Lennard-Jones Parameters Research Articles

In Silico Screening of Metal-Organic Frameworks for Formaldehyde Capture with and without Humidity by Molecular Simulation.

Capturing formaldehydes (HCHO) from indoor air with porous adsorbents still faces challenges due to their low capacity and poor selectivity. Metal-organic frameworks (MOFs) with tunable pore properties were regarded as promising adsorbents for HCHO removal. However, the water presence in humid air heavily influences the formaldehyde capture performance due to the competition adsorption. To find suitable MOFs for formaldehyde capture and explore the relationship between MOFs structure and performance both in dry air and humid air, we performed grand canonical Monte Carlo (GCMC) molecular simulations to obtain working capacity and selectivity that evaluated the HCHO capture performance of MOFs without humidity. The results reveal that small pore size (~5 Å) and moderate heat of adsorption (40-50 kJ/mol) are favored for HCHO capture without water. It was found that the structure with a 3D cage instead of a 2D channel benefits the HCHO adsorption. Atoms in these high-performing MOFs should possess relatively small charges, and large Lennard-jones parameters were also preferred. Furthermore, it was indicated that Henry's constant (KH) can reflect the HCHO adsorption performance without humidity, in which the optimal range is 10-2-101. Hence, Henry's constant selectivity of HCHO over water (SKH HCHO/H2O) and HCHO over mixture components (H2O, N2, and O2) was obtained to screen MOFs at an 80% humidity condition. It was suggested that SKH for the mixture component overestimates the influence of N2 and O2, in which the top structures absorb a quantity of water in GCMC simulation, while SKH HCHO/H2O can efficiently find high-performing MOFs for HCHO capture at humidity in low adsorption pressure. The ECATAT found in this work has 0.64 mol/kg working capacity, and barely adsorbs water during 0-1 bar, which is the promising candidate MOF for HCHO capture.

Phase equilibria molecular simulations of hydrogen hydrates via the direct phase coexistence approach.

We report the three-phase (hydrate-liquid water-vapor) equilibrium conditions of the hydrogen-water binary system calculated with molecular dynamics simulations via the direct phase coexistence approach. A significant improvement of ∼10.5K is obtained in the current study, over earlier simulation attempts, by using a combination of modifications related to the hydrogen model that include (i) hydrogen Lennard-Jones parameters that are a function of temperature and (ii) the water-guest energy interaction parameters optimized further by using the Lorentz-Berthelot combining rules, based on an improved description of the solubility of hydrogen in water.

Comparison of the United- and All-Atom Representations of (Halo)alkanes Based on Two Condensed-Phase Force Fields Optimized against the Same Experimental Data Set.

The level of accuracy that can be achieved by a force field is influenced by choices made in the interaction-function representation and in the relevant simulation parameters. These choices, referred to here as functional-form variants (FFVs), include for example the model resolution, the charge-derivation procedure, the van der Waals combination rules, the cutoff distance, and the treatment of the long-range interactions. Ideally, assessing the effect of a given FFV on the intrinsic accuracy of the force-field representation requires that only the specific FFV is changed and that this change is performed at an optimal level of parametrization, a requirement that may prove extremely challenging to achieve in practice. Here, we present a first attempt at such a comparison for one specific FFV, namely the choice of a united-atom (UA) versus an all-atom (AA) resolution in a force field for saturated acyclic (halo)alkanes. Two force-field versions (UA vs AA) are optimized in an automated way using the CombiFF approach against 961 experimental values for the pure-liquid densities ρliq and vaporization enthalpies ΔHvap of 591 compounds. For the AA force field, the torsional and third-neighbor Lennard-Jones parameters are also refined based on quantum-mechanical rotational-energy profiles. The comparison between the UA and AA resolutions is also extended to properties that have not been included as parameterization targets, namely the surface-tension coefficient γ, the isothermal compressibility κT, the isobaric thermal-expansion coefficient αP, the isobaric heat capacity cP, the static relative dielectric permittivity ϵ, the self-diffusion coefficient D, the shear viscosity η, the hydration free energy ΔGwat, and the free energy of solvation ΔGche in cyclohexane. For the target properties ρliq and ΔHvap, the UA and AA resolutions reach very similar levels of accuracy after optimization. For the nine other properties, the AA representation leads to more accurate results in terms of η; comparably accurate results in terms of γ, κT, αP, ϵ, D, and ΔGche; and less accurate results in terms of cP and ΔGwat. This work also represents a first step toward the calibration of a GROMOS-compatible force field at the AA resolution.

Continuum Modeling with Functional Lennard-Jones Parameters for Methane Storage inside Various Carbon Nanostructures

Methane capture and storage are of particular importance for the development of new technology to reduce the effects of climate change and global warming. Carbon-based nanomaterials are among several porous nanomaterials proposed as potential candidates for methane storage. In this paper, we adopt a new continuum approach with functional Lennard-Jones parameters to provide interaction energies for methane inside carbon nanostructures, namely fullerenes, nanotube bundles, and nanocones. This study provides a significant improvement to previous continuum modeling approaches using the Lennard-Jones potential.

Nonbonded Force Field Parameters from Minimal Basis Iterative Stockholder Partitioning of the Molecular Electron Density Improve CB7 Host-Guest Affinity Predictions.

Binding affinity prediction by means of computer simulation has been increasingly incorporated in drug discovery projects. Its wide application, however, is limited by the prediction accuracy of the free energy calculations. The main error sources are force fields used to describe molecular interactions and incomplete sampling of the configurational space. Organic host-guest systems have been used to address force field quality because they share similar interactions found in ligands and receptors, and their rigidity facilitates configurational sampling. Here, we test the binding free energy prediction accuracy for 14 guests with an aromatic or adamantane core and the CB7 host using molecular electron density derived nonbonded force field parameters. We developed a computational workflow written in Python to derive atomic charges and Lennard-Jones parameters with the Minimal Basis Iterative Stockholder method using the polarized electron density of several configurations of each guest in the bound and unbound states. The resulting nonbonded force field parameters improve binding affinity prediction, especially for guests with an adamantane core in which repulsive exchange and dispersion interactions to the host dominate.

Water-Graphene non-bonded interaction parameters: Development and influence on molecular dynamics simulations

Molecular dynamics simulations have been extensively used to study water-graphene systems, and the force field parameters are vital for the accuracy of simulation results. Herein, water-graphene non-bonded Lennard-Jones (LJ) parameters were developed according to the experimental water contact angle (θ), and were further validated by the quantum-chemistry calculated water-graphene interaction energy (Eint). The LJ parameters were developed based on various water models, and were employed to simulated a large diversity of water-graphene systems (e.g. water nanodroplet (or one water molecule) on graphene, water slab-graphene interface, graphene nanochannel connected to a water reservoir, water confined in graphene nanochannel, etc.), with thorough comparison against LJ parameters derived from Lorentz-Berthelot mixing rule. All these abundant data were studied in-depth to yield plenty of insights (some were rarely reported) that could be extended to other two-dimensional materials or systems, e.g. linear correlation of cos θ ∼ LJ parameter and the slope is also linear with the reciprocal of water’s surface tension, linear correlation of Eint ∼ density of the 1st water layer on graphene, correlation of Eint ∼ water molecules’ residue time on graphene, (roughly) linear correlation of water density inside graphene 2D nanochannel ∼ water’s diffusivity etc.

Accurate Description of Solvent-Exposed Salt Bridges with a Non-polarizable Force Field Incorporating Solvent Effects.

The strength of salt bridges resulting from the interaction of cations and anions is modulated by their environment. However, polarization of the solvent molecules by the charged moieties makes the accurate description of cation-anion interactions in an aqueous solution by means of a pairwise additive potential energy function and classical combination rules particularly challenging. In this contribution, aiming at improving the representation of solvent-exposed salt-bridge interactions with an all-atom non-polarizable force field, we put forth here a parametrization strategy. First, the interaction of a cation and an anion is characterized by hybrid quantum mechanical/molecular mechanics (QM/MM) potential of mean force (PMF) calculations, whereby constantly exchanging solvent molecules around the ions are treated at the quantum mechanical level. The Lennard-Jones (LJ) parameters describing the salt-bridge ion pairs are then optimized to match the reference QM/MM PMFs through the so-called nonbonded FIX, or NBFIX, feature of the CHARMM force field. We apply the new set of parameters, coined CHARMM36m-SBFIX, to the calculation of association constants for the ammonium-acetate and guanidinium-acetate complexes, the osmotic pressures for glycine zwitterions, guanidinium, and acetate ions, and to the simulation of both folded and intrinsically disordered proteins. Our findings indicate that CHARMM36m-SBFIX improves the description of solvent-exposed salt-bridge interactions, both structurally and thermodynamically. However, application of this force field to the standard binding free-energy calculation of a protein-ligand complex featuring solvent-excluded salt-bridge interactions leads to a poor reproduction of the experimental value, suggesting that the parameters optimized in an aqueous solution cannot be readily transferred to describe solvent-excluded salt-bridge interactions. Put together, owing to their sensitivity to the environment, modeling salt-bridge interactions by means of a single, universal set of LJ parameters remains a daunting theoretical challenge.

Refinement of the Optimized Potentials for Liquid Simulations Force Field for Thermodynamics and Dynamics of Liquid Alkanes.

Torsion and Lennard-Jones parameters of the optimized potentials for liquid simulations (OPLS) all-atom force field have been refined for describing thermodynamics and dynamics of a wide range of liquid alkanes. Monte Carlo statistical mechanics (MC) and molecular dynamics (MD) simulations were carried out. For thermodynamics properties, MC simulations with truncated electrostatic interactions performed very closely to MD simulations with a Verlet neighbor list and the particle mesh Ewald algorithm. The average errors in comparison with experimental data for computed properties were improved with the modified force field (OPLS/2020), especially for long-chain alkanes. For liquid densities, heats of vaporization, and free energies of hydration, the average errors are 0.01 g/cm3, 0.2 kcal/mol, and ca. 0.5 kcal/mol, respectively; significant gains were made for relative heats of vaporization of isomeric series. Results for self-diffusion coefficients also reproduce experimental data well for linear alkane liquids up to hexadecane. The new force field is suitable for use in improved modeling of myriad systems of importance in chemistry, biology, and materials science.

Mechanism of oscillation of aqueous electrical double layer capacitance: Role of solvent

The present classical density functional theory (CDFT) study is focused on role of solvent in differential capacitance (Cd) behavior of aqueous electrolyte electric double-layer capacitor (EDLC). In the CDFT, water molecule is described by a solvent primitive model, which is constructed to give two experimentally measured aandb parameters in the van der Waals equation of state of water; Lennard-Jones parameters of both cation and anion are chosen to be reminiscent of properties of K+ andCl-1; a structureless and soft wall comprised of carbon atoms is considered to represent a graphene electrode. Main findings are summarized as follows. (i) The CdH (H is separation between two graphene electrodes) curve is always shifted up (at lower electrode voltage) or down (at higher electrode voltage) by increasing the electrolyte bulk concentrationc. The anomalous negative correlation between c and Cd at high voltage originates from the so-called charge inversion and one additional weak co-ion peak located closer to the electrode surface at higher voltage. (ii) Oscillation periods of CdH curves are basically fixed at 3 Å regardless of molecular characteristics of counter- and co-ions, c value, and electrode voltage; explicit consideration of the solvent granularity and polarity greatly reduces the attenuation rate of the oscillation with pore size. Increase of CdH with pore size reducing towards the ion size, does occur but only with moderate magnitude; a main CdH extreme value occurs approximately around H being two times ion diameter, which can be either a maximum or a minimum, depending on electrolyte bulk concentration, polarity and strength of the electrode. These oscillation features differ greatly from those observed in solvent-free ionic liquids and continuum solvent model. (iii) Potential of zero charge ψpzc for the case of small size of cation and weaker LJ interaction of the cation with solvent molecule in large number, is necessarily positive and its value is positively correlated with the c value; minimum point ψMin of the Cdψs curve is always larger than theψpzc, not consistent with the Gouy-Chapman theory, and both the ψpzcH curve and ψMinH curve change quasi periodically with the pore size H also in 3 Å cycle. (iv) Theoretical analysis shows that the capacitance behavior is mainly controlled by the number and position of solvent peaks and their changes with pore size, while distribution of ions is largely controlled by their LJ interaction with solvent. This shows the importance of the solvent in modulating the capacitance behavior.

A Lennard-Jones based surface tension analogy model for liquid breakup

The breakup of liquid drops is an important phenomenology for many applications. We approach this problem with the objective of improving methods for modeling the impulse and impact dispersal of liquids in transportation accident scenarios. These scenarios can be distinguished from many other simpler problems due to the quantity of liquid and the complexity of the intermediate liquid morphology. These differences necessitate alternative (lower computational cost and lower fidelity) approaches to the problem compared to much of the historical modeling work. This work leverages a recently implemented model for inter-particle forces in a Lagrangian/Eulerian computational fluid dynamics (CFD) code. The inter-particle force model is inspired by molecular dynamics methods. It employs a Lennard-Jones (LJ) attractive force and a spring-based repulsive force that is governed by LJ parameters. The LJ parameters are related to the bulk fluid properties through a theoretical relationship to the surface tension. Methods are developed for modifying the single particle aerodynamic drag term, depending on the new notion of particle connectivity. These methods are evaluated for potential utilization in practical simulations. Breakup experiments for drops in flows from prior studies suggest a critical Weber number relating to the onset of breakup for a drop. These data are replicated with the proposed model and it is shown that the proposed method can reasonably reproduce aspects of breakup for a range of scales with only a single tuned parameter.

Modeling Gd3+ Complexes for Molecular Dynamics Simulations: Toward a Rational Optimization of MRI Contrast Agents.

The correct parametrization of lanthanide complexes is of the utmost importance for their characterization using computational tools such as molecular dynamics simulations. This allows the optimization of their properties for a wide range of applications, including medical imaging. Here we present a systematic study to establish the best strategies for the correct parametrization of lanthanide complexes using [Gd(DOTA)]- as a reference, which is used as a contrast agent in MRI. We chose the bonded model to parametrize the lanthanide complexes, which is especially important when considering the study of the complex as a whole (e.g., for the study of the dynamics of its interaction with proteins or membranes). We followed two strategies: a so-called heuristic approach employing strategies already published by other authors and another based on the more recent MCPB.py tool. Adjustment of the Lennard-Jones parameters of the metal was required. The final topologies obtained with both strategies were able to reproduce the experimental ion to oxygen distance, vibrational frequencies, and other structural properties. We report a new strategy to adjust the Lennard-Jones parameters of the metal ion in order to capture dynamic properties such as the residence time of the capping water (τm). For the first time, the correct assessment of the τm value for Gd-based complexes was possible by recording the dissociative events over up to 10 μs all-atom simulations. The MCPB.py tool allowed the accurate parametrization of [Gd(DOTA)]- in a simpler procedure, and in this case, the dynamics of the water molecules in the outer hydration sphere was also characterized. This sphere was divided into the first hydration layer, an intermediate region, and an outer hydration layer, with a residence time of 18, 10 and 19 ps, respectively, independent of the nonbonded parameters chosen for Gd3+. The Lennard-Jones parameters of Gd3+ obtained here for [Gd(DOTA)]- may be used with similarly structured gadolinium MRI contrast agents. This allows the use of molecular dynamics simulations to characterize and optimize the contrast agent properties. The characterization of their interaction with membranes and proteins will permit the design of new targeted contrast agents with improved pharmacokinetics.

Accurate and Efficient Estimation of Lennard–Jones Interactions for Coarse-Grained Particles via a Potential Matching Method

The Lennard-Jones (LJ) energy functions are commonly used to describe the nonbonded interactions in bulk coarse-grained (CG) models, which contribute significantly to the stabilization of a local binding configuration or a self-assembly system. In many cases, systematic development of the LJ interaction parameters in a CG model requires a comprehensive sampling of the objective molecules at the all-atom (AA) level, which is therefore extremely time-consuming for large systems. Inspired by the concept of electrostatic potential (ESP), we define the LJ static potential (LJSP), by which the embedding potential energy surface can be constructed analytically. A semianalytic approach, namely, the LJSP matching method, is developed here to derive the CG parameters by minimizing the LJSP difference between the AA and the CG models, which provides a universal way to derive the CG LJ parameters from the AA models without doing presampling. The LJSP matching method is successful not only in deriving the LJ interaction energy landscape in the CG models for proteins, lipids, and DNA but also in reproducing the critical properties such as intermediate structures and enthalpy contributions as exemplified in simulating the self-assembly process of the dipalmitoylphosphatidylcholine (DPPC) lipids.

A Polarizable Cationic Dummy Metal Ion Model.

A novel locally polarizable multisite model based on the original cation dummy atom (CDA) model is described for molecular dynamics simulations of ions in condensed phases. Polarization effects are introduced by the electronegativity equalization model (EEM) method where charges on the metal ion and its dummy atoms can fluctuate to respond to the environment. This model includes explicit polarization and ion-induced interactions and can be coupled with nonpolarizable or polarizable water models, making it more transferable to simpler force fields. This approach allows us to enhance the original fixed charge CDA model where the charge distribution cannot adapt to the local solvent structure. To illustrate the new CDApol model, we examined properties of the Zn2+, Al3+, and Zr4+ ions in aqueous solution. The polarizable model and Lennard-Jones parameters were refined for octahedrally coordinated Zn2+, Al3+, and Zr4+ CDAs to reproduce thermodynamic and geometrical properties. Using this locally polarizable model, we were able to obtain the experimental hydration free energy, ion-oxygen distance, and coordination number coupled with the standard 12-6 Lennard-Jones model. This model can be used in myriad additional applications where local polarization and charge transfer is important.

Consistent Picture of Phosphate–Divalent Cation Binding from Models with Implicit and Explicit Electronic Polarization

The binding of divalent cations to the ubiquitous phosphate group is essential for a number of key biological processes, such as DNA compaction, RNA folding, or interactions of some proteins with membranes. Yet, probing their binding sites, modes, and associated binding free energy is a challenge for both experiments and simulations. In simulations, standard force fields strongly overestimate the interaction between phosphate groups and divalent cations. Here, we examine how different strategies to include electronic polarization effects in force fields─implicitly, through the use of scaled charges or pair-specific Lennard-Jones parameters, or explicitly, with the polarizable force fields Drude and AMOEBA─capture the interactions of a model phosphate compound, dimethyl phosphate, with calcium and magnesium divalent cations. We show that both implicit and explicit approaches, when carefully parameterized, are successful in capturing the overall binding free energy and that common trends emerge from the comparison of different simulation approaches. Overall, the binding is very moderate, slightly weaker for Ca2+ than Mg2+, and the solvent-shared ion pair is slightly more stable than the contact monodentate ion pair. The bidentate ion pair is higher in energy (or even fully unstable for Mg2+). Our results thus suggest practical ways to capture the divalent cations with biomolecular phosphate groups in complex biochemical systems. In particular, the computational efficiency of implicit models makes them ideally suited for large-scale simulations of biological assemblies, with improved accuracy compared to state-of-the-art fixed-charge force fields.

Improving Force Field Accuracy by Training against Condensed-Phase Mixture Properties.

Developing a sufficiently accurate classical force field representation of molecules is key to realizing the full potential of molecular simulations as a route to gaining a fundamental insight into a broad spectrum of chemical and biological phenomena. This is only possible, however, if the many complex interactions between molecules of different species in the system are accurately captured by the model. Historically, the intermolecular van der Waals (vdW) interactions have primarily been trained against densities and enthalpies of vaporization of pure (single-component) systems, with occasional usage of hydration free energies. In this study, we demonstrate how including physical property data of binary mixtures can better inform these parameters, encoding more information about the underlying physics of the system in complex chemical mixtures. To demonstrate this, we retrain a select number of Lennard-Jones parameters describing the vdW interactions of the OpenFF 1.0.0 (Parsley) fixed charge force field against training sets composed of densities and enthalpies of mixing for binary liquid mixtures as well as densities and enthalpies of vaporization of pure liquid systems and assess the performance of each of these combinations. We show that retraining against the mixture data improves the force field's ability to reproduce mixture properties, including solvation free energies, correcting some systematic errors that exist when training vdW interactions against properties of pure systems only.

Improving 1-propanol force field: a new methodology.

A new force field for 1-propanol, in the united and all atom models, has been obtained by combining two different empirical methodologies. The first was developed by scaling atom charges and Lennard-Jones parameters to fit the dielectric constant, surface tension, and density; this methodology is named three steps systematic parameterization procedure (3SSPP), as reported by Pérez de la Luz et al. (J Chem Theory Comput 14:5949-5958, 2018). The second methodology consists of moving these parameters and together with the bond distance to obtain the liquid-vapor phase diagram of the CO2 molecule as discussed by Harris and Yung (J Phys Chem 99:12021-12024, 1995). The last methodology is used to obtain the self-diffusion coefficient, which was not consider in the 3SSPP. The 3SSPP/bond methodology is the 3SSPP plus the bond distance scaling. With this new methodology, the experimental density, dielectric constant, surface tension, and self-diffusion coefficient at ambient temperature could be achieved. Furthermore, we show the temperature dependence of the aforementioned properties. The static structure factors are in accordance with the experimental spectrum. Solubility is increased to the experimental value for the united atom (UA) model after applying this methodology and for all atom (AA) scheme, the experimental solubility value is maintained. Graphical abstract The reduction in bond distance of the 1-propanol molecule does not modify the structure factor.

Systematic Evaluation of Ion Diffusion and Water Exchange.

As a fundamental property of all fluids, diffusion plays myriad roles in both science and our daily lives. Diffusive properties of many liquids including water have been extensively studied both experimentally and theoretically, while for transition metal ions, there exist significant experimental data that have not been extensively studied theoretically. Hence, high-confidence predictions for challenging systems like radioactive ions that are biohazardous cannot be reliably generated. In this work, a workflow named ISAIAH (Ion Simulation using AMBER for dIffusion Action when Hydrated) was designed to accurately simulate the diffusion coefficients of 15 monoatomic ions with charges varying from -1 to +3 in four water models. As the results indicate, good agreement with experimental values was achieved, leading us to select 239Pu4+ (for which no experimental data are available) as a candidate ion to make a theoretical prediction of its diffusion coefficient in water. Among all the force field parameter sets, the ones parametrized using an augmented 12-6-4 Lennard-Jones (LJ) potential showed lower average unsigned errors (AUE) for ions of various radii and electron configurations relative to some 12-6 LJ parameters. This observation agrees well with the fact that diffusion is affected by both the hydration free energy (HFE) and the ion-oxygen distance (IOD) between solute and solvent molecules, both of which are handled well by the 12-6-4 model.

Harnessing Deep Learning for Optimization of Lennard-Jones Parameters for the Polarizable Classical Drude Oscillator Force Field.

The outcomes of computational chemistry and biology research, including drug design, are significantly influenced by the underlying force field (FF) used in molecular simulations. While improved FF accuracy may be achieved via inclusion of explicit treatment of electronic polarization, such an extension must be accompanied by optimization of van der Waals (vdW) interactions, in the context of the Lennard-Jones (LJ) formalism in the present study. This is particularly challenging due to the extensive nature of chemical space combined with the correlated nature of LJ parameters. To address this challenge, a deep learning (DL)-based parametrization framework is developed, allowing for sampling of wide ranges of LJ parameters targeting experimental condensed phase thermodynamic properties. The present work utilizes this framework to develop the LJ parameters for atoms associated with four distinct groups covering 10 different atom types. Final parameter selection was facilitated by quantum mechanical data on rare-gas interactions with the training set molecules. The chosen parameters were then validated through experimental hydration free energies and condensed phase thermodynamic properties of validation set molecules to confirm transferability. The ultimate outcome of utilizing this framework is a set of LJ parameters in the context of the polarizable Drude FF, which demonstrated improvement in the reproduction of both experimental pure solvent and crystal properties and hydration free energies of the molecules compared to the additive CHARMM General FF (CGenFF) including the ability of the Drude FF to accurately reproduce both experimental pure solvent properties and hydration free energies. The study also shows how correlations between difference in the reproduction of condensed phase data between model compounds may be used to direct the selection of new atom types and training set molecules during FF development.

Theoretical Investigations for Kinetics of the Chemical Reactions: H + SiClx (x = 1, 2, 3).

Hydrogen atoms and SiClx (x = 1, 2, 3) radicals coexist during the hydrogenation of silicon tetrachloride (STC, SiCl4), an important process in the fabrication of industrial polysilicon. In this work, the mechanisms and kinetics of the reactions between H and SiClx (x = 1, 2, 3) were studied by theory. The structures and vibrational frequencies of reactants, products, intermediates, and transition states (TSs) were determined at the B2PLYP/may-cc-pVTZ level. The single-point energies of minima and saddle points were refined using the coupled-cluster single-double with triple perturbative (CCSD(T)) with the complete basis set extrapolation method. Some special treatments were designed to obtain reliable wave functions for unimolecular reactions without tight TSs by the density functional theory. Subsequently, Lennard-Jones (L-J) parameters between each intermediate (SiHClx) and bath gas (He) were obtained at the MP2/jul-cc-pVTZ level to derive reliable temperature- and pressure-dependent rate coefficients for unimolecular reactions according to the variational Rice-Ramsperger-Kassel-Marcus theory. For bimolecular reactions, rate coefficients were determined by the variational transition-state theory. The rate coefficients of barrierless reactions were derived based on the loose TSs with the maximum free energy. Finally, the master equation analysis was used to investigate the variation of the rate coefficients with pressure and temperature in the activated paths.

Optimizing Lennard-Jones parameters by coupling single molecule and ensemble target data

This contribution is a proof-of-concept that a diverse set of training observables leads to a meaningful force field even if a very limited number of thermodynamic state points (i.e. temperatures) is used. This approach generates optimized force-field parameters, enabling the user to extract additional information from MD simulations. The ultimate goal is to extend this approach and enable an increased amount of observables to be reproduced using a single force field for a series of chemically similar molecules (e.g. oligomer hydrocarbons). Specifically, we present a new optimization strategy to expand the limits of existing force fields and investigate how much added error is introduced to already reproducible observables. For this purpose, we optimized the Lennard-Jones parameters of n-octane using an isolated molecule's relative conformational energies and the liquid-phase density (293.15 K) for a molecular ensemble as optimization objectives. To test the impact on other observables, additional substances and temperatures that were not part of the training set were evaluated. This evaluation includes the surface tension, viscosity and density for n-hexane, n-heptane, n-octane and n-nonane at 293.15, 315.15 and 338.15 K. We show that it is possible to expand the limits of a force field, improving its overall accuracy at a small cost to its previously well-reproduced observables. Additionally, we propose approaches for further developments of the optimization strategy to increase the observables accuracies that suffer a loss in exchange for the capability of reproducing additional properties.