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At least 19 records

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗

REACTER: A Versatile Tool for Large-Scale Reactive Molecular Dynamics

Accurately describing reactive events over long length and time scales remains a grand challenge of computational materials science. REACTER is a general protocol for modeling chemical reactions using classical force fields, and is implemented in the popular molecular dynamics software LAMMPS. REACTER has a growing user base and has been used as a model-building tool for a variety of materials, including thermoplastics, thermosets, glassy materials and composites. The method has also been applied to accelerated modeling of reversible chemical reactions, such as the formation of electrochemical components for batteries. Recently, the REACTER protocol has received some major upgrades to enhance its ability to predict when reactions occur and to make it easier to use. Force field parameters can now be automatically assigned to newly created bonds, angles and other interactions. Advanced reaction constraints have also been added, including an Arrhenius constraint to enforce an effective activation energy, a root-mean-square-deviation option for complex geometrical constraints, and a constraint based on the total potential energy of the atoms involved in a reactive site. This potential energy constraint allows for the accurate reproduction of DFT-based tight-binding (DFTB3) predicted bond dissociation curves for mechanically induced bond breaking.

polymer simulations, molecular dynamics↗

Effect of Aromaticity on Soot Formation: A Reactive Molecular Dynamics Study

This study investigates the formation of soot from n-dodecane and its blend with m-xylene under pyrolytic and low-oxygen conditions with reactive molecular dynamics (MD) simulations. ReaxFF force field is used to simulate the interactions of fuel and oxygen molecules at engine-relevant conditions (2500-3500 K and 70-75 bar). Fuel molecules with carbon atom density of 0.03 g/cm 3 are dispersed into a cube and constant temperature simulations are carried out with a Nosé-Hoover thermostat. Pyrolysis of n-dodecane and the chemical pathway towards the formation of aromatic hydrocarbons are investigated. The initial pyrolysis rate of n-dodecane is observed to be slightly higher with the addition of aromatic compounds and oxygen. While the first aromatics formed from the decomposed n-dodecane are phenyl radicals at 2500 K, decomposition of the aliphatic fuel compound is observed to be necessary to build a carbon cluster, and eventually soot. Morphological properties of the created soot particles are also analyzed. The maturity, size and aromatics content of the soot particle are slightly affected with the addition of m-xylene and oxygen at 3500 K within the 3 ns simulation time possibly due the formation of larger and more condensed aromatic rings, resulting in larger soot molecules. The outcomes of this study provide important insights into the formation mechanism of soot and its morphological characteristics depending on varying fuel concentrations at pyrolysis and low oxygen engine conditions. Results of this analysis will further contribute to the understanding of contrail formation on generated soot particles originated from the combustion of different chemical components with particle chemistry matching companion experiments.

soot formation↗

Quantum mechanical algebraic variational methods for inelastic and reactive molecular collisions

The quantum mechanical problem of reactive or nonreactive scattering of atoms and molecules is formulated in terms of square-integrable basis sets with variational expressions for the reactance matrix. Several formulations involving expansions of the wave function (the Schwinger variational principle) or amplitude density (a generalization of the Newton variational principle), single-channel or multichannel distortion potentials, and primitive or contracted basis functions are presented and tested. The test results, for inelastic and reactive atom-diatom collisions, suggest that the methods may be useful for a variety of collision calculations and may allow the accurate quantal treatment of systems for which other available methods would be prohibitively expensive.

Schwenke, David W.↗

Entropy and chemical change. 1: Characterization of product (and reactant) energy distributions in reactive molecular collisions: Information and enthropy deficiency

Optimal means of characterizing the distribution of product energy states resulting from reactive collisions of molecules with restricted distributions of initial states are considered, along with those for characterizing the particular reactant state distribution which yields a given set of product states at a specified total energy. It is suggested to represent the energy-dependence of global-type results in the form of square-faced bar plots, and of data for specific-type experiments as triangular-faced prismatic plots. The essential parameters defining the internal state distribution are isolated, and the information content of such a distribution is put on a quantitative basis. The relationship between the information content, the surprisal, and the entropy of the continuous distribution is established. The concept of an entropy deficiency, which characterizes the specificity of product state formation, is suggested as a useful measure of the deviance from statistical behavior. The degradation of information by experimental averaging is considered, leading to bounds on the entropy deficiency.

Bernstein, R. B.↗

Time-dependent wave-packet method for the complete determination of S-matrix elements for reactive molecular collisions in three dimensions

An alternative time-dependent wave-packet method for treating three-dimensional gas phase reactive atom-diatom collisions is presented. The method employs a nonreactive body-frame wave packet propagation procedure, made possible by judicious use of absorbing optical potentials, a novel scheme for interpolating the wave function from coordinates in one arrangement to those in another and the fact that the time-dependent Schroedinger equation is an initial-value problem. The last feature makes possible a computationally viable and accurate procedure for changing from one arrangement's coordinates to another. In addition, the method allows the determination of S-matrix elements over a wide range of energies from a single wave-packet propagation. The method is illustrated by carrying out detailed calculations of inelastic and reactive scattering in the H + H2 system using the Liu-Siegbahn-Truhlar-Horowitz potential surface.

Judson, Richard S.↗

REACTER: A Heuristic Method for Reactive Molecular Dynamics

REACTER (www.reacter.org) is a heuristic protocol that enables the simulation of complex reactions using atomistic molecular dynamics (MD) with a fixed-valence force field. Incorporating reactions into classical MD with this approach allows modeling of reactive systems over greatly-increased time scales, enabling systems to be modeled with MD that would not otherwise be feasible. One or more competing multi-step reactions or series of reactions can be invoked simultaneously. Special treatment can be applied to neighboring atoms to relax high energy configurations while the simulation progresses. The original version of REACTER, which was implemented in the open-source LAMMPS simulation package as fix bond/react, was only available for serial simulations. This work describes the expansion of fix bond/react for use in parallel simulations, as well as the addition of various new options, including deletion of reaction by-products, reversible reactions, and custom reaction constraints. These new capabilities are demonstrated through large-scale simulations (200,000+ atoms) of the polymerization of polystyrene and nylon 6,6. The morphologies of both polymers are analyzed after reaching >99% extent of polymerization. Finally, the newly-added reversible reactions feature is demonstrated by rupturing these highly-entangled systems under uniaxial strain by defining a chain scission reaction.

polymer simulations, molecular dynamics↗

Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

Polyether ether ketone (PEEK) is a high-performance, semi-crystalline thermoplastic that is used in a wide range of engineering applications, including some structural components of aircraft. The design of new PEEK-based materials requires a precise understanding of the multiscale structure and behavior of semi-crystalline PEEK. Molecular Dynamics (MD) modeling can efficiently predict bulk-level properties of single phase polymers, and micromechanics can be used to homogenize those phases based on the overall polymer microstructure. In this study, MD modeling was used to predict the mechanical properties of the amorphous and crystalline phases of PEEK. The hierarchical microstructure of PEEK, which combines the aforementioned phases, was modeled using a multiscale modeling approach facilitated by NASA's MSGMC. The bulk mechanical properties of semi-crystalline PEEK predicted using MD modeling and MSGMC agree well with vendor data, thus validating the multiscale modeling approach.

Pisani, William A.↗

Surrogate Fuel Chemistry from ReaxFF Molecular Dynamics

Reactive molecular dynamics with ReaxFF simulations are used to study the chemistry of four component jet fuel mixtures of n-dodecane, iso-octane, n-propylbenzene, and mesitylene. ReaxFF does not require knowledge of the chemistry a priori providing insight into reactions otherwise not seen in established chemical kinetic mechanisms. The results show that a difference in the local chemical environment can change the fuel decomposition pathways across the surrogate mixtures where the same fuel species are used. These simulations highlight the need to consider cross-chemical interactions in chemical kinetic mechanism development and the importance of resonance stabilized polyaromatic hydrocarbon reactions for soot growth and formation. A method for predicting the threshold sooting index from the carbon species formed at the end of the simulations is established. The results of the simulations are consistent with measurements of the threshold sooting index with the predicted values within 20% of the measured data

Surrogate Fuels↗

Theoretical studies of molecular collisions

The following subject areas are covered: (1) total integral reactive cross sections and vibrationally resolved reaction probabilities for F + H2 = HF + H; (2) a theoretical study of inelastic O + N2 collisions; (3) body frame close coupling wave packet approach to gas phase atom-rigit rotor inelastic collisions; (4) wave packet study of gas phase atom-rigit motor scattering; (5) the application of optical potentials for reactive scattering; (6) time dependent, three dimensional body frame quantal wave packet treatment of the H + H2 exchange reaction; (7) a time dependent wave packet approach to atom-diatom reactive collision probabilities; (8) time dependent wave packet for the complete determination of s-matrix elements for reactive molecular collisions in three dimensions; (9) a comparison of three time dependent wave packet methods for calculating electron-atom elastic scattering cross sections; and (10) a numerically exact full wave packet approach to molecule-surface scattering.

Kouri, Donald J.↗

Novel polyelectrolytes

Cationic polyelectrolytes are formed by the polymerization in absence of oxygen of a monomer of the general formula: ##STR1## where x is 3 or more than 6 and Z is I, Br or Cl to form high charge density linear polymers. Segments of the linear polymer may be attached to or formed in the presence of polyfunctional reactive tertiary amines or halogen polymeric substrates or polyfunctional lower molecular reactive polyfunctional substrates to form branched or star polyelectrolytes by a quaternization polymerization reaction.

Rembaum, Alan↗

Modeling Ring-Opening Polymerization with Machine-Learned Committors

Many important industrial and biological processes depend on ring-opening polymerization (ROP), including large-scale production polymers, such as nylon 6, and a variety of biodegradable polymers and high-performance resins. Large-scale simulations (>200K atoms) of ROP were performed using a deep neural network-based method that captured the effect of the local chemical environment of the reactive sites using training data from quantum chemical methods. The utility of this method was demonstrated by modeling the cationic ROP of bis-benzoxazine, a promising resin for use in advanced high-temperature application composites (>200°C). Density functional theory calculations were used to map out the various ring opening and polymerization reaction paths that occur during the thermal processing of bis-benzoxazine. The probabilities of these reactions, as a function of local atomic configurations, were used to construct committor functions using a neural network approach. The learned committor functions were then used to determine when a particular reaction occurred within the REACTER framework for reactive molecular dynamics simulations. The experimentally observed exotherm that occurs during bis-benzoxazine ROP was captured in an effective manner in the simulations by imposing a local heating of the system that corresponds to the enthalpy of reaction for each reaction. The dependence of the final polymer morphology on the ROP reaction temperature was analyzed at the molecular scale. The results presented in this work indicate that machine-learned committor functions are a promising approach for incorporating high-fidelity reactivity criteria that capture the effect of local chemical environments into large-scale polymerization simulations.

machine learning, polymer simulations, molecular d↗

Molecular Dynamics Modeling of Carbon Nanotube Composite Fracture Using ReaxFF

Carbon nanotube (CNT) fiber reinforced composites with specific tensile strengths and moduli approaching those of aerospace grade carbon fiber composites have recently been reported. This achievement was enabled by the emerging availability of high N/tex yarns in kilometer-scale quantities. While the production of this yarn is an impressive advance, its strength is still much lower than that of the individual CNTs comprising the yarn. Closing this gap requires understanding load transfer between CNTs at the nanometer dimensional scale. This work uses reactive molecular dynamics simulations to gain an understanding at the nanometer scale of the key factors that determine CNT nanocomposite mechanical performance, and to place more realistic upper bounds on the target properties. While molecular dynamics simulations using conventional force fields can predict elastic properties, the ReaxFF reactive forcefield can also model fracture behavior because of its ability to accurately describe bond breaking and formation during a simulation. The upper and lower bounds of CNT composite properties are investigated by comparing systems composed of CNTs continuously connected across the periodic boundary with systems composed of finite length CNTs. These lengths, effectively infinite for the continuous tubes and an aspect ratio of 13 for the finite length case, result from practical limitations on the number of atoms that can be included in a simulation. Experimentally measured aspect ratios are typically on the order of 100,000, so the calculated results should represent upper and lower limits on experimental mechanical properties. Finally, the effect of various degrees of covalent crosslinking between the CNTs and amorphous carbon matrix is considered to identify the amount of CNT-matrix covalent bonding that maximizes overall composite properties.

Jensen, Benjamin D.↗