A method for analyzing nanomechanical deformation of nanocrystalline Ni at higher timesteps than is possible in classical molecular dynamics

2006 ◽  
Vol 978 ◽  
Author(s):  
Vikas Tomar
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Strain Rate ◽  
Defect Formation ◽  
Interatomic Potential ◽  
Md Simulations ◽  
Classical Molecular Dynamics ◽  
Rate Dependent ◽  
Nanocrystalline Structures ◽  
Defect Nucleation

AbstractA majority of computational mechanical analyses of nanocrystalline materials have been carried out using classical molecular dynamics (MD). Due to the fundamental reason that the MD simulations must resolve atomic level vibrations, they cannot be carried out at the timescale of the order of microseconds. Additionally, MD simulations have to be carried out at very high loading rates (∼108 s−1) rarely observed in experiments. In this investigation a modified Hybrid Monte Carlo (HMC) method that can be used to analyze time-dependent (strain rate dependent) atomistic mechanical deformation of nanocrystalline structures at higher timescales than currently possible using MD is established. In this method there is no restriction on the size of MD timestep except that it must be such that to ensure a reasonable acceptance rate between consecutive Monte-Carlo (MC) time-steps. For the purpose of comparison HMC analyses of a nanocrystalline Ni sample at a strain rate of 109 s−1 with three different timesteps, viz. 2 fs, 4fs, and 8 fs, are compared with the analyses based on MD simulations at the same strain rate and a MD timestep of 2 fs. MD simulations of nanocrystalline Ni reproduce the defect nucleation and propagation results as well as strength values reported in the literature. In addition, HMC with timestep of 8 fs correctly reproduces defect formation and stress-strain response observed in the case of MD simulations with permissible timestep of 2 fs (for the interatomic potential used 2 fs is the highest MD timestep). Simulation time analyses show that by using HMC a saving of the order of 4 can be achieved bringing the atomistic analyses closer to the continuum timescales.

Atomistic Simulations of Strain Rate Dependent Deformation Behavior at Continuum Timescales

2006 ◽  
Vol 976 ◽  
Author(s):  
Vikas Tomar
Keyword(s):  
Monte Carlo ◽  
Strain Rate ◽  
Defect Formation ◽  
Interatomic Potential ◽  
Md Simulations ◽  
Strain Rates ◽  
Cu Nanowires ◽  
Rate Dependent ◽  
Fundamental Reason ◽  
Dependent Strain

AbstractA majority of computational mechanical analyses of nanocrystalline materials or nanowires have been carried out using classical molecular dynamics (MD). Due to the fundamental reason that the MD simulations must resolve atomic level vibrations, they cannot be carried out at the timescale of the order of microseconds. Additionally, MD simulations have to be carried out at very high loading rates (∼108 s−1) rarely observed in experiments. In this investigation, a modified Hybrid Monte Carlo (HMC) method that can be used to analyze time-dependent (strain rate dependent) atomistic mechanical deformation of nanostructures at continuum timescales is established. In this method there is no restriction on the size of MD timestep except that it must be such that to ensure a reasonable acceptance rate between consecutive Monte-Carlo (MC) time-steps. For the purpose of comparison HMC analyses of Cu nanowires deformation at two different strain rates (108 s−1 and 109 s−1) (each with three different timesteps 2 fs, 4fs, and 8 fs) are compared with the analyses based on MD simulations at the same strain rates and a MD timestep of 2 fs. As expected, the defect formation is found to be strain rate dependent. In addition, HMC with timestep of 8 fs correctly reproduces defect formation and stress-strain response observed in the case of MD with 2 fs (for the interatomic potential used 2 fs is the highest MD timestep). Simulation time analyses show that by using HMC a saving of the order of 4 can be achieved bringing the atomistic analyses closer to the continuum timescales.

Characterization of Defect Nucleation and Propagation in Fe2O3+FCC-Al Nanocomposites During Uniaxial Tensile and Compressive Deformations

2006 ◽  
Author(s):  
Vikas Tomar ◽  
Min Zhou
Keyword(s):  
Molecular Dynamics ◽  
Grain Size ◽  
Defect Formation ◽  
Voronoi Tessellation ◽  
Orientation Distribution ◽  
Uniaxial Tensile ◽  
Grain Sizes ◽  
Classical Molecular Dynamics ◽  
Average Grain Size ◽  
Nanocrystalline Structures

The objective of this research is to analyze uniaxial tensile and compressive mechanical deformations of α-Fe2O3 + fcc Al nanoceramic-metal composites using classical molecular dynamics (MD). Specifically, variations in the nucleation and the propagation of defects (such as dislocations and stacking faults etc.) with variation in the nanocomposite phase morphology and their effect on observed tensile and compressive strengths of the nanocomposites are analyzed. For this purpose, a classical molecular dynamics (MD) potential that includes an embedded atom method (EAM) cluster functional, a Morse type pair function, and a second order electrostatic interaction function is developed, see Tomar and Zhou (2004) and Tomar and Zhou (2006b). The nanocrystalline structures (nanocrystalline Al, nanocrystalline Fe2O3 and the nanocomposites with 40% and 60% Al by volume) with average grain sizes of 3.9 nm, 4.7 nm, and 7.2 nm are generated using a combination of the well established Voronoi tessellation method with the Inverse Monte-Carlo method to conform to prescribed log-normal grain size distributions. For comparison purposes, nanocrystalline structures with a specific average grain size have the same grain morphologies and the same grain orientation distribution. MD simulations are performed at the room temperature (300 K). Calculations show that the deformation mechanism is affected by a combination of factors including the fraction of grain boundary (GB) atoms and the electrostatic forces between atoms. The significance of each factor is dependent on the volume fractions of the Al and Fe2O3 phases. Depending on the relative orientations of the two phases at an interface, the contribution of the interface to the defect formation varies. The interfaces have stronger effect in structures with smaller average grain sizes than in structures with larger average grain sizes.

scholarly journals Fully Atomistic Molecular Dynamics Computation of Physico-Mechanical Properties of PB, PS, and SBS

Nanomaterials ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 1088 ◽  
Author(s):  
Yang Kang ◽  
Dunhong Zhou ◽  
Qiang Wu ◽  
Fuyan Duan ◽  
Rufang Yao ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Strain Rate ◽  
Strain Hardening ◽  
Md Simulation ◽  
Md Simulations ◽  
Strain Rates ◽  
Young’S Moduli ◽  
Plastic Modulus ◽  
Styrene Butadiene ◽  
Butadiene Styrene

The physical properties—including density, glass transition temperature (Tg), and tensile properties—of polybutadiene (PB), polystyrene (PS) and poly (styrene-butadiene-styrene: SBS) block copolymer were predicted by using atomistic molecular dynamics (MD) simulation. At 100 K, for PB and SBS under uniaxial tension with strain rate ε ˙ = 1010 s−1 and 109 s−1, their stress–strain curves had four features, i.e., elastic, yield, softening, and strain hardening. At 300 K, the tensile curves of the three polymers with strain rates between 108 s−1 and 1010 s−1 exhibited strain hardening following elastic regime. The values of Young’s moduli of the copolymers were independent of strain rate. The plastic modulus of PS was independent of strain rate, but the Young’s moduli of PB and SBS depended on strain rate under the same conditions. After extrapolating the Young’s moduli of PB and SBS at strain rates of 0.01–1 s−1 by the linearized Eyring-like model, the predicted results by MD simulations were in accordance well with experimental results, which demonstrate that MD results are feasible for design of new materials.

L1 Regularization-Based Model Reduction of Complex Chemistry Molecular Dynamics for Statistical Learning of Kinetic Monte Carlo Models

MRS Advances ◽  
2016 ◽  
Vol 1 (24) ◽  
pp. 1767-1772 ◽  
Author(s):  
Qian Yang ◽  
Carlos A. Sing-Long ◽  
Evan J. Reed
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Kinetic Monte Carlo ◽  
A Priori ◽  
Reaction Network ◽  
Md Simulations ◽  
Rate Coefficients ◽  
Elementary Reactions ◽  
L1 Regularization ◽  
Complex Chemistry

ABSTRACTKinetic Monte Carlo (KMC) methods have been a successful technique for accelerating time scales and increasing system sizes beyond those achievable with fully atomistic simulations. However, a requirement for its success is a priori knowledge of all relevant reaction pathways and their rate coefficients. This can be difficult for systems with complex chemistry, such as shock-compressed materials at high temperatures and pressures or phenolic spacecraft heat shields undergoing pyrolysis, which can consist of hundreds of molecular species and thousands of distinct reactions. In this work, we develop a method for first estimating a KMC model composed of elementary reactions and rate coefficients by using large datasets derived from a few molecular dynamics (MD) simulations of shock compressed liquid methane, and then using L1 regularization to reduce the estimated chemical reaction network. We find that the full network of 2613 reactions can be reduced by 89% while incurring approximately 9% error in the dominant species (CH4) population. We find that the degree of sparsity achievable decreases when similar accuracy is required for additional populations of species.

scholarly journals Sorption, Structure and Dynamics of CO2 and Ethane in Silicalite at High Pressure: A Combined Monte Carlo and Molecular Dynamics Simulation Study

Molecules ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 99 ◽  
Author(s):  
Siddharth Gautam ◽  
Tingting Liu ◽  
David Cole
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Time Scales ◽  
Rotational Motion ◽  
High Pressures ◽  
Sorption Isotherms ◽  
Md Simulations ◽  
Dynamics Simulation ◽  
Structure And Dynamics ◽  
Low Pressures

Silicalite is an important nanoporous material that finds applications in several industries, including gas separation and catalysis. While the sorption, structure, and dynamics of several molecules confined in the pores of silicalite have been reported, most of these studies have been restricted to low pressures. Here we report a comparative study of sorption, structure, and dynamics of CO2 and ethane in silicalite at high pressures (up to 100 bar) using a combination of Monte Carlo (MC) and molecular dynamics (MD) simulations. The behavior of the two fluids is studied in terms of the simulated sorption isotherms, the positional and orientational distribution of sorbed molecules in silicalite, and their translational diffusion, vibrational spectra, and rotational motion. Both CO2 and ethane are found to exhibit orientational ordering in silicalite pores; however, at high pressures, while CO2 prefers to reside in the channel intersections, ethane molecules reside mostly in the sinusoidal channels. While CO2 exhibits a higher self-diffusion coefficient than ethane at low pressures, at high pressures, it becomes slower than ethane. Both CO2 and ethane exhibit rotational motion at two time scales. At both time scales, the rotational motion of ethane is faster. The differences observed here in the behavior of CO2 and ethane in silicalite pores can be seen as a consequence of an interplay of the kinetic diameter of the two molecules and the quadrupole moment of CO2.

Combining Molecular Dynamics and Monte Carlo Simulations to Model Chemical Vapor Deposition: Application to Diamond

1992 ◽  
Vol 278 ◽  
Author(s):  
D.W. Brenner ◽  
D.H. Robertson ◽  
R.J. Carty ◽  
D. Srivastava ◽  
B.J. Garrison
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Chemical Vapor Deposition ◽  
Vapor Deposition ◽  
Surface Reactions ◽  
Chemical Vapor ◽  
Md Simulations ◽  
Monte Carlo Algorithm ◽  
Surface Collision ◽  
Classical Trajectories

AbstractGas-surface reactions of the type that contribute to growth during the chemical vapor deposition (CVD) of diamond films are generally completed in picoseconds, well within timescales accessible by molecular dynamics (MD) simulations. For low-pressure deposition, however, the time between collisions for a surface site can be microseconds, which makes direct modeling of CVD crystal growth impossible using standard MD methods. To effectively bridge this discrepancy in timescales, the gas-surface reactions can be modeled using MD trajectories, and then this data can be used to define probabilities in a Monte Carlo algorithm where each step represents a gas-surface collision. We illustrate this approach using the reaction of atomic hydrogen with a diamond (111) surface as an example, where we use abstraction and sticking probabilities generated using classical trajectories in a simple Monte Carlo algorithm to determine the number of open sites as a function of temperature. We also include models for the thermal desorption of hydrogen that predict that growth temperatures are not restricted by the thermal loss of chemisorbed hydrogen.

scholarly journals Application of classical simulations for the computation of vibrational properties of free molecules

2016 ◽  
Vol 18 (40) ◽  
pp. 28325-28338 ◽  
Author(s):  
Denis S. Tikhonov ◽  
Dmitry I. Sharapa ◽  
Jan Schwabedissen ◽  
Vladimir V. Rybkin
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Vibrational Properties ◽  
Vibrational Motion ◽  
Classical Molecular Dynamics ◽  
Free Molecules

In this study, we investigate the ability of classical molecular dynamics (MD) and Monte-Carlo (MC) simulations for modeling of the intramolecular vibrational motion.

Molecular Dynamics Simulations of Diffusion of O2 and N2 Penetrants in Polydimethylsiloxane-Based Nanocomposites

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Douglas E. Spearot ◽  
Alex Sudibjo ◽  
Varun Ullal ◽  
Adam Huang
Keyword(s):  
Molecular Dynamics ◽  
Polymer Composites ◽  
Diffusion Coefficients ◽  
Metal Particle ◽  
Interatomic Potential ◽  
Md Simulations ◽  
Coarse Grained ◽  
Cu Nanoparticles ◽  
Cu Nanoparticle ◽  
Nanoparticle Inclusions

Recently, metal particle polymer composites have been proposed as sensing materials for micro corrosion sensors. To design the sensors, a detailed understanding of diffusion through metal particle polymer composites is necessary. Accordingly, in this work molecular dynamics (MD) simulations are used to study the diffusion of O2 and N2 penetrants in metal particle polymer nanocomposites composed of an uncross-linked polydimethylsiloxane (PDMS) matrix with Cu nanoparticle inclusions. PDMS is modeled using a hybrid interatomic potential with explicit treatment of Si and O atoms along the chain backbone and coarse-grained methyl side groups. In most models examined in this work, MD simulations show that diffusion coefficients of O2 and N2 molecules in PDMS-based nanocomposites are lower than that in pure PDMS. Nanoparticle inclusions act primarily as geometric obstacles for the diffusion of atmospheric penetrants, reducing the available porosity necessary for diffusion, with instances of O2 and N2 molecule trapping also observed at or near the PDMS/Cu nanoparticle interfaces. In models with the smallest gap between Cu nanoparticles, MD simulations show that O2 and N2 diffusion coefficients are higher than that in pure PDMS at the lowest temperatures studied. This is due to PDMS chain confinement at low temperatures in the presence of the Cu nanoparticles, which induces low-density regions within the PDMS matrix. MD simulations show that the role of temperature on diffusion can be modeled using the Williams–Landel–Ferry equation, with parameters influenced by nanoparticle content and spacing.

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