Optimization of the anisotropic united atoms intermolecular potential forn-alkanes

On De Gennes narrowing of fluids confined at the molecular scale in nanoporous materials

Beyond well-documented confinement and surface effects arising from the large internal surface and severely confining porosity of nanoporous hosts, the transport of nanoconfined fluids remains puzzling in many aspects. With striking examples such as memory, i.e., non-viscous effects, intermittent dynamics, and surface barriers, the dynamics of fluids in nanoconfinement challenge classical formalisms (e.g., random walk, viscous/advective transport)-especially for molecular pore sizes. In this context, while molecular frameworks such as intermittent Brownian motion, free volume theory, and surface diffusion are available to describe the self-diffusion of a molecularly confined fluid, a microscopic theory for collective diffusion (i.e., permeability), which characterizes the flow induced by a thermodynamic gradient, is lacking. Here, to fill this knowledge gap, we invoke the concept of "De Gennes narrowing," which relates the wavevector-dependent collective diffusivity D0(q) to the fluid structure factor S(q). First, using molecular simulation for a simple yet representative fluid confined in a prototypical solid (zeolite), we unravel an essential coupling between the wavevector-dependent collective diffusivity and the structural ordering imposed on the fluid by the crystalline nanoporous host. Second, despite this complex interplay with marked Bragg peaks in the fluid structure, the fluid collective dynamics is shown to be accurately described through De Gennes narrowing. Moreover, in contrast to the bulk fluid, the departure from De Gennes narrowing for the confined fluid in the macroscopic limit remains small as the fluid/solid interactions in severe confinement screen collective effects and, hence, weaken the wavevector dependence of collective transport.

Prediction of ionic conductivity from adiabatic heating in non-equilibrium molecular dynamics on various test systems

CONTEXT

The evaluation of ionic conductivity through atomistic modeling typically involves calculating diffusion coefficients, which often necessitates simulations spanning several hundreds of nanoseconds. This study introduces a less computationally demanding approach based on non-equilibrium molecular dynamics applicable to a wide range of systems.

METHOD

Ionic conductivity is determined by evaluating the Joule heating effect recorded during non-equilibrium molecular dynamics (NEMD) simulations. These simulations which involve applying a uniform electric field using classical force fields in LAMMPS are conducted within the MedeA software environment. The conductivity value for a specific temperature can thus be obtained from a single simulation together with an estimation of the associated uncertainty. Guidelines for selecting NEMD parameters such as electric field intensity and initial temperature are proposed to satisfy linear irreversible transport.

RESULTS

The protocol presented in this study is applied to four different types of systems, namely, (i) molten NaCl, (ii) NaCl and LiCl aqueous solutions, (iii) solution of ionic liquid with two solvents, and (iv) NaX zeolites in the anhydrous and hydrated states. The main advantages of the proposed protocol are simplicity of implementation (eliminating the need to store individual ion trajectories), reliability (low electric field, linear response, no perturbation of the equations of motion by a thermostat), and a wide range of applications. The estimated contribution of field-induced drift motion of ions to kinetic energy appears very low, justifying the use of standard kinetic energy in the method. For each system, the reported influence of temperature, ion concentration, solvent nature, or hydration is correctly predicted.

Determining Lennard-Jones Parameters Using Multiscale Target Data through Presampling-Enhanced, Surrogate-Assisted Global Optimization

Force field-based models are a Newtonian mechanics approximation of reality and are inherently noisy. Coupling models from different molecular scale domains (including single, gas-phase molecules up to multimolecule, condensed phase ensembles) is difficult, which is also the case for finding solutions that transfer well between the scales. In this contribution, we introduce a surrogate-assisted algorithm to optimize Lennard-Jones parameters for target data from different scale domains to overcome the difficulties named above. Specifically, our approach combines a surrogate-assisted global evolutionary optimization method with a presampling phase that takes advantage of one scale domain being less computationally expensive to evaluate. The algorithm's components were evaluated individually, elucidating their individual merits. Our findings show that the process of parametrizing force fields can significantly benefit from both the presampling method, which alleviates the need to have a good initial guess for the parameters, and the surrogate model, which improves efficiency.

Comprehensive Automated Routine Implementation, Validation, and Benchmark of the Anisotropic Force Field (AUA4) Using Python and GROMACS

Molecular simulation users are sometimes discouraged from using specific molecular models because of the inconvenience of finding the force field parameters and preparing and validating the topology files. To facilitate this process and make the accurate anisotropic force field AUA4 available to molecular dynamics users, we have created and validated an automated topology and coordinate file creation routine for the GROMACS molecular simulation software. In the present work, we describe the AUA4, explain its particularities and how it was implemented, thoroughly validating the implementation, and for the first time, perform a molecular dynamics benchmark for this transferable force field. Several properties were computed, namely, liquid density, vapor pressure, and vaporization enthalpy by conducting explicit vapor-liquid interface simulations. The results evidence the correct implementation showing slight deviations from the parametrization studies. The benchmark shows the superior predictive capability of the AUA4 in recreating liquid density (RMSD equal to 17.0 kg/m³) and vaporization enthalpy (RMSD equal to 1.3 kJ/mol) compared to other transferable force fields. In addition, its superior computational time performance doubles or even triples compared to an all-atom force field such as the OPLS, depending on whether the workstation counts with GPU.

gmak: A Parameter-Space Mapping Strategy for Force-Field Calibration

In the context of classical molecular simulations, the accuracy of a force field is highly influenced by the values of the relevant simulation parameters. In this work, a parameter-space mapping (PSM) workflow is proposed to aid in the calibration of force-field parameters, based mainly on the following features: (i) regular-grid discretization of the search space; (ii) partial sampling of the search-space grid; (iii) training of surrogate models to predict the estimates of the target properties for nonsampled parameter sets; (iv) post hoc interpretation of the results in terms of multiobjective optimization concepts; (v) attenuation of statistical errors achieved via empiric extension of the duration of the simulations; (vi) iterative search-space translation according to a user-defined scalar objective function that measures the accuracy of the force field (e.g., the weighted root-mean-square deviation of the target properties relative to the reference data). This combination of features results in a hybrid of a single- and a multiobjective optimization strategy, allowing for the approximate determination of both a local minimum of the chosen objective function and its neighboring Pareto efficient points. The PSM workflow is implemented in the extensible Python program gmak, which is made available in the Git repository at http://github.com/mssm-labmmol/gmak. Using this implementation, the PSM workflow was tested in a proof-of-concept fashion in the recalibration of the Lennard-Jones parameters of the 3-point Optimal Point Charge (OPC3) water model for compatibility with the GROMOS treatment of nonbonded interactions. The recalibrated model reproduces typical pure-liquid properties with an accuracy similar to the original OPC3 model and represents a significant improvement relative to the Simple Point Charge (SPC) model, which is the official recommendation for simulations using GROMOS force fields.

Polarizable Force Field for Acetonitrile Based on the Single-Center Multipole Expansion

A polarizable potential function describing the interaction between acetonitrile molecules is introduced. The molecules are described as rigid and linear, with three mass sites corresponding to the CH₃ group (methyl, Me), the central carbon atom (C), and the nitrogen atom (N). The electrostatic interaction is represented using a single-center multipole expansion as has been done previously for H₂O [Wikfeldt et al., Phys. Chem. Chem. Phys. 15, 16542 (2013)], by including multipole moments from dipole up to and including hexadecapole, as well as anisotropic dipole-dipole, dipole-quadrupole, and quadrupole-quadrupole polarizability tensors. The model is free of point charges. The non-electrostatic part is described in a pair-wise fashion by a Born-Mayer repulsion and damped dispersion attraction. The potential function is parameterized to fit the interaction energy of small (CH₃CN)_n, n = 2-6, clusters calculated using the PBE0 hybrid functional with an additional atomic many-body dispersion contribution. The parameterized potential function is found to compare well with results of the electronic structure calculations of dissociation curves for different dimer orientations and cohesive properties (the equilibrium volume, cohesive energy, and the bulk modulus) of the α-phase of acetonitrile crystal. The average value of the molecular dipole moment obtained in the α-phase is 5.53 D, corresponding to ca. 40% increase as compared to the dipole moment of an isolated acetonitrile molecule, 3.92 D. The calculated densities of solid and liquid acetonitrile turn out to be 8-10% higher than experimental values. This appears to be caused by an overestimate of the atomic many-body dispersion interaction in the density functional calculations used as input in the parametrization of the potential function.

Exploration for the Optical Properties and Fluorescent Prediction of Nitrotriazole and Nitrofurazan: First-Principles and TD-DFT Calculations

High-energy materials containing azole and furazan have revealed numerous properties; however, the underlying optical properties need to be solved. Meanwhile, the uncertainty for the choice of fluorescent matrix materials and the flexible situational conditions prompted us to estimate the optical and fluorescent properties of 5,5'-dinitro-2H,2H'-3,3'-bi-1,2,4-triazole (DNBT), 4,4'-dinitroazolefurazan (DNAF), and 4,4'-dinitro-3,3'-4,3'-ter-1,2,5-oxadiazole (DNTO). The first-principles calculation with improved dispersion correction terms and time-dependent density functional theory were utilized to calculate the absorbance and excitation energy of DNBT, DNAF, and DNTO, as well as characterization for their crystal structure, electronic structure, molecular orbitals, and so forth, synchronously. In this work, the absorbance anisotropy of DNBT and DNTO is stronger than that of DNAF. The absorbance for each of the (0,0,1) crystal planes in the three compounds is greater than that of the other two crystal planes. Moreover, DNBT has the maximum absorbance on the (0,0,1) crystal plane. The N-N-H from DNBT and N-O-N from DNTO and DNAF are responsible for these results, while N=N in DNAF weakens the performance of N-O-N. UV-vis spectra show that the maximum absorption wavelengths λmax for DNBT, DNAF, and DNTO are 225, 228, and 201 nm, respectively. The number of five-membered rings and the coplanarity of groups in the intermolecular non-conjugation interaction potentially improve this ability due to the results from the crystal diffraction analysis. In addition, the polarization rate DNBT > DNTO > DNAF based on the molecular orbital analysis and the electrostatic potential calculation implies that the excitation energy of DNBT is less than DNTO, and the excitation energy of DNTO is less than DNAF. This work is beneficial to the expansion of energetic materials into the optical field and the accelerated application process of the related industry.

Gas Adsorption in Zeolite and Thin Zeolite Layers: Molecular Simulation, Experiment, and Adsorption Potential Theory

Molecular simulations and experiments are used to investigate methane adsorption in bulk and thin layers of MFI zeolite (silicalite-1). After comparing the theoretical adsorption data obtained using Grand Canonical Monte Carlo simulations for bulk MFI at various temperatures against experiments, zeolite layers with different crystalline orientations and levels of surface flexibility are considered. The data obtained for such prototypical systems allow us to rationalize both the qualitative and quantitative impact of external surface in nanoporous solids. In particular, due to strong confinement in zeolite pores, methane is found to adsorb at low pressures in the core of the zeolite while external surface adsorption occurs at pressures where the internal porosity of zeolite is saturated. Using Polanyi's adsorption potential theory, which is derived here from Hill's general scheme for adsorption, we provide a simple thermodynamic formalism to predict consistently adsorption both in the internal porosity and at the external surface of nanoporous solids. While this seminal theory has been already applied for gases in nanoporous solids, its extension to describe both surface and volume adsorption is important to provide a general rational framework for fluid adsorption in finely divided materials. We also discuss the applicability of this formalism for gas adsorption data under supercritical conditions.

Molecular Dynamics Simulation of the Soret Effect on Two Binary Liquid Solutions with Equimolar n-Alkane Mixtures

Molecular dynamics is employed to simulate the Soret effect on two binary liquid solutions with equimolar mixtures: normal pentane (n-pentane, nC-5) and normal heptane (n-heptane, nC-7) molecules plus normal decane (n-decane, nC-10) and normal pentane molecules. Moreover, two coarse-grained force field (the CG-FF) potentials, which may depict inter-/intramolecular interactions fairly well among n-alkane molecules, are developed to fulfill such investigations. In addition, thermal diffusion for the mass fraction of each of these n-alkane molecules is simulated under an effect of a weak thermal gradient (temperature difference) exerting on solution systems from their hot to cold boundary sides. Finally, quantities of the Soret coefficient (SC) for two binary solutions are calculated by means of the developed CG-FF potentials, so as to improve the calculation rationality. As a result, first, it is found that molecules with light molar masses will migrate toward the hot boundary side, while those with heavy molar masses will migrate toward the cold boundary one ; second, the SC quantities indicate that they match relevant experimental determinations fairly well, i.e., trends of these SC quantities show inverse proportionality to the thermal gradient on the systems.

Shape selectivity effects in the hydroconversion of perhydrophenanthrene over bifunctional catalysts

The zeolite pore structure dictates the formation of isomers, which in turn influences the preferred ring opening products and the distribution of cracking products.

Interplay of the adsorption of light and heavy paraffins in hydroisomerization over H-beta zeolite

Hydroisomerization: controlling selectivity by tuning the Pt/zeolite properties.

Thermodynamic Properties of Vapor-Liquid Equilibria from Monte-Carlo Simulation using ab initio Intermolecular Potentials of Systems H2-H2 and F2-F2

In this work, we have been carried out GEMC-NVT simulations in the temperature range 18 K–32 K for fluid hydrogen and in range 60 K–140 K for fluid fluorine using four our developed ab initio 5-site intermolecular potentials for dimers H2-H2 and F2-F2, respectively. The thermodynamic properties of vapor-liquid equilibria and the critical points of fluids hydrogen and fluorine were calculated with the obtained densities of coexisting phases and vapor pressures. The simulation results drived from ab initio pair potentials were compared with those from ab initio potential plus three-body Axilrod-Teller potential and experimental data as well as those from Monte Carlo simulation using Lennard-Jones potentials, Deiters equation of state (D1-EOS) and Benedict-Webb-Rubin equation of state (EOS) reported in the literature.

Uncertainty quantification confirms unreliable extrapolation toward high pressures for united-atom Mie λ-6 force field

Molecular simulation results at extreme temperatures and pressures can supplement experimental data when developing fundamental equations of state. Since most force fields are optimized to agree with vapor-liquid equilibria (VLE) properties, however, the reliability of the molecular simulation results depends on the validity/transferability of the force field at higher temperatures and pressures. As demonstrated in this study, although state-of-the-art united-atom Mie λ-6 potentials for normal and branched alkanes provide accurate estimates for VLE, they tend to over-predict pressures for dense supercritical fluids and compressed liquids. The physical explanation for this observation is that the repulsive barrier is too steep for the "optimal" united-atom Mie λ-6 potential parameterized with VLE properties. Bayesian inference confirms that no feasible combination of non-bonded parameters (ϵ, σ, and λ) is capable of simultaneously predicting saturated vapor pressures, saturated liquid densities, and pressures at high temperatures and densities. This conclusion has both practical and theoretical ramifications, as more realistic non-bonded potentials may be required for accurate extrapolation to high pressures of industrial interest.

Thermodiffusion in multicomponent n-alkane mixtures

Compositional grading within a mixture has a strong impact on the evaluation of the pre-exploitation distribution of hydrocarbons in underground layers and sediments. Thermodiffusion, which leads to a partial diffusive separation of species in a mixture due to the geothermal gradient, is thought to play an important role in determining the distribution of species in a reservoir. However, despite recent progress, thermodiffusion is still difficult to measure and model in multicomponent mixtures. In this work, we report on experimental investigations of the thermodiffusion of multicomponent n-alkane mixtures at pressure above 30 MPa. The experiments have been conducted in space onboard the Shi Jian 10 spacecraft so as to isolate the studied phenomena from convection. For the two exploitable cells, containing a ternary liquid mixture and a condensate gas, measurements have shown that the lightest and heaviest species had a tendency to migrate, relatively to the rest of the species, to the hot and cold region, respectively. These trends have been confirmed by molecular dynamics simulations. The measured condensate gas data have been used to quantify the influence of thermodiffusion on the initial fluid distribution of an idealised one dimension reservoir. The results obtained indicate that thermodiffusion tends to noticeably counteract the influence of gravitational segregation on the vertical distribution of species, which could result in an unstable fluid column. This confirms that, in oil and gas reservoirs, the availability of thermodiffusion data for multicomponent mixtures is crucial for a correct evaluation of the initial state fluid distribution.

Calibration of forcefields for molecular simulation: sequential design of computer experiments for building cost-efficient kriging metamodels

We present a global strategy for molecular simulation forcefield optimization, using recent advances in Efficient Global Optimization algorithms. During the course of the optimization process, probabilistic kriging metamodels are used, that predict molecular simulation results for a given set of forcefield parameter values. This enables a thorough investigation of parameter space, and a global search for the minimum of a score function by properly integrating relevant uncertainty sources. Additional information about the forcefield parameters are obtained that are inaccessible with standard optimization strategies. In particular, uncertainty on the optimal forcefield parameters can be estimated, and transferred to simulation predictions. This global optimization strategy is benchmarked on the TIP4P water model.