from thermal motion alone, which originates from the complex interplay between the colloid and polymer chains.

Analysis of 2D THz-Raman spectroscopy using a non-Markovian Brownian oscillator model with nonlinear system-bath interactions.

We explore and describe the roles of inter-molecular vibrations employing a Brownian oscillator (BO) model with linear-linear (LL) and square-linear (SL) system-bath interactions, which we use to analyze two-dimensional (2D) THz-Raman spectra obtained by means of molecular dynamics (MD) simulations. In addition to linear infrared absorption (1D IR), we calculated 2D Raman-THz-THz, THz-Raman-THz, and THz-THz-Raman signals for liquid formamide, water, and methanol using an equilibrium non-equilibrium hybrid MD simulation. The calculated 1D IR and 2D THz-Raman signals are compared with results obtained from the LL+SL BO model applied through use of hierarchal Fokker-Planck equations with non-perturbative and non-Markovian noise. We find that all of the qualitative features of the 2D profiles of the signals obtained from the MD simulations are reproduced with the LL+SL BO model, indicating that this model captures the essential features of the inter-molecular motion. We analyze the fitted 2D profiles in terms of anharmonicity, nonlinear polarizability, and dephasing time. The origins of the echo peaks of the librational motion and the elongated peaks parallel to the probe direction are elucidated using optical Liouville paths.

Electrophoretic Mobility of Polyelectrolytes within a Confining Well.

We present a numerical study of polyelectrolytes electrophoresing in free solution while squeezed by an axisymmetric confinement force transverse to their net displacement. Hybrid multiparticle collision dynamics and molecular dynamics simulations with mean-field finite Debye layers show that even though the polyelectrolyte chains remain "free-draining" their electrophoretic mobility increases with confinement in nanoconfining potential wells. The primary mechanism leading to the increase in mobility above the free-solution value, despite long-range hydrodynamic screening by counterion layers, is the orientation of polymer segments within Debye layers. The observed length dependence of the electrophoretic mobility arises due to secondary effects of counterion condensation related to confinement compactification.