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Discussion on molecular dynamics (MD) simulations of the asphalt materials

The application of asphalt materials in pavement engineering has been increasingly widespread and sophisticated over the past several decades. Variations in the properties of asphalt binder during mixing, transportation, and paving can affect the performance of asphalt pavement. However, the asphalt material is a non-homogeneous and complex organic substance, consisting of various molecules with widely various molecular weights, elemental compositions, and structures. This complexity leads to difficulties for researchers to clearly and immediately understand the properties of asphalt materials and their variations. The multi-scale research approach combines macroscopic experimental data and microscopic simulation results from a practical engineering perspective. It helps to improve the understanding of asphalt materials. The molecular dynamics (MD) simulation proposes a corresponding molecular model of asphalt material based on experimental data, and the simulation algorithm is able to derive properties similar to those of real asphalt. Here, this paper provides a comprehensive review of the current studies on MD simulation of asphalt materials, including modeling, properties, and multi-scale analysis. As a key part of the computational simulation, this paper discusses the typical asphalt binder and asphalt-aggregate interface models constructed by different groups, and also presents their differences from real samples and their feasibility based on fundamental properties. After the introduction of molecular models, the extensive work made by researchers based on molecular models is categorically reviewed and discussed. The strengths and weaknesses of MD simulation methods in the study of asphalt materials are also summarized in order to provide the reader with a more comprehensive understanding of the relevant contents and to guide subsequent research.

36 MATERIALS SCIENCE↗

Computational Capabilities for Predictions of Interactions at the Grain Boundary of Refractory Alloys

New high performance refractory alloys are critically required for improving efficiency and decreasing CO 2 emissions of fossil energy systems. The development of these materials remains slow because it is driven by a trial-and-error experimental approach and lacks a rational design approach. Atomistic Molecular Dynamic (MD) design has the potential to accelerate this development through the prediction of mechanical properties and corrosion resistance of new materials. The success of MD simulations depends critically on the fidelity of interatomic potentials. This project, in collaboration with Penn State, has focused on developing and validating high quality quantum mechanics based reactive potentials, ReaxFF, for Ni-Fe-Al-Cr-O-S system. A larger number of accurate density functional theory (DFT) calculations were performed to generate data for parameterizing the ReaxFF potentials. These potentials were then used in molecular dynamics (MD) and molecular dynamics-Monte Carlo (MD-MC) for much larger system to study for which DFT calculation would be prohibitively expensive, and to understand a number of chemical phenomena Ni-Fe-Al-Cr-O-S based alloy systems . These include catalytic oxidation of butane on clean Cr 2 O 3 and pyrite/Cr 2 O 3 , interfacial reaction between Cr 2 O 3 (refractory material) and Al 2 O 3 (slag), cohesive strength of at the grain boundary of S-enriched Cr compared to bulk Cr and Ssegregation study in Al, Al 2 O 3 , Cr and Cr 2 O 3 with a grain structure. The developed quantum based ReaxFF potential are available from the authors upon request. During this project, a number of papers were published in peer-reviewed journals. In addition, several conference presentations were made.

01 COAL, LIGNITE, AND PEAT↗

Computational Capabilities for Predictions of Interactions at the Grain Boundary of Refractory Alloys

New high performance refractory alloys are critically required for improving efficiency and decreasing CO 2 emissions of fossil energy systems. The development of these materials remains slow because it is driven by a trial-and-error experimental approach and lacks a rational design approach. Atomistic Molecular Dynamic (MD) design has the potential to accelerate this development through the prediction of mechanical properties and corrosion resistance of new materials. The success of MD simulations depends critically on the fidelity of interatomic potentials. This project, in collaboration with Penn State, has focused on developing and validating high quality quantum mechanics based reactive potentials, ReaxFF, for Ni-Fe-Al-Cr-O-S system. A larger number of accurate density functional theory (DFT) calculations were performed to generate data for parameterizing the ReaxFF potentials. These potentials were then used in molecular dynamics (MD) and molecular dynamics-Monte Carlo (MD-MC) for much larger system to study for which DFT calculation would be prohibitively expensive, and to understand a number of chemical phenomena Ni-Fe-Al-Cr-O-S based alloy systems . These include catalytic oxidation of butane on clean Cr 2 O 3 and pyrite/Cr 2 O 3 , interfacial reaction between Cr 2 O 3 (refractory material) and Al 2 O 3 (slag), cohesive strength of at the grain boundary of S-enriched Cr compared to bulk Cr and Ssegregation study in Al, Al 2 O 3 , Cr and Cr 2 O 3 with a grain structure. The developed quantum based ReaxFF potential are available from the authors upon request. During this project, a number of papers were published in peer-reviewed journals. In addition, several conference presentations were made.

36 MATERIALS SCIENCE↗

Extending molecular simulation time scales: Parallel in time integrations for high-level quantum chemistry and complex force representations

Parallel in time simulation algorithms are presented and applied to conventional molecular dynamics (MD) and ab initio molecular dynamics (AIMD) models of realistic complexity. Assuming that a forward time integrator, f (e.g., Verlet algorithm), is available to propagate the system from time t{sub i} (trajectory positions and velocities x{sub i} = (r{sub i}, v{sub i})) to time t{sub i+1} (x{sub i+1}) by x{sub i+1} = f{sub i}(x{sub i}), the dynamics problem spanning an interval from t{sub 0}…t{sub M} can be transformed into a root finding problem, F(X) = [x{sub i} − f(x{sub (i−1})]{sub i} {sub =1,M} = 0, for the trajectory variables. The root finding problem is solved using a variety of root finding techniques, including quasi-Newton and preconditioned quasi-Newton schemes that are all unconditionally convergent. The algorithms are parallelized by assigning a processor to each time-step entry in the columns of F(X). The relation of this approach to other recently proposed parallel in time methods is discussed, and the effectiveness of various approaches to solving the root finding problem is tested. We demonstrate that more efficient dynamical models based on simplified interactions or coarsening time-steps provide preconditioners for the root finding problem. However, for MD and AIMD simulations, such preconditioners are not required to obtain reasonable convergence and their cost must be considered in the performance of the algorithm. The parallel in time algorithms developed are tested by applying them to MD and AIMD simulations of size and complexity similar to those encountered in present day applications. These include a 1000 Si atom MD simulation using Stillinger-Weber potentials, and a HCl + 4H{sub 2}O AIMD simulation at the MP2 level. The maximum speedup ((serial execution time)/(parallel execution time) ) obtained by parallelizing the Stillinger-Weber MD simulation was nearly 3.0. For the AIMD MP2 simulations, the algorithms achieved speedups of up to 14.3. The parallel in time algorithms can be implemented in a distributed computing environment using very slow transmission control protocol/Internet protocol networks. Scripts written in Python that make calls to a precompiled quantum chemistry package (NWChem) are demonstrated to provide an actual speedup of 8.2 for a 2.5 ps AIMD simulation of HCl + 4H{sub 2}O at the MP2/6-31G* level. Implemented in this way these algorithms can be used for long time high-level AIMD simulations at a modest cost using machines connected by very slow networks such as WiFi, or in different time zones connected by the Internet. The algorithms can also be used with programs that are already parallel. Using these algorithms, we are able to reduce the cost of a MP2/6-311++G(2d,2p) simulation that had reached its maximum possible speedup in the parallelization of the electronic structure calculation from 32 s/time step to 6.9 s/time step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model-free estimation of the effective correlation time for C–H bond reorientation in amphiphilic bilayers: {sup 1}H–{sup 13}C solid-state NMR and MD simulations

Molecular dynamics (MD) simulations give atomically detailed information on structure and dynamics in amphiphilic bilayer systems on timescales up to about 1 μs. The reorientational dynamics of the C–H bonds is conventionally verified by measurements of {sup 13}C or {sup 2}H nuclear magnetic resonance (NMR) longitudinal relaxation rates R{sub 1}, which are more sensitive to motional processes with correlation times close to the inverse Larmor frequency, typically around 1-10 ns on standard NMR instrumentation, and are thus less sensitive to the 10-1000 ns timescale motion that can be observed in the MD simulations. We propose an experimental procedure for atomically resolved model-free estimation of the C–H bond effective reorientational correlation time τ{sub e}, which includes contributions from the entire range of all-atom MD timescales and that can be calculated directly from the MD trajectories. The approach is based on measurements of {sup 13}C R{sub 1} and R{sub 1ρ} relaxation rates, as well as {sup 1}H−{sup 13}C dipolar couplings, and is applicable to anisotropic liquid crystalline lipid or surfactant systems using a conventional solid-state NMR spectrometer and samples with natural isotopic composition. The procedure is demonstrated on a fully hydrated lamellar phase of 1-palmitoyl-2-oleoyl-phosphatidylcholine, yielding values of τ{sub e} from 0.1 ns for the methyl groups in the choline moiety and at the end of the acyl chains to 3 ns for the g{sub 1} methylene group of the glycerol backbone. MD simulations performed with a widely used united-atom force-field reproduce the τ{sub e}-profile of the major part of the acyl chains but underestimate the dynamics of the glycerol backbone and adjacent molecular segments. The measurement of experimental τ{sub e}-profiles can be used to study subtle effects on C–H bond reorientational motions in anisotropic liquid crystals, as well as to validate the C–H bond reorientation dynamics predicted in MD simulations of amphiphilic bilayers such as lipid membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Formation of I 1 stacking fault by deformation defect evolution from grain boundaries in Mg

I 1 stacking faults (SFs) in Mg alloys are regarded as the nucleation sites of $\langle \text{c+a} \rangle$ dislocations that are critical for these alloys to achieve high ductility. Previously it was proposed that the formation of I 1 SFs requires the accumulations of a large number of vacancies, which are difficult to achieve at low temperatures. In this study, molecular dynamics (MD) and molecular statics (MS) simulations based on empirical interatomic potentials were applied to investigate the deformation defect evolutions from the symmetric tilt grain boundaries (GBs) in Mg and Mg-Y alloys under external loading along $\langle c \rangle$-axis. The results show the planar faults (PFs) on Pyramidal I planes first appear due to the nucleation and glide of $\langle {\frac {1}{2}}c + p\rangle$ partial dislocations from GBs, where $\langle p\rangle$ = ${\frac {1}{3}} \langle10\bar{1}0\rangle$. These partial dislocations with pyramidal PFs interact with other defects, including pyramidal PFs themselves, GBs, and $\langle p\rangle$ partial dislocations, generating a large amount of I 1 SFs. Detailed analyses show the nucleation and growth of I 1 SFs are achieved by atomic shuffle events and deformation defect reactions without the requirements of vacancy diffusion. Our simulations also suggest the Y clusters at GBs can reduce the critical stress for the formation of pyramidal PFs and I 1 SFs, which provide a possible reason for the experimental observations that Y promotes the $\langle{\text{c+a}}\rangle$ dislocation activities.

36 MATERIALS SCIENCE↗

Local volume effects in the generalized pseudopotential theory

The generalized pseudopotential theory (GPT) is a compelling approach for deriving real-space transferable interatomic potentials. Using a coarse-grained electronic structure, one can explicitly determine the pair ion-ion and multi-ion interactions in simple and transition metals. While successful in determining bulk properties, in central force metals the GPT fails to describe crystal defects for which there is a significant local volume change. A previous paper [J. A. Moriarty and R. Phillips, Phys. Rev. Lett. 66, 3036 (1991)] found that by allowing the GPT total energy to depend upon some spatially averaged local electron density, the energetics of vacancies and surfaces could be calculated within experimental ranges. In this paper, we develop the formalism further by explicitly calculating the forces and stress tensor associated with this total energy. We call this scheme the adaptive GPT (aGPT) and it is capable of both molecular dynamics (MD) and molecular statics. We apply the aGPT to vacancy formation, divacancy binding, and stacking faults in hcp Mg. We also calculate the local electron density corrections to the bulk elastic constants and phonon dispersion for which there is refinement over the baseline GPT treatment. Furthermore, we demonstrate aGPT-MD simulation through the calculation of thermal expansion in magnesium to 700 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗