Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

Chemical understanding is driven by the experimental discovery of new compounds and reactivity, and is supported by theory and computation that provides detailed physical insight. While theoretical and computational studies have generally focused on specific processes or mechanistic hypotheses, recent methodological and computational advances harken the advent of their principal role in discovery. Here we report the development and application of the ab initio nanoreactor – a highly accelerated, first-principles molecular dynamics simulation of chemical reactions that discovers new molecules and mechanisms without preordained reaction coordinates or elementary steps. Using the nanoreactor we show new pathways for glycine synthesis from primitive compounds proposed to exist on the early Earth, providing new insight into the classic Urey-Miller experiment. These results highlight the emergence of theoretical and computational chemistry as a tool for discovery in addition to its traditional role of interpreting experimental findings.

/pdf/discovering-chemistry-with-an-ab-initio-nanoreactor-1v1zz669b4.pdf

Discovering chemistry with an ab initio nanoreactor

The molecular dynamics simulation of lignite combustion process in O2/CO2 atmosphere with ReaxFF force field

Two-dimensional (2D) hexagonal boron nitride materials are isomorphs of carbon nanomaterials and hold promise for electronics applications owing to their unique properties. Despite the recent advances in synthesis, the current production capacity for boron nitride (BN) nanostructures is far behind that for carbon-based nanostructures. Understanding the growth mechanism of BN nanostructures through modeling and experiments is key to improving this situation. In the current work, we present the development of a ReaxFF-based force field capable of modeling the gas-phase chemistry important for the chemical vapor deposition (CVD) synthesis process. This force field is parameterized to model the boron nitride nanostructure (BNNS) formation in the gas phase using BN and HBNH as precursors. Our ReaxFF simulations show that BN is the best of these two precursors in terms of quality and the size of BNNSs. The BN precursors lead to the formation of closed BNNSs. However, BNNSs are replaced with complex polymeric structures at temperatures of 2500 K and higher due to entropic effects. Compared to the BN precursors, the HBNH precursors form relatively small, flat, and low-quality BNNSs, but this structure is less affected by temperature. Additives like H2 significantly affect the BNNS formation by preventing closed BNNS formation. Our results show the ReaxFF capability in predicting the BN gas-phase chemistry and BNNS formation, thus providing key insights for experimental synthesis.

ReaxFF Force Field Development for Gas-Phase hBN Nanostructure Synthesis.

Under the vision of “low carbonization”, ammonia (NH3), as a carbon-free hydrogen-rich fuel, blended with reactive additives, is an effective means to achieve low carbon emissions and reduce the consumption of traditional fossil fuels. In this work, the combustion behaviors of NH3 and CH4, the distribution of main products and the formation and reduction characteristics of NO at different temperatures, CH4 mixing ratios, and O2 equivalence ratios are explored by means of reactive molecular dynamics simulation to reveal the microscopic mechanism of NH3/CH4 co-combustion. The calculated results show that CH4 takes the lead in producing H radicals which react with O2 to generate OH radicals to promote the oxidation of NH3, and it is found that the co-combustion process of NH3/CH4 in the radical chain transfer stage is similar to the respective pyrolysis and oxidation reactions of CH4 and NH3. Accordingly, an optimized kinetic mechanism of NH3/CH4 co-combustion is constructed based on the mechanisms proposed by Glarborg et al. and Okafor et al. by incorporating the NH3 pyrolysis sub-mechanisms related to NH2, HNO, and N2H2 and the skeletal mechanism of CH4 oxidation. The optimized mechanisms of NH3/CH4 co-combustion are found to improve the prediction of the ignition delay time (IDT) and laminar burning velocity (LBV) of NH3/CH4 mixture under wide ranges of conditions compared to the original mechanisms of Glarborg et al. and Okafor et al. To decrease the computational cost of three-dimensional combustion numerical simulations, the skeletal mechanism models are established by simplification of the optimized mechanisms of NH3/CH4 co-combustion using direct relation graph method with error propagation and sensitivity analysis, which can provide nearly the same estimates of IDTs and LBVs as the optimized mechanisms mentioned above. 

Reactive molecular dynamics simulation and chemical kinetic modeling of ammonia/methane co-combustion

Exploring the Chemistry of Low-Temperature Ignition by Pressure-Accelerated Dynamics

Synthesizing microgels with new functionalities is vital for applications in various disciplines; yet microgel synthesis kinetics are mostly unknown. We present a bottom-up approach to model the synthesis of N-vinylcaprolactam-based microgels functionalized with glycidyl methacrylate. The existing synthesis model requires parameter values for unknown reaction rates, which we estimate by a hybrid approach based on quantum chemical calculations and experimental data. Using quantum mechanics, we compute propagation rate constants and enthalpies of the underlying polymerization reactions. We estimate 7 out of 21 reaction parameter values using the reaction calorimetry measurements and a mechanistic process model. Our hybrid approach averages a coefficient of determination of 0.97 for the enthalpy transfer rate over time during microgel synthesis. Our approach illustrates that quantum chemistry methods and physical experiments can be integrated into models toward better understanding and designing of pVCL/GMA microgel synthesis processes. 

Kinetic Modeling of a Poly(N-vinylcaprolactam-co-glycidyl methacrylate) Microgel Synthesis: A Hybrid In Silico and Experimental Approach

In our two-paper series, we first present the development of ReaxFF CHOCl parameters using the recently published ParAMS parametrization tool.In this second part, we update the reactive Molecular Dynamics - Quantum Mechanics coupling scheme ChemTraYzer and combine it with our new ReaxFF parameters from Part I to study formation and decomposition processes of chlorinated dibenzofurans.We introduce a self-learning method for recovering failed transition-state searches that improves the overall ChemTraYzer transition-state search success rate by 10 percentage points to a total of $48\%$.With ChemTraYzer, we automatically find and quantify more than 500 reactions using transition state theory and DFT.Among the discovered chlorinated dibenzofuran reactions are numerous reactions that are new to the literature.In three case studies, we discuss the set of reactions that are most relevant to the dibenzofuran literature: (i) bimolecular reactions of the chlorinated-dibenzofuran precursors phenoxy radical and 1,3,5-trichlorobenzene, (ii) dibenzofuran chlorination and pyrolysis, and (iii) oxidation of chlorinated dibenzofurans.

A Reactive Molecular Dynamics Study of Chlorinated Organic Compounds. Part II: A ChemTraYzer Study of Chlorinated Dibenzofuran Formation and Decomposition Processes.

The recently discovered, membrane–active peptide LBF14 contains several non–proteinogenic amino acids and is able to transform vesicles into tubule networks. The exact membrane interaction mechanis...

Determining structure and action mechanism of LBF14 by molecular simulation.

This work presents a novel parametrization for the ReaxFF formalism as a means to investigate reaction processes of chlorinated organic compounds. Force field parameters cover the chemical elements C, H, O, Cl and were obtained using a novel optimization approach involving relaxed potential energy surface scans as training targets. The resulting ReaxFF parametrization shows good transferability, as demonstrated on two independent ab initio validation sets. While this first part of our two-paper series focuses on force field parametrization, we apply our parameters to the simulation of chlorinated dibenzofuran formation and decomposition processes in Part II.

A Reactive Molecular Dynamics Study of Chlorinated Organic Compounds. Part I: Force Field Development.

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