Optimum trajectories in a central force field
Optimum trajectories in central force field
FORCE FIELD↗
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Perfluoropolyethers: Development of an All-Atom Force Field for Molecular Simulations and Validation with New Experimental Vapor Pressures and Liquid Densities
A force field for perfluoropolyethers (PFPEs) based on the general optimized potentials for liquid simulations all-atom (OPLS-AA) force field has been derived in conjunction with experiments and ab initio quantum mechanical calculations. Vapor pressures and densities of two liquid PFPEs, perfluorodiglyme (CF 3 –O–(CF 2 –CF 2 –O)2–CF 3 ) and perfluorotriglyme (CF 3 –O–(CF 2 –CF 2 –O) 3 –CF 3 ), have been measured experimentally to validate the force field and increase our understanding of the physical properties of PFPEs. Force field parameters build upon those for related molecules (e.g., ethers and perfluoroalkanes) in the OPLS-AA force field, with new parameters introduced for interactions specific to PFPEs. Molecular dynamics simulations using the new force field demonstrate excellent agreement with ab initio calculations at the RHF/6-31G* level for gas-phase torsional energies (<0.5 kcal mol –1 error) and molecular structures for several PFPEs, and also accurately reproduce experimentally determined densities (<0.02 g cm –3 error) and enthalpies of vaporization derived from experimental vapor pressures (<0.3 kcal mol–1). Additional comparisons between experiment and simulation show that polyethers demonstrate a significant decrease in enthalpy of vaporization upon fluorination unlike related molecules (e.g., alkanes and alcohols). Simulation suggests this phenomenon is a result of reduced cohesion in liquid PFPEs due to a reduction in localized associations between backbone oxygen atoms and neighboring molecules.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Optimization of classical nonpolarizable force fields for OH{sup −} and H{sub 3}O{sup +}
We optimize force fields for H{sub 3}O{sup +} and OH{sup −} that reproduce the experimental solvation free energies and the activities of H{sub 3}O{sup +} Cl{sup −} and Na{sup +} OH{sup −} solutions up to concentrations of 1.5 mol/l. The force fields are optimized with respect to the partial charge on the hydrogen atoms and the Lennard-Jones parameters of the oxygen atoms. Remarkably, the partial charge on the hydrogen atom of the optimized H{sub 3}O{sup +} force field is 0.8 ± 0.1|e|—significantly higher than the value typically used for nonpolarizable water models and H{sub 3}O{sup +} force fields. In contrast, the optimal partial charge on the hydrogen atom of OH{sup −} turns out to be zero. Standard combination rules can be used for H{sub 3}O{sup +} Cl{sup −} solutions, while for Na{sup +} OH{sup −} solutions, we need to significantly increase the effective anion-cation Lennard-Jones radius. While highlighting the importance of intramolecular electrostatics, our results show that it is possible to generate thermodynamically consistent force fields without using atomic polarizability.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Frequency-dependent local field factors in dielectric liquids by a polarizable force field and molecular dynamics simulations
A force field model for calculating local field factors, i.e. the linear response of the local electric field for example at a nucleus in a molecule with respect to an applied electric field, is discussed. It is based on a combined charge-transfer and point-dipole interaction model for the polarizability, and thereby it includes two physically distinct terms for describing electronic polarization: changes in atomic charges arising from transfer of charge between the atoms and atomic induced dipole moments. A time dependence is included both for the atomic charges and the atomic dipole moments and if they are assumed to oscillate with the same frequency as the applied electric field, a model for frequency-dependent properties are obtained. Furthermore, if a life-time of excited states are included, a model for the complex frequency-dependent polariability is obtained including also information about excited states and the absorption spectrum. We thus present a model for the frequency-dependent local field factors through the first molecular excitation energy. It is combined with molecular dynamics simulations of liquids where a large set of configurations are sampled and for which local field factors are calculated. We are normally not interested in the average of the local field factor but rather in configurations where it is as high as possible. In electrical insulation, we would like to avoid high local field factors to reduce the risk for electrical breakdown, whereas for example in surface-enhanced Raman spectroscopy, high local field factors are desired to give dramatically increased intensities.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Communication: Nucleation rates of supersaturated aqueous NaCl using a polarizable force field
In this work, we use molecular dynamics simulations with a polarizable force field, namely, the modified AH/BK3 model [J. Kolafa, J. Chem. Phys. 145, 204509 (2016)], in combination with the forward flux sampling technique, to calculate the rates of homogeneous nucleation of NaCl from supersaturated aqueous solutions at 298 K and 1 bar. A non-polarizable model that reproduces the experimental equilibrium solubility {AH/TIP4P-2005 of Benavides et al. [J. Chem. Phys. 147, 104501 (2017)]} is also used for comparison. Nucleation rates calculated from the polarizable force field are found to be in good agreement with experimental measurements, while the non-polarizable model severely underestimates the nucleation rates. These results, in combination with our earlier study of a different non-polarizable force field [H. Jiang et al., J. Chem. Phys. 148, 044505 (2018)], lead to the conclusion that nucleation rates are sensitive to the details of force fields, and a good representation of nucleation rates may not be feasible using available non-polarizable force fields, even if these reproduce the equilibrium salt solubility. Finally, inclusion of polarization could be important for an accurate prediction of nucleation rates in salt solutions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A test on reactive force fields for the study of silica dimerization reactions
We studied silica dimerization reactions in the gas and aqueous phase by density functional theory (DFT) and reactive force fields based on two parameterizations of ReaxFF. For each method (both ReaxFF force fields and DFT), we performed constrained geometry optimizations, which were subsequently evaluated in single point energy calculations using the other two methods. Standard fitting procedures typically compare the force field energies and geometries with those from quantum mechanical data after a geometry optimization. The initial configurations for the force field optimization are usually the minimum energy structures of the ab initio database. Hence, the ab initio method dictates which structures are being examined and force field parameters are being adjusted in order to minimize the differences with the ab initio data. As a result, this approach will not exclude the possibility that the force field predicts stable geometries or low transition states which are realistically very high in energy and, therefore, never considered by the ab initio method. Our analysis reveals the existence of such unphysical geometries even at unreactive conditions where the distance between the reactants is large. To test the effect of these discrepancies, we launched molecular dynamics simulations using DFT and ReaxFF and observed spurious reactions for both ReaxFF force fields. Our results suggest that the standard procedures for parameter fitting need to be improved by a mutual comparative method.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Flexible and Transferable ab Initio Force Field for Zeolitic Imidazolate Frameworks: ZIF-FF
We have developed a transferable ab initio intramolecular force field for zeolitic imidazolate frameworks (ZIFs), “ZIF-FF”, that is capable of quantitatively describing the structural properties and relative stabilities of ZIFs. In contrast to nearly all prior force fields, ZIF-FF properly describes the relative stability of ZIF polymorphs, a crucial element in ZIF nucleation and crystal growth. Beginning with a general Amber force field (GAFF), Zn-related force field parameters were optimized against dispersion-corrected DFT-calculated properties using a genetic algorithm. We validated the resulting force field by examining bond and angle distributions, phonon density of states, mechanical properties, diffusion properties and via modeling a ZIF amorphization process. Moreover, we find that ZIF-FF is transferable, successfully describing relative stability of various ZIF surface structures, as well as the densities of ZIFs with diverse functionalized linkers.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events
Abstract Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations, which can result in low training efficiency and unpredictable errors when applied to structures not represented in the training set of the model. This severely limits the practical application of these models in systems with dynamics governed by important rare events, such as chemical reactions and diffusion. We present an adaptive Bayesian inference method for automating the training of interpretable, low-dimensional, and multi-element interatomic force fields using structures drawn on the fly from molecular dynamics simulations. Within an active learning framework, the internal uncertainty of a Gaussian process regression model is used to decide whether to accept the model prediction or to perform a first principles calculation to augment the training set of the model. The method is applied to a range of single- and multi-element systems and shown to achieve a favorable balance of accuracy and computational efficiency, while requiring a minimal amount of ab initio training data. We provide a fully open-source implementation of our method, as well as a procedure to map trained models to computationally efficient tabulated force fields.
36 MATERIALS SCIENCE↗
Force field preconditioned ab initio structure relaxation method
We present a general method to accelerate ab initio atomic structural relaxations. In this method, the conjugate gradient ab initio relaxation is preconditioned by a force field relaxation. This force field is constructed on-the-flight with the information of the ab initio forces and the current atomic configuration. At each ab initio relaxation step, the so-constructed force field is used to prerelax the system, with the relaxation direction as the preconditioned direction for the ab initio conjugated gradient method. The force field model and its parameters are rather general making this method applicable for a wide range of systems commonly used in material simulations. We report more than 80 different systems have been tested representing different cases in material simulations. Across the board, we find accelerations mostly over a factor of 2 and for some large systems with a factor of 6 ~ 9 . There is no case where the relaxation becomes worse. The code and lib for this method are provided, which can be used as a plugin in a standard ab initio atomic relaxation code.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Machine Learning Force Field Parameters from Ab Initio Data
Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (i.e., density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. Our results were further improved by introducing an offset factor during the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not involved in the objective function, but were only used for model validation. The best model, optimized from the QM data at the DFMP2(fc)/jul-cc-pVTZ level, appears to perform even better than the original AMOEBA force field (amoeba09.prm), which was optimized empirically to match liquid properties. The present effort shows the possibility of using machine learning techniques to develop descriptive polarizable force field using only QM data. The ML/GA strategy to optimize force fields parameters described here could easily be extended to other molecular systems.
97 MATHEMATICS AND COMPUTING↗
Refined Classical Force Field for Choline Chloride and Ethylene Glycol Mixtures over Wide Composition Range
In this work, a classical force field based on the General Amber Force Field (GAFF) was refined for the simulation of choline chloride (ChCl) and ethylene glycol (EG) mixtures over a wide composition range by scaling the partial charges and van der Waals parameters. The scaling factors were derived by fitting the simulation results to only eight experimental density and viscosity data points of pure EG, and ChCl/EG mixtures at 1:2, 1:4, and 1:6 molar ratios. Using the refined force field, properties essential for electrochemical applications such as density, viscosity, self-diffusion coefficient, and ionic conductivity were calculated, and excellent agreement to experimental results was found even for compositions and temperatures not used in the fitting procedure. In addition, new experimental data for density, viscosity, and ionic conductivity are reported as a function of temperature and composition for this mixture. To the best of our knowledge, this is the first classical force field developed for the study of ChCl/EG mixtures over a composition range that includes the eutectic point. Using the new model, the liquid dynamics was studied in terms of ionic conductivity. It was found that the dynamics in ChCl/EG mixtures with ChCl mole fraction higher than 20% is similar to that of ionic liquids, high temperature molten salts, and highly concentrated water-in-salt electrolytes.
25 ENERGY STORAGE↗
Development of an Advanced Force Field for Water Using Variational Energy Decomposition Analysis
Given the piecewise approach to modeling intermolecular interactions for force fields, they can be difficult to parametrize since they are fit to data like total energies that only indirectly connect to their separable functional forms. Furthermore, by neglecting certain types of molecular interactions such as charge penetration and charge transfer, most classical force fields must rely on, but do not always demonstrate, how cancellation of errors occurs among the remaining molecular interactions accounted for such as exchange repulsion, electrostatics, and polarization. In this work we present the first generation of the (many-body) MB-UCB force field that explicitly accounts for the decomposed molecular interactions commensurate with a variational energy decomposition analysis, including charge transfer, with force field design choices that reduce the computational expense of the MB-UCB potential while remaining accurate. We optimize parameters using only a single water molecule and water cluster data up through pentamers, with no fitting to condensed phase data, and we demonstrate that high accuracy is maintained when the force field is subsequently validated against conformational energies of larger water cluster data sets, radial distribution functions of the liquid phase, and the temperature dependence of thermodynamic and transport water properties. Finally, we conclude that MB-UCB is comparable in performance to MB-Pol but is less expensive and more transferable by eliminating the need to represent short-ranged interactions through large parameter fits to high order polynomials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A new force field including charge directionality for TMAO in aqueous solution
We propose a new force field for trimethylamine N-oxide (TMAO), which is designed to reproduce the long-lived and highly directional hydrogen bond between the TMAO oxygen (O{sub TMAO}) atom and surrounding water molecules. Based on the data obtained by ab initio molecular dynamics simulations, we introduce three dummy sites around O{sub TMAO} to mimic the O{sub TMAO} lone pairs and we migrate the negative charge on the O{sub TMAO} to the dummy sites. The force field model developed here improves both structural and dynamical properties of aqueous TMAO solutions. Moreover, it reproduces the experimentally observed dependence of viscosity upon increasing TMAO concentration quantitatively. The simple procedure of the force field construction makes it easy to implement in molecular dynamics simulation packages and makes it compatible with the existing biomolecular force fields. This paves the path for further investigation of protein-TMAO interaction in aqueous solutions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Physics-based, neural network force fields for reactive molecular dynamics: Investigation of carbene formation from [EMIM + ][OAc - ]
Reactive molecular dynamics simulations enable detailed understanding of solvent effects on chemical reaction mechanisms and reaction rates. While classical molecular dynamics using reactive force fields allows significantly longer simulation time scales and larger system sizes compared with ab initio molecular dynamics, constructing reactive force fields is a difficult and complex task. In this work, we describe a general approach following the Empirical Valence Bond (EVB) framework for constructing ab initio reactive force fields for condensed phase simulations by combining physics-based methods with neural networks (PB/NN). The physics-based terms ensure correct asymptotic behavior of electrostatic, polarization, and dispersion interactions, and are compatible with existing solvent force fields. Neural networks are utilized for versatile description of short-range orbital interactions within the transition state region, and accurate rendering of vibrational motion of the reacting complex. Herein, we demonstrate our methodology for a simple deprotonation reaction of the 1-ethyl-3-methylimidazolium (EMIM+) cation with acetate to form 1-ethyl- 3-methylimidazol-2-ylidene and acetic acid. Our PB/NN force field exhibits ~ 1 kJ/mol MAE accuracy within the transition state region for the gas-phase complex. To characterize solvent modulation of the reaction profile, we compute potentials of mean force (PMFs) for the gas-phase reaction as well as the reaction within a four ion cluster, and benchmark against ab initio molecular dynamics simulations. We find that the surrounding ionic environment significantly destabilizes formation of the carbene product, and we show that this effect is accurately captured by the reactive force field. By construction, the PB/NN potential may be directly employed for simulations of other solvents/chemical environments without additional parameterization.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
STEPs-SOL, a Peptoid Force Field Parameterization to Include Solvent Effects
As peptoids (N-substituted glycines) continue to gain popularity as a class of biomimetic polymers, the importance and demand for accurate force fields in molecular simulations also grow. Building on the vacuum-optimized Systematic and Extensible Force Field for Peptoids (STEPs) force field, here we present STEPs-SOL, a novel peptoid force field parametrization that effectively incorporates solvent effects to enhance the accuracy of peptoid simulations. The development of STEPs-SOL is based on the need for precise electrostatic modeling achieved through solvent-specific partial charge optimization. Here, our systematic approach significantly improves agreement with experimental measurements, reducing the mean absolute error in cis/trans ratio predictions (ΔG c/t ) by an average of 38% across multiple peptoid residues and solvent environments. This improved parametrization addresses computational challenges associated with nonbonded energies while maintaining a workflow that relies on high-level quantum mechanical data rather than depending solely on limited experimental equilibrium properties. By evaluating the effects of conformational bias in restrained electrostatic potential (RESP) charge generation and examining their impact on peptoid conformations in various solvents, we enhance our understanding of peptoid structural dynamics while providing a more accurate modeling framework.
force field↗
Perspective: Ab initio force field methods derived from quantum mechanics
It is often desirable to accurately and efficiently model the behavior of large molecular systems in the condensed phase (thousands to tens of thousands of atoms) over long time scales (from nanoseconds to milliseconds). In these cases, ab initio methods are difficult due to the increasing computational cost with the number of electrons. A more computationally attractive alternative is to perform the simulations at the atomic level using a parameterized function to model the electronic energy. Many empirical force fields have been developed for this purpose. However, the functions that are used to model interatomic and intermolecular interactions contain many fitted parameters obtained from selected model systems, and such classical force fields cannot properly simulate important electronic effects. Furthermore, while such force fields are computationally affordable, they are not reliable when applied to systems that differ significantly from those used in their parameterization. They also cannot provide the information necessary to analyze the interactions that occur in the system, making the systematic improvement of the functional forms that are used difficult. Ab initio force field methods aim to combine the merits of both types of methods. The ideal ab initio force fields are built on first principles and require no fitted parameters. Ab initio force field methods surveyed in this perspective are based on fragmentation approaches and intermolecular perturbation theory. This perspective summarizes their theoretical foundation, key components in their formulation, and discusses key aspects of these methods such as accuracy and formal computational cost. The ab initio force fields considered here were developed for different targets, and this perspective also aims to provide a balanced presentation of their strengths and shortcomings. Finally, this perspective suggests some future directions for this actively developing area.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Systematic Parameterization of Lignin for the CHARMM Force Field
Lignin is an abundant aromatic biopolymer within plant cell walls formed through radical coupling chemistry, whose composition and topology can vary greatly depending on the biomass source. Computational modeling provides a complementary approach to traditional experimental techniques to probe lignin interactions, lignin structure, and lignin material properties. However, current modeling approaches are limited based on the subset of lignin chemistries covered by existing lignin force fields. To fill the gap, we developed a comprehensive lignin force field that accounts for more lignin-lignin and lignin-carbohydrate interlinkages than existing lignin force fields, and also greatly expands the lignin monomer chemistries that can be modeled beyond simple alcohols and into the rich mixture of natural lignin varieties. The development of this force field utilizes recent developments in parameterization methodology, and synthesizes them into a workflow that combines target data from multiple molecules simultaneously into a single consistent and comprehensive parameter set. The parameter set represents a significant improvement to alternatives for atomic modeling of diverse lignin topologies, more accurately reproducing experimental observables while also significantly reducing the error relative to quantum calculations. The improved energetics, as well as the rigid adherence to CHARMM parameterization philosophy, enables simulation of lignin within its biological context with greater accuracy than was previously possible. The lignin force field presented here is therefore a crucial first step towards modeling lignin structure across a broad range of environments, including within plant cell walls where lignin is complexed with carbohydrates and deconstructed by bacterial or fungal enzymes, or as it exists within industrial solvent mixtures. Future simulations enabled by this updated lignin force field will thus lead to better chemical and structural understanding of lignin, providing new insight into its role in biomass recalcitrance or probing the potential for lignin to be used within industrial processes.
09 BIOMASS FUELS↗
Ab initio and force field molecular dynamics study of bulk organophosphorus and organochlorine liquid structures
Here, we performed ab initio molecular dynamics (AIMD) simulations to benchmark bulk liquid structures and to evaluate results from all-atom force field molecular dynamics (FFMD) simulations with the generalized Amber force field (GAFF) for organophosphorus (OP) and organochlorine (OC) compounds. Our work also addresses the current and important topic of force field validation, applied here to a set of nonaqueous organic liquids. Our approach differs from standard treatments, which validate force fields based on thermodynamic data. Utilizing radial distribution functions (RDFs), our results show that GAFF reproduces the AIMD-predicted asymmetric liquid structures moderately well for OP compounds that contain bulky alkyl groups. Among the OCs, RDFs obtained from FFMD overlap well with AIMD results, with some offsets in position and peak structuring. However, re-parameterization of GAFF for some OCs is needed to reproduce fully the liquid structures predicted by AIMD. The offsets between AIMD and FFMD peak positions suggest inconsistencies in the developed force fields, but, in general, GAFF is able to capture short-ranged and long-ranged interactions of OPs and OCs observed in AIMD. Along with the local coordination structure, we also compared enthalpies of vaporization. Overall, calculated bulk properties from FFMD compared reasonably well with experimental values, suggesting that small improvements within the FF should focus on parameters that adjust the bulk liquid structures of these compounds.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗