ReaxFF(MgH) reactive force field for magnesium hydride systems

We have developed a reactive force field (ReaxFF(MgH)) for magnesium and magnesium hydride systems. The parameters for this force field were derived from fitting to quantum chemical (QM) data on magnesium clusters and on the equations of states for condensed phases of magnesium metal and magnesium hydride crystal. The force field reproduces the QM-derived cell parameters, density, and the equations of state for various pure Mg and MgH(2) crystal phases as well as and bond dissociation, angle bending, charge distribution, and reaction energy data for small magnesium hydride clusters. To demonstrate one application of ReaxFF(MgH), we have carried out MD simulations on the hydrogen absorption/desorption process in magnesium hydrides, focusing particularly on the size effect of MgH(2) nanoparticles on H(2) desorption kinetics. Our results show a clear relationship between grain size and heat of formation of MgH(2); as the particle size decreases, the heat of formation increases. Between 0.6 and 2.0 nm, the heat of formation ranges from -16 to -19 kcal/Mg and diverges toward that of the bulk value (-20.00 kcal/Mg) as the particle diameter increases beyond 2 nm. Therefore, it is not surprising to find that Mg nanoparticles formed by ball milling (20-100 nm) do not exhibit any significant change in thermochemical properties.     

A force field for some weakly coupled conjugated systems

A force field developed in a series of overlay calculations for some weakly coupled conjugated systems is discussed. The force fieid is compared with other, mainly overlay force fields of related molecules, as this gives further evidence for the transferability of the force constants. In order to be of any use for large molecules the force field must be easy to transfer to related, more complicated molecules. The disadvantages of using individual force fields are also discussed.     

A reactive force field simulation of liquid-liquid phase transitions in phosphorus

A force field model of phosphorus has been developed based on density functional (DF) computations and experimental results, covering low energy forms of local tetrahedral symmetry and more compact (simple cubic) structures that arise with increasing pressure. Rules tailored to DF data for the addition, deletion, and exchange of covalent bonds allow the system to adapt the bonding configuration to the thermodynamic state. Monte Carlo simulations in the N-P-T ensemble show that the molecular (P(4)) liquid phase, stable at low pressure P and relatively low temperature T, transforms to a polymeric (gel) state on increasing either P or T. These phase changes are observed in recent experiments at similar thermodynamic conditions, as shown by the close agreement of computed and measured structure factors in the molecular and polymer phases. The polymeric phase obtained by increasing pressure has a dominant simple cubic character, while the polymer obtained by raising T at moderate pressure is tetrahedral. Comparison with DF results suggests that the latter is a semiconductor, while the cubic form is metallic. The simulations show that the T-induced polymerization is due to the entropy of the configuration of covalent bonds, as in the polymerization transition in sulfur. The transition observed with increasing P is the continuation at high T of the black P to arsenic (A17) structure observed in the solid state, and also corresponds to a semiconductor to metal transition.     

ReaxFF reactive force field for the Y-doped BaZrO3 proton conductor with applications to diffusion rates for multigranular systems

Proton-conducting perovskites such as Y-doped BaZrO 3 (BYZ) are promising candidates as electrolytes for a proton ceramic fuel cell (PCFC) that might permit much lower temperatures (from 400 to 600 degrees C). However, these materials lead to relatively poor total conductivity ( approximately 10 (-4) S/cm) because of extremely high grain boundary resistance. In order to provide the basis for improving these materials, we developed the ReaxFF reactive force field to enable molecular dynamics (MD) simulations of proton diffusion in the bulk phase and across grain boundaries of BYZ. This allows us to elucidate the atomistic structural details underlying the origin of this poor grain boundary conductivity and how it is related to the orientation of the grains. The parameters in ReaxFF were based entirely on the results of quantum mechanics (QM) calculations for systems related to BYZ. We apply here the ReaxFF to describe the proton diffusion in crystalline BYZ and across grain boundaries in BYZ. The results are in excellent agreement with experiment, validating the use of ReaxFF for studying the transport properties of these membranes. Having atomistic structures for the grain boundaries from simulations that explain the overall effect of the grain boundaries on diffusion opens the door to in silico optimization of these materials. That is, we can now use theory and simulation to examine the effect of alloying on both the interfacial structures and on the overall diffusion. As an example, these calculations suggest that the reduced diffusion of protons across the grain boundary results from the increased average distances between oxygen atoms in the interface, which necessarily leads to larger barriers for proton hopping. Assuming that this is the critical issue in grain boundary diffusion, the performance of BYZ for multigranular systems might be improved using additives that would tend to precipitate to the grain boundary and which would tend to pull the oxygens atoms together. Possibilities might be to use a small amount of larger trivalent ions, such as La or Lu or of tetravalent ions such as Hf or Th. Since ReaxFF can also be used to describe the chemical processes on the anode and cathode and the migration of ions across the electrode-membrane interface, ReaxFF opens the door to the possibility of atomistic first principles predictions on models of a complete fuel cell.     

ReaxFF reactive force field for molecular dynamics simulations of hydrocarbon oxidation

To investigate the initial chemical events associated with high-temperature gas-phase oxidation of hydrocarbons, we have expanded the ReaxFF reactive force field training set to include additional transition states and chemical reactivity of systems relevant to these reactions and optimized the force field parameters against a quantum mechanics (QM)-based training set. To validate the ReaxFF potential obtained after parameter optimization, we performed a range of NVT-MD simulations on various hydrocarbon/O2 systems. From simulations on methane/O2, o-xylene/O2, propene/O2, and benzene/O2 mixtures, we found that ReaxFF obtains the correct reactivity trend (propene > o-xylene > methane > benzene), following the trend in the C-H bond strength in these hydrocarbons. We also tracked in detail the reactions during a complete oxidation of isolated methane, propene, and o-xylene to a CO/CO2/H2O mixture and found that the pathways predicted by ReaxFF are in agreement with chemical intuition and our QM results. We observed that the predominant initiation reaction for oxidation of methane, propene, and o-xylene under fuel lean conditions involved hydrogen abstraction of the methyl hydrogen by molecular oxygen forming hydroperoxyl and hydrocarbon radical species. While under fuel rich conditions with a mixture of these hydrocarbons, we observed different chemistry compared with the oxidation of isolated hydrocarbons including a change in the type of initiation reactions, which involved both decomposition of the hydrocarbon or attack by other radicals in the system. Since ReaxFF is capable of simulating complicated reaction pathways without any preconditioning, we believe that atomistic modeling with ReaxFF provides a useful method for determining the initial events of oxidation of hydrocarbons under extreme conditions and can enhance existing combustion models.     

Global optimization of parameters in the reactive force field ReaxFF for SiOH

We have used unbiased global optimization to fit a reactive force field to a given set of reference data. Specifically, we have employed genetic algorithms (GA) to fit ReaxFF to SiOH data, using an in‐house GA code that is parallelized across reference data items via the message‐passing interface (MPI). Details of GA tuning turn‐ed out to be far less important for global optimization efficiency than using suitable ranges within which the parameters are varied. To establish these ranges, either prior knowledge can be used or successive stages of GA optimizations, each building upon the best parameter vectors and ranges found in the previous stage. We have finally arrive‐ed at optimized force fields with smaller error measures than those published previously. Hence, this optimization approach will contribute to converting force‐field fitting from a specialist task to an everyday commodity, even for the more difficult case of reactive force fields. © 2013 Wiley Periodicals, Inc.     

Development and application of a ReaxFF reactive force field for hydrogen combustion

To investigate the reaction kinetics of hydrogen combustion at high-pressure and high-temperature conditions, we constructed a ReaxFF training set to include reaction energies and transition states relevant to hydrogen combustion and optimized the ReaxFF force field parameters against training data obtained from quantum mechanical calculations and experimental values. The optimized ReaxFF potential functions were used to run NVT MD (i.e., molecular dynamics simulation with fixed number of atoms, volume, and temperature) simulations for various H(2)/O(2) mixtures. We observed that the hydroperoxyl (HO(2)) radical plays a key role in the reaction kinetics at our input conditions (T ≥ 3000 K, P > 400 atm). The reaction mechanism observed is in good agreement with predictions of existing continuum-scale kinetic models for hydrogen combustion, and a transition of reaction mechanism is observed as we move from high pressure, low temperature to low pressure, high temperature. Since ReaxFF derives its parameters from quantum mechanical data and can simulate reaction pathways without any preconditioning, we believe that atomistic simulations through ReaxFF could be a useful tool in enhancing existing continuum-scale kinetic models for prediction of hydrogen combustion kinetics at high-pressure and high-temperature conditions, which otherwise is difficult to attain through experiments.     

Optimization and application of lithium parameters for the reactive force field, ReaxFF

To make a practical molecular dynamics (MD) simulation of the large-scale reactive chemical systems of Li-H and Li-C, we have optimized parameters of the reactive force field (ReaxFF) for these systems. The parameters for this force field were obtained from fitting to the results of density functional theory (DFT) calculations on the structures and energy barriers for a number of Li-H and Li-C molecules, including Li(2), LiH, Li(2)H(2), H(3)C-Li, H(3)C-H(2)C-Li, H(2)C=C-LiH, HCCLi, H(6)C(5)-Li, and Li(2)C(2), and to the equations of state and lattice parameters for condensed phases of Li. The accuracy of the developed ReaxFF was also tested by comparison to the dissociation energies of lithium-benzene sandwich compounds and the collision behavior of lithium atoms with a C(60) buckyball.     

A transferable active-learning strategy for reactive molecular force fields

Predictive molecular simulations require fast, accurate and reactive interatomic potentials. Machine learning offers a promising approach to construct such potentials by fitting energies and forces to high-level quantum-mechanical data, but doing so typically requires considerable human intervention and data volume. Here we show that, by leveraging hierarchical and active learning, accurate Gaussian Approximation Potential (GAP) models can be developed for diverse chemical systems in an autonomous manner, requiring only hundreds to a few thousand energy and gradient evaluations on a reference potential-energy surface. The approach uses separate intra- and inter-molecular fits and employs a prospective error metric to assess the accuracy of the potentials. We demonstrate applications to a range of molecular systems with relevance to computational organic chemistry: ranging from bulk solvents, a solvated metal ion and a metallocage onwards to chemical reactivity, including a bifurcating Diels–Alder reaction in the gas phase and non-equilibrium dynamics (a model S_N2 reaction) in explicit solvent. The method provides a route to routinely generating machine-learned force fields for reactive molecular systems.

An efficient strategy for training Gaussian Approximation Potential (GAP) models to study chemical reactions using hierarchical and active learning.     

A molecular mechanics force field for lignin

A CHARMM molecular mechanics force field for lignin is derived. Parameterization is based on reproducing quantum mechanical data of model compounds. Partial atomic charges are derived using the RESP electrostatic potential fitting method supplemented by the examination of methoxybenzene:water interactions. Dihedral parameters are optimized by fitting to critical rotational potentials and bonded parameters are obtained by optimizing vibrational frequencies and normal modes. Finally, the force field is validated by performing a molecular dynamics simulation of a crystal of a lignin fragment molecule and comparing simulation-derived structural features with experimental results. Together with the existing force field for polysaccharides, this lignin force field will enable full simulations of lignocellulose.     

A corrected valence force field for benzene

A corrected valence force field for benzene is presented. The force constants have been determined by refining the observed and calculated frequencies of ¹³C and deuterated isotopes. The definitions of various force constant interaction terms are clarified.     

Parameterization of a reactive force field using a Monte Carlo algorithm

Parameterization of a molecular dynamics force field is essential in realistically modeling the physicochemical processes involved in a molecular system. This step is often challenging when the equations involved in describing the force field are complicated as well as when the parameters are mostly empirical. ReaxFF is one such reactive force field which uses hundreds of parameters to describe the interactions between atoms. The optimization of the parameters in ReaxFF is done such that the properties predicted by ReaxFF matches with a set of quantum chemical or experimental data. Usually, the optimization of the parameters is done by an inefficient single‐parameter parabolic‐search algorithm. In this study, we use a robust metropolis Monte‐Carlo algorithm with simulated annealing to search for the optimum parameters for the ReaxFF force field in a high‐dimensional parameter space. The optimization is done against a set of quantum chemical data for MgSO₄ hydrates. The optimized force field reproduced the chemical structures, the equations of state, and the water binding curves of MgSO₄ hydrates. The transferability test of the ReaxFF force field shows the extend of transferability for a particular molecular system. This study points out that the ReaxFF force field is not indefinitely transferable. © 2013 Wiley Periodicals, Inc.     

Modeling the sorption dynamics of NaH using a reactive force field

We have parametrized a reactive force field for NaH, ReaxFF(NaH), against a training set of ab initio derived data. To ascertain that ReaxFF(NaH) is properly parametrized, a comparison between ab initio heats of formation of small representative NaH clusters with ReaxFF(NaH) was done. The results and trend of ReaxFF(NaH) are found to be consistent with ab initio values. Further validation includes comparing the equations of state of condensed phases of Na and NaH as calculated from ab initio and ReaxFF(NaH). There is a good match between the two results, showing that ReaxFF(NaH) is correctly parametrized by the ab initio training set. ReaxFF(NaH) has been used to study the dynamics of hydrogen desorption in NaH particles. We find that ReaxFF(NaH) properly describes the surface molecular hydrogen charge transfer during the abstraction process. Results on heat of desorption versus cluster size shows that there is a strong dependence on the heat of desorption on the particle size, which implies that nanostructuring enhances desorption process. To gain more insight into the structural transformations of NaH during thermal decomposition, we performed a heating run in a molecular dynamics simulation. These runs exhibit a series of drops in potential energy, associated with cluster fragmentation and desorption of molecular hydrogen. This is consistent with experimental evidence that NaH dissociates at its melting point into smaller fragments.     

CHARMM force field parameters for simulation of reactive intermediates in native and thio-substituted ribozymes

Force field parameters specifically optimized for residues important in the study of RNA catalysis are derived from density-functional calculations, in a fashion consistent with the CHARMM27 all-atom empirical force field. Parameters are presented for residues that model reactive RNA intermediates and transition state analogs, thio-substituted phosphates and phosphoranes, and bound Mg(2+) and di-metal bridge complexes. Target data was generated via density-functional calculations at the B3LYP/6-311++G(3df,2p)// B3LYP/6-31++G(d,p) level. Partial atomic charges were initially derived from CHelpG electrostatic potential fitting and subsequently adjusted to be consistent with the CHARMM27 charges. Lennard-Jones parameters were determined to reproduce interaction energies with water molecules. Bond, angle, and torsion parameters were derived from the density-functional calculations and renormalized to maintain compatibility with the existing CHARMM27 parameters for standard residues. The extension of the CHARMM27 force field parameters for the nonstandard biological residues presented here will have considerable use in simulations of ribozymes, including the study of freeze-trapped catalytic intermediates, metal ion binding and occupation, and thio effects.     

Development of a ReaxFF reactive force field for ettringite and study of its mechanical failure modes from reactive dynamics simulations

Ettringite is a hexacalcium aluminate trisulfate hydrate mineral that forms during Portland cement hydration. Its presence plays an important role in controlling the setting rate of the highly reactive aluminate phases in cement paste and has also been associated with severe cracking in cured hardened cement. To understand how it forms and how its properties influence those of hardened cement and concrete, we have developed a first-principles-based ReaxFF reactive force field for Ca/Al/H/O/S. Here, we report on the development of this ReaxFF force field and on its validation and application using reactive molecular dynamics (RMD) simulations to characterize and understand the elastic, plastic, and failure response of ettringite at the atomic scale. The ReaxFF force field was validated by comparing the lattice parameters, pairwise distribution functions, and elastic constants of an ettringite crystal model obtained from RMD simulations with those from experiments. The predicted results are in close agreement with published experimental data. To characterize the atomistic failure modes of ettringite, we performed stress-strain simulations to find that Ca-O bonds are responsible for failure of the calcium sulfate and tricalcium aluminate (C3A) column in ettringite during uniaxial compression and tension and that hydrogen bond re-formation during compression induces an increase in plastic strain beyond the material's stress-strain proportionality limit. These results provide essential insight into understanding the mechanistic role of this mineral in cement and concrete degradation, and the ReaxFF potential developed in this work serves as a fundamental tool to further study the kinetics of hydration in cement and concrete.     

A new GROMOS force field for hexopyranose-based carbohydrates

A new parameter set (referred to as 45A4) is developed for the explicit-solvent simulation of hexopyranose-based carbohydrates. This set is compatible with the most recent version of the GROMOS force field for proteins, nucleic acids, and lipids, and the SPC water model. The parametrization procedure relies on: (1) reassigning the atomic partial charges based on a fit to the quantum-mechanical electrostatic potential around a trisaccharide; (2) refining the torsional potential parameters associated with the rotations of the hydroxymethyl, hydroxyl, and anomeric alkoxy groups by fitting to corresponding quantum-mechanical profiles for hexopyranosides; (3) adapting the torsional potential parameters determining the ring conformation so as to stabilize the (experimentally predominant) (4)C(1) chair conformation. The other (van der Waals and nontorsional covalent) parameters and the rules for third and excluded neighbors are taken directly from the most recent version of the GROMOS force field (except for one additional exclusion). The new set is general enough to define parameters for any (unbranched) hexopyranose-based mono-, di-, oligo- or polysaccharide. In the present article, this force field is validated for a limited set of monosaccharides (alpha- and beta-D-glucose, alpha- and beta-D-galactose) and disaccharides (trehalose, maltose, and cellobiose) in solution, by comparing the results of simulations to available experimental data. More extensive validation will be the scope of a forthcoming article. (c) 2005 Wiley Periodicals, Inc. J Comput Chem 26: 1400-1412, 2005.