eReaxFF: A Pseudoclassical Treatment of Explicit Electrons within Reactive Force Field Simulations

Inferring the existence of hydrogen bonds directly from statistical analysis of molecular dynamics trajectories

As a demonstration of how fundamental chemical concepts can be gleaned from data using machine learning methods, we demonstrate the automated detection of hydrogen bonds by statistical analysis of molecular dynamics trajectories. In particular, we infer the existence and nature of electrostatically driven noncovalent interactions by examining the relative probability of supramolecular configurations with and without electrostatic interactions. Then, using Laplacian eigenmaps clustering, we identify hydrogen bonding motifs in hydrogen fluoride, water, and methanol. The hydrogen bonding motifs that we identify support traditional geometric criteria.

Molecular Dynamics Simulations of Soft and Reactive Landing of Proteins Desorbed by Argon Cluster Bombardment

Reactive molecular dynamics (MD) simulations were conducted to investigate the soft and reactive landing of hyperthermal velocity proteins transferred to a vacuum using large argon clusters. Experimentally, the interaction of argon cluster ion beams (Ar1000-5000+) with a target biofilm was previously used in such a manner to transfer lysozymes onto a collector with the retention of their bioactivity, paving the way to a new solvent-free method for complex biosurface nanofabrication. However, the experiments did not give access to a microscopic view of the interactions needed for their full understanding, which can be provided by the MD model. Our reactive force field simulations clarify the landing mechanisms of the lysozymes and their fragments on collectors with different natures (gold- and hydrogen-terminated graphite). The results highlight the conditions of soft and reactive landing on rigid surfaces, the effects of the protein structure, energy, and incidence angle before landing, and the adhesion forces with the collector substrate. Many of the obtained results can be generalized to other soft and reactive landing approaches used for biomolecules such as electrospray ionization and matrix-assisted laser desorption ionization.

Unraveling the Molecular Dynamics of Glucose Oxidase Desorption Induced by Argon Cluster Collision

The bombardment of a protein multilayer target by an energetic argon cluster ion beam enables protein transfer onto a collector in the vacuum while preserving their bioactivity (iBEAM method). In parallel to this new soft-landing variant, protein transfer in the gas phase is a prerequisite for their characterization by mass spectrometry. The successful transfer of bioactive lysozymes (14 kDa) by cluster-induced soft landing and its mechanistic explanation by molecular dynamics (MD) simulations have sparked an important inquiry: Can heavier biomolecules be desorbed while maintaining their tridimensional structure and hence their bioactivity? To address this question, we employed MD simulations using a reactive force field (ReaxFF). Specifically, the Ar cluster-induced desorption of glucose oxidase from either a gold substrate or a lysozyme underlayer was modeled using the LAMMPS code. First, the force field parameters were trained by computing the dissociation energetics of a series of organic molecules with ReaxFF and DFT, in order to realistically describe N-S and O-S interactions in the bombarded glucose oxidase molecule. Second, bombardment simulations investigated the effects of cluster size (ranging from 1000 to 10000 Ar atoms) and kinetic energy (1.5 and 3.0 eV/atom) on the structural features and energetics of the desorbing glucose oxidase. Our results show that large argon clusters (≥7000) are needed to desorb glucose oxidase from a gold surface, yet protein fragmentation and/or pronounced denaturation occur. However, the transfer of structurally preserved glucose oxidase in the gas phase is predicted by the simulations when an organic layer is used as a substrate.

In silico characterization of nanoparticles

Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often require different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations.

Development of a Mg/O ReaxFF Potential to describe the Passivation Processes in Magnesium-Ion Batteries

One of the key challenges preventing the breakthrough of magnesium-ion batteries (MIB) is the formation of a passivating boundary layer at the Mg anode. To describe the initial steps of Mg anode degradation by O2 impurities, a Mg/O ReaxFF (force field for reactive systems) parameter set was developed capable of accurately modeling the bulk, surface, adsorption, and diffusion properties of metallic Mg and the salt MgO. It is shown that O2 immediately dissociates upon first contact with the Mg anode (modeled as Mg(0001), Mg(101 ‾ $\bar 1$ 0)A, and Mg(101 ‾ $\bar 1$ 1)), heating the surface to several 1000 K. The high temperature assists the further oxidation and forms a rock salt interphase intersected by several grain boundaries. Among the Mg surface terminations, Mg(101 ‾ $\bar 1$ 0)A is the most reactive, forming an MgO layer with a thickness of up to 25 Å. The trained force field can be used to model the ongoing reactions in Mg-air batteries but also to study the oxidation of magnesium metal in general.

Atomistic insight into the effects of electrostatic fields on hydrocarbon reaction kinetics

Reactive Molecular Dynamics (MD) and Density Functional Theory (DFT) computations are performed to provide insight into the effects of external electrostatic fields on hydrocarbon reaction kinetics. By comparing the results from MD and DFT, the suitability of the MD method in modeling electrodynamics is first assessed. Results show that the electric field-induced polarization predicted by the MD charge equilibration method is in good agreement with various DFT charge partitioning schemes. Then, the effects of oriented external electric fields on the transition pathways of non-redox reactions are investigated. Results on the minimum energy path suggest that electric fields can cause catalysis or inhibition of oxidation reactions, whereas pyrolysis reactions are not affected due to the weaker electronegativity of the hydrogen and carbon atoms. MD simulations of isolated reactions show that the reaction kinetics is also affected by applied external Lorentz forces and interatomic Coulomb forces since they can increase or decrease the energy of collision depending on the molecular conformation. In addition, electric fields can affect the kinetics of polar species and force them to align in the direction of field lines. These effects are attributed to energy transfer via intermolecular collisions and stabilization under the external Lorentz force. The kinetics of apolar species is not significantly affected mainly due to the weak induced dipole moment even under strong electric fields. The dynamics and reaction rates of species are studied by means of large-scale combustion simulations of n-dodecane and oxygen mixtures. Results show that under strong electric fields, the fuel, oxidizer, and most product molecules experience translational and rotational acceleration mainly due to close charge transfer along with a reduction in their vibrational energy due to stabilization. This study will serve as a basis to improve the current methods used in MD and to develop novel methodologies for the modeling of macroscale reacting flows under external electrostatic fields.

Plasma-Assisted Chemical-Looping Combustion: Low-Temperature Methane and Ethylene Oxidation with Nickel Oxide

The chemical reaction network of low-temperature plasma-assisted oxidation of methane (CH₄) and ethylene (C₂H₄) with nickel oxide (NiO) was investigated in a heated plasma reactor through time-dependent species measurements by electron-ionization molecular beam mass spectrometry (EI-MBMS). Methane (ethylene) oxidation by NiO was explored in temperature ranges from 300-700 °C (300-500 °C) and 300-800 °C (300-600 °C) for the plasma and nonplasma conditions. Significant enhancement of methane oxidation was observed with plasma between 400 and 500 °C, where no oxidation was observed under nonplasma conditions. For the oxidation of methane at higher temperatures, three different oxidation stages were observed: (I) a period of complete oxidation, (II) a period of incomplete CO oxidation, and (III) a period of carbon buildup. For the C₂H₄ experiments, and unlike the CH₄ experiments, the plasma resulted in a significant amount of new intermediate oxygenated species, such as CH₂O, CH₃OH, C₂H₄O, and C₂H₆O. Carbon deposits were observed under both methane and ethylene conditions and verified by X-ray photoelectron spectroscopy (XPS). ReaxFF (reactive force field) simulations were performed for the oxidation of CH₄ and C₂H₄ in a nonplasma environment. The simulated intermediates and products largely agree with the species measured in the experiments, though the predicted intermediate oxygenated species such as CH₂O and C₂H₆O were not observed in experiments under nonplasma conditions. A reaction pathway analysis for CH₄ and C₂H₄ reacting with NiO was created based on the observed species from the MBMS spectra along with ReaxFF simulations.

A Reactive Molecular Dynamics Study of Chlorinated Organic Compounds. Part I: Force Field Development

This work presents a novel parametrization for the ReaxFF formalism as a means to investigate reaction processes of chlorinated organic compounds. Force field parameters cover the chemical elements C, H, O, Cl and were obtained using a novel optimization approach involving relaxed potential energy surface scans as training targets. The resulting ReaxFF parametrization shows good transferability, as demonstrated on two independent ab initio validation sets. While this first part of our two-paper series focuses on force field parametrization, we apply our parameters to the simulation of chlorinated dibenzofuran formation and decomposition processes in Part II.

A new framework for frequency-dependent polarizable force fields

A frequency-dependent extension of the polarizable force field "Atom-Condensed Kohn-Sham density functional theory approximated to the second-order" (ACKS2) [Verstraelen et al., J. Chem. Phys. 141, 194114 (2014)] is proposed, referred to as ACKS2ω. The method enables theoretical predictions of dynamical response properties of finite systems after partitioning of the frequency-dependent molecular response function. Parameters in this model are computed simply as expectation values of an electronic wavefunction, and the hardness matrix is entirely reused from ACKS2 as an adiabatic approximation is used. A numerical validation shows that accurate models can already be obtained with atomic monopoles and dipoles. Absorption spectra of 42 organic and inorganic molecular monomers are evaluated using ACKS2ω, and our results agree well with the time-dependent DFT calculations. Also for the calculation of C₆ dispersion coefficients, ACKS2ω closely reproduces its TDDFT reference. When parameters for ACKS2ω are derived from a PBE/aug-cc-pVDZ ground state, it reproduces experimental values for 903 organic and inorganic intermolecular pairs with an MAPE of 3.84%. Our results confirm that ACKS2ω offers a solid connection between the quantum-mechanical description of frequency-dependent response and computationally efficient force-field models.

Sensitivity Analysis of ReaxFF Potential: The Case of Si/O System

Sensitivity analysis of the ReaxFF potential for two Si and SiO₂ systems has been carried out using the method of Morris. The goal is to identify the most important force field parameters for selected properties. Thus, a clearer physical interpretation for some of the parameters can be obtained while the ranking of the parameters per magnitude of sensitivity for each property facilitates the development of parametrizations with improved quality. The parameters related to the σ-bond and van der Waals interactions have the greatest influence on the properties of the cubic diamond Si phase. Counterintuitively, parameters which have an impact on mechanical properties, such as the ones for ππ-bonds, do not influence pressure and vice versa. For the β-cristobalite SiO₂ phase, the Si-O cross-interaction parameters have stronger effect on all properties than the Si-Si and O-O elemental ones. This dependence is attributed to the tetrahedral structure of the SiO₂ phase. Regarding the sensitivity measures, the mean of the absolute values of the elementary effect (EE) distribution correlates with the standard deviation of the EE distribution in all cases; it quantifies the sensitivity of a property on a parameter and the cross-correlation of the parameter with the other ones. The mean of the EE distribution has a poor performance and its use should be avoided. It is also argued that performing a sensitivity analysis before force field optimization might greatly enhance the efficiency of the optimization methods by considering a two-step procedure, where the most relevant parameters are optimized first.

High-Dimensional Neural Network Potential for Liquid Electrolyte Simulations

Liquid electrolytes are one of the most important components of Li-ion batteries, which are a critical technology of the modern world. However, we still lack the computational tools required to accurately calculate key properties of these materials (viscosity and ionic diffusivity) from first principles necessary to support improved designs. In this work, we report a machine learning-based force field for liquid electrolyte simulations, which bridges the gap between the accuracy of range-separated hybrid density functional theory and the efficiency of classical force fields. Predictions of material properties made with this force field are quantitatively accurate compared to experimental data. Our model uses the QRNN deep neural network architecture, which includes both long-range interactions and global charge equilibration. The training data set is composed solely of non-periodic density functional theory (DFT), allowing the practical use of an accurate theory (here, ωB97X-D3BJ/def2-TZVPD), which would be prohibitively expensive for generating large data sets with periodic DFT. In this report, we focus on seven common carbonates and LiPF₆, but this methodology has very few assumptions and can be readily applied to any liquid electrolyte system. This provides a promising path forward for large-scale atomistic modeling of many important battery chemistries.

DFT-ReaxFF hybrid molecular dynamics investigation of the decomposition effects of localized high-concentration electrolyte in lithium metal batteries: LiFSI/DME/TFEO

Due to its low electrochemical potential and high theoretical specific energy, lithium-metal batteries (LMBs) have been considered as a promising advanced energy storage system for portable applications such as electric vehicles (EVs). However, the uncontrolled growth of lithium dendrites during cycling has remained a challenge. By utilizing an inert solvent to "dilute" the high concentration electrolytes, the concept of localized high-concentration electrolytes (LHCEs) has recently been demostrated as an effective solution to enable the dendrite-free cycling of LMBs. In this work, we investigated the reactions of 2 M lithium bis(fluorosulfonyl)imide (LiFSI) in a mixture of dimethoxyethane (DME)/tris(2,2,2-trifluoroethyl) orthoformate (TFEO) electrolyte at a Li metal anode. The SEI formation mechanism is investigated using a hybrid ab initio and reactive force field (HAIR) method. The 1n reactive HAIR trajectory reveals the important initial reduction reactions of LiFSI, TFEO, and DME. Particularly, both FSI anions and TFEO decompose quickly to release a considerable amount of F^-, which leads to a LiF-rich SEI inorganic inner layer (IIL). Furthermore, TFEO produces a significant amount of unsaturated carbon products, such as thiophene, which can potentially increase the conductivity of SEI to increase the battery performance. Meanwhile, XPS analysis is utilized to further investigate the evolution of the atomic environment in SEI. Future designs of better electrolytes can be greatly aided by these results.

Valence energy correction for electron reactive force field

Reactive force fields (ReaxFF) are a classical method to describe material properties based on a bond-order formalism, that allows bond dissociation and consequently investigations of reactive systems. Semiclassical treatment of electrons was introduced within ReaxFF simulations, better known as electron reactive force fields (eReaxFF), to explicitly treat electrons as spherical Gaussian waves. In the original version of eReaxFF, the electrons and electron-holes can lead to changes in both the bond energy and the Coulomb energy of the system. In the present study, the method was modified to allow an electron to modify the valence energy, therefore, permitting that the electron's presence modifies the three-body interactions, affecting the angle among three atoms. When a reaction path involving electron transfer is more sensitive to the geometric configuration of the molecules, corrections in the angular structure in the presence of electrons become more relevant; in this case, bond dissociation may not be enough to describe a reaction path. Consequently, the application of the extended eReaxFF method developed in this work should provide an improved description of a reaction path. As a first demonstration this semiclassical force field was parametrized for hydrogen and oxygen interactions, including water and water's ions. With the modified methodology both the overall accuracy of the force field but also the description of the angles within the molecules in presence of electrons could be improved.

Modeling Electronic Response Properties with an Explicit-Electron Machine Learning Potential

Explicit-electron force fields introduce electrons or electron pairs as semiclassical particles in force fields or empirical potentials, which are suitable for molecular dynamics simulations. Even though semiclassical electrons are a drastic simplification compared to a quantum-mechanical electronic wave function, they still retain a relatively detailed electronic model compared to conventional polarizable and reactive force fields. The ability of explicit-electron models to describe chemical reactions and electronic response properties has already been demonstrated, yet the description of short-range interactions for a broad range of chemical systems remains challenging. In this work, we present the electron machine learning potential (eMLP), a new explicit electron force field in which the short-range interactions are modeled with machine learning. The electron pair particles will be located at well-defined positions, derived from localized molecular orbitals or Wannier centers, naturally imposing the correct dielectric and piezoelectric behavior of the system. The eMLP is benchmarked on two newly constructed data sets: eQM7, an extension of the QM7 data set for small molecules, and a data set for the crystalline β-glycine. It is shown that the eMLP can predict dipole moments, polarizabilities, and IR-spectra of unseen molecules with high precision. Furthermore, a variety of response properties, for example, stiffness or piezoelectric constants, can be accurately reproduced.

Water in an External Electric Field: Comparing Charge Distribution Methods Using ReaxFF Simulations

The growing interest in the effects of external electric fields on reactive processes requires predictive methods that can reach longer length and time scales than quantum mechanical simulations. Recently, many studies have included electric fields in ReaxFF, a widely used reactive molecular dynamics method. In the case of modeling an external electric field, the charge distribution method used in ReaxFF is critical. The most common charge distribution method used in previous studies of electric fields is the charge equilibration (QEq) method, which assumes that the system is a contiguous conductor and that charge transfer can occur across any distance. In contrast, many systems of interest are insulators or semiconductors, and long-distance charge transfer should not occur in response to a small difference in potential. This study focuses on the limitations of the QEq method in the context of water in an external electric field. We demonstrate that QEq can predict unphysical charge distributions and exhibits properties that do not converge as a function of system size. Furthermore, we show that electric fields within the recently developed atom-condensed Kohn-Sham density functional theory (DFT) approximated to the second-order (ACKS2) approach address the major limitations of electric fields in QEq. With ACKS2, we observe more physical charge distributions and properties that converge as a function of system size. We do not suggest that ACKS2 is perfect in all circumstances but rather show specific cases where it addresses the major shortcomings of QEq in the context of an external electric field.

Using C-DFT to develop an e-ReaxFF force field for acetophenone radical anion

Increased electricity usage over the past several decades has accelerated the need for efficient high-voltage power transmission with reliable insulating materials. Cross-linked polyethylene (XLPE) prepared via dicumyl peroxide (DCP) cross-linking has emerged as the insulator of choice for modern power cables. Although DCP cross-linking generates the desired XLPE product in high yield, other by-products are also produced. One such by-product, acetophenone, is particularly intriguing due to its aromaticity and positive electron affinity. In this work, constrained density functional theory (C-DFT) was utilized to develop an e-ReaxFF force field suitable for describing the acetophenone radical anion. Initial parameters were taken from the 2021 Akbarian e-ReaxFF force field, which was developed to describe XLPE chemistry. Then, C-DFT geometry optimizations were performed wherein an excess electron was constrained to each atom of acetophenone. The resulting C-DFT energy values for the various electronic positions were added to the e-ReaxFF training set. Next, an analogous set of structures was energy-minimized using e-ReaxFF, and equilibrium mixture compositions for the two methods were compared at multiple temperatures. Iterative fitting against C-DFT energy data was performed until satisfactory agreement was achieved. To test force field performance, molecular dynamics simulations were performed in e-ReaxFF and the resulting electronic distributions were qualitatively compared to unconstrained-DFT spin density data. By expanding our e-ReaxFF force field for XLPE, namely, adding the capability to describe acetophenone and its interactions with an excess electron, we move one step closer to a comprehensive molecular understanding of XLPE chemistry in a high-voltage power cable.

Understanding physical chemistry of BaxSr1-xTiO3 using ReaxFF molecular dynamics simulations

Barium strontium titanate Ba_xSr_1-xTiO₃ (BSTO) has been widely used in nano devices due to its unique ferroelectric properties and can be epitaxially grown on a SrTiO₃ (STO) support, with a reduced lattice and thermal mismatch. In this work, we developed a ReaxFF reactive force field verified against quantum mechanical data to investigate the temperature and composition dependency of BSTO in non-ferroelectric/ferroelectric phases. This potential was also explicitly designed to capture the surface energetics of STO with SrO and TiO₂ terminations. Our molecular dynamics simulations indicate that when the percentage of Sr increases, the phase transition temperature and the polarizations of the Ba_xSr_1-xTiO₃ system decrease monotonically. In addition, as the oxygen vacancy concentration enhances, the initial polarization and the phase transition temperature of the system drop significantly. Furthermore, our simulation results show that charge screening induced by adsorption of water molecules on TiO₂ terminated surfaces leads to an increased initial polarization.

Generalized Method for Charge-Transfer Equilibration in Reactive Molecular Dynamics

Variable charge models (e.g., electronegativity equalization method (EEM), charge equilibration (QEq), electrostatic plus (ES+)) used in reactive molecular dynamics simulations often inherently impose a global charge transfer between atoms (approximating each system as an ideal metal). Consequently, most surface processes (e.g., adsorption, desorption, deposition, sputtering) are affected, potentially causing dubious dynamics. This issue has been addressed by certain split charge variants (i.e., split charge equilibration (SQE), redoxSQE) through a distance-dependent bond hardness, by the atomic charge ACKS2 and QTPIE models, which are based on the Kohn-Sham density functional theory, as well as by an electronegativity screening extension to the QEq model (approximating each system as an ideal insulator). In a brief review of the QEq and the QTPIE model, their applicability for studying surface interactions is assessed in this work. Following this evaluation, a revised generalization of the QEq and QTPIE models is proposed and formulated, called the charge-transfer equilibration model or in short the QTE model. This method is based on the equilibration of charge-transfer variables, which locally constrain the split charge transfer per unit time (i.e., due to overlapping orbitals) without any kind of bond hardness specification. Furthermore, a formalism relying solely on atomic charges is obtained by a respective transformation, employing an extended Lagrangian method. We moreover propose a mirror boundary condition and its implementation to accelerate surface investigations. The models proposed in this work facilitate reactive molecular dynamics simulations, which describe various materials and surface phenomena appropriately.

A Review of Recent Developments in Molecular Dynamics Simulations of the Photoelectrochemical Water Splitting Process

In this review, we provide a short overview of the Molecular Dynamics (MD) method and how it can be used to model the water splitting process in photoelectrochemical hydrogen production. We cover classical non-reactive and reactive MD techniques as well as multiscale extensions combining classical MD with quantum chemical and continuum methods. Selected examples of MD investigations of various aqueous semiconductor interfaces with a special focus on TiO2 are discussed. Finally, we identify gaps in the current state-of-the-art where further developments will be needed for better utilization of MD techniques in the field of water splitting.

Recent Advances for Improving the Accuracy, Transferability, and Efficiency of Reactive Force Fields

Reactive force fields provide an affordable model for simulating chemical reactions at a fraction of the cost of quantum mechanical approaches. However, classically accounting for chemical reactivity often comes at the expense of accuracy and transferability, while computational cost is still large relative to nonreactive force fields. In this Perspective, we summarize recent efforts for improving the performance of reactive force fields in these three areas with a focus on the ReaxFF theoretical model. To improve accuracy, we describe recent reformulations of charge equilibration schemes to overcome unphysical long-range charge transfer, new ReaxFF models that account for explicit electrons, and corrections for energy conservation issues of the ReaxFF model. To enhance transferability we also highlight new advances to include explicit treatment of electrons in the ReaxFF and hybrid nonreactive/reactive simulations that make it possible to model charge transfer, redox chemistry, and large systems such as reverse micelles within the framework of a reactive force field. To address the computational cost, we review recent work in extended Lagrangian schemes and matrix preconditioners for accelerating the charge equilibration method component of ReaxFF and improvements in its software performance in LAMMPS.

Effects of High and Low Salt Concentrations in Electrolytes at Lithium-Metal Anode Surfaces Using DFT-ReaxFF Hybrid Molecular Dynamics Method

Due to creating a passivated solid electrolyte interphase (SEI), high concentration (HC) electrolytes demonstrate peculiar physicochemical properties and outstanding electrochemical performance. However, the structures of such SEI remains far from clear. In this work, a hybrid ab initio and reactive molecular dynamics (HAIR) scheme is employed to investigate the concentration effect of SEI formation by simulating the reductive degradation reactions of lithium bis(fluorosulfonyl)imide (LiFSI) in 1,3 dioxalane (DOL) electrolytes at concentrations of 1 M, 4 M, and 10 M. The efficient HAIR scheme allows the simulations to reach 1 ns to predict electrolytes' deep products at different concentrations. The simulation findings show that the most critical distinction between HC and its low concentration (LC) analogue is that anion decomposition in HC is much more incomplete when only S-F breaking is observed. These insights are important for the future development of advanced electrolytes by rational design of electrolytes.

Atomistic-Scale Simulations on Graphene Bending Near a Copper Surface

Molecular insights into graphene-catalyst surface interactions can provide useful information for the efficient design of copper current collectors with graphitic anode interfaces. As graphene bending can affect the local electron density, it should reflect its local reactivity as well. Using ReaxFF reactive molecular simulations, we have investigated the possible bending of graphene in vacuum and near copper surfaces. We describe the energy cost for graphene bending and the binding energy with hydrogen and copper with two different ReaxFF parameter sets, demonstrating the relevance of using the more recently developed ReaxFF parameter sets for graphene properties. Moreover, the draping angle at copper step edges obtained from our atomistic simulations is in good agreement with the draping angle determined from experimental measurements, thus validating the ReaxFF results.

The DFT-ReaxFF Hybrid Reactive Dynamics Method with Application to the Reductive Decomposition Reaction of the TFSI and DOL Electrolyte at a Lithium-Metal Anode Surface

The high energy density and suitable operating voltage make rechargeable lithium ion batteries (LIBs) promising candidates to replace such conventional energy storage devices as nonrechargeable batteries. However, the large-scale commercialization of LIBs is impeded significantly by the degradation of the electrolyte, which reacts with the highly reactive lithium metal anode. Future improvement of the battery performance requires a knowledge of the reaction mechanism that is responsible for the degradation and formation of the solid-electrolyte interphase (SEI). In this work, we develop a hybrid computational scheme, Hybrid ab initio molecular dynamics combined with reactive force fields, denoted HAIR, to accelerate Quantum Mechanics-based reaction dynamics (QM-MD or AIMD, for ab initio RD) simulations. The HAIR scheme extends the time scale accessible to AIMD by a factor of 10 times through interspersing reactive force field (ReaxFF) simulations between the AIMD parts. This enables simulations of the initial chemical reactions of SEI formation, which may take 1 ns, far too long for AIMD. We apply the HAIR method to the bis(trifluoromethanesulfonyl)imide (TFSI) electrolyte in 1,3-dioxolane (DOL) solvent at the Li metal electrode, demonstrating that HAIR reproduces the initial reactions of the electrolyte (decomposition of TFSI) previously observed in AIMD simulation while also capturing solvent reactions (DOL) that initiate by ring-opening to form such stable products as CO, CH₂O, and C₂H₄, as observed experimentally. These results demonstrate that the HAIR scheme can significantly increase the time scale for reactive MD simulations while retaining the accuracy of AIMD simulations. This enables a full atomistic description of the formation and evolution of SEI.

Atomistic-scale insight into the polyethylene electrical breakdown: An eReaxFF molecular dynamics study

Cross-linked polyethylene (XLPE) has been recognized as an outstanding insulator for high-voltage power cables due to its favorable structural integrity at high temperature, low moisture sensitivity, chemical resistance, and low rates of failure due to aging. However, the roles of by-products and amorphous regions generated during the XLPE production are not clearly known at the atomistic scale. In this study, we present an eReaxFF-based molecular dynamics simulation framework with an explicit electron description verified against density functional theory data to investigate the roles of XLPE by-products and processing variables such as density and voids on the time to dielectric breakdown (TDDB) of polyethylene (PE). Our simulation results indicate that an increase in density of PE increases the TDDB; however, adding a by-product with positive electron affinity such as acetophenone can reduce the TDDB. Furthermore, during the electrical breakdown in PE, electrons tend to migrate through voids when transferring from the anode to cathode. In comparison with neutral acetophenone, we find that the acetophenone radical anion can significantly reduce the energy barrier and the reaction energy of secondary chemical reactions.

A Reactive Force Field with Coarse-Grained Electrons for Liquid Water

Nonreactive force fields are defined by perturbations of electron density that are relatively small, whereas chemical reactivity involves wholesale electronic rearrangements that make and break bonds. Thus, reactive force fields are incredibly difficult to develop compared to nonreactive force fields, yet at the same time, they fill a critical need when ab initio molecular dynamics methods are not affordable. We introduce a new reactive force field model for water that combines modified nonbonded terms of the ReaxFF model and its embedding in the electrostatic interactions described by our recently introduced coarse-grained electron model (C-GeM). The ReaxFF/C-GeM force field is characterized for many energetic and dissociative water properties for water clusters, structure, and dynamical properties under ambient conditions in the condensed phase, as well as the temperature dependence of density and water diffusion, with very good agreement with experiment. The ReaxFF/C-GeM force field should be more transferable and more broadly applicable to a range of reactive systems involving both proton and electron transfer in the condensed phase.

Reactive Molecular Dynamics at Constant Pressure via Nonreactive Force Fields: Extending the Empirical Valence Bond Method to the Isothermal-Isobaric Ensemble

The Empirical Valence Bond (EVB) method offers a suitable framework to obtain reactive potentials through the coupling of nonreactive force fields. In this formalism, most of the implemented coupling terms are built using functional forms that depend on spatial coordinates, while parameters are fitted against reference data to model the change of chemistry between the participating nonreactive states. In this work, we demonstrate that the use of such coupling terms precludes the computation of the stress tensor for condensed phase systems and prevents the possibility to carry out EVB molecular dynamics in the isothermal-isobaric (NPT) ensemble. Alternatively, we make use of coupling terms that depend on the energy gaps, defined as the energy differences between the participating nonreactive force fields, and derive a general expression for the EVB stress tensor suitable for computation. Implementation of this new methodology is tested for a model of a single reactive malonaldehyde solvated in nonreactive water. Mass densities and probability distributions for the values of the energy gaps computed in the NPT ensemble reveal a negligible role of the reactive potential in the limit of low concentrated solutions, thus corroborating for the first time the validity of approximations based on the canonical NVT ensemble, customarily adopted for EVB simulations. The presented formalism also aims to contribute to future implementations and extensions of the EVB method to research the limit of highly concentrated solutions.

C-GeM: Coarse-Grained Electron Model for Predicting the Electrostatic Potential in Molecules

We have developed a new coarse-grained electron model, C-GeM, in which atoms are represented by a positive core and an electron shell described by Gaussian charge distributions, with the interaction energy between the core and shell reflecting the electronegativity of a given atomic element. By minimizing the electronic shell positions in the field of atomic core positions, the model can provide accurate electrostatic properties of molecules and their interactions. We have tested the performance of the C-GeM model for a set of molecules containing H, C, O, and Cl atoms to show that it can predict the electrostatic potential with high accuracy, and correctly describe the dissociation of HCl into ionic fragments in solution and to neutral atoms in the gas phase. The resulting C-GeM approach offers many advantages over expensive ab initio methods and reactive force field charge equilibration methodologies: it can rapidly predict the electrostatic potential surfaces of molecules, molecules dissociate into integer charge fragments so that redox reactions are easily described, there is no unphysical long-range charge transfer, it can account for out-of-plane polarization, and charges are not required to be centered on atoms, thereby accounting for electrostatic features such as sigma holes.

Toward First-Principles-Level Polarization Energies in Force Fields: A Gaussian Basis for the Atom-Condensed Kohn-Sham Method

The last 20 years of force field development have shown that even well parametrized classical models need to at least approximate the dielectric response of molecular systems-based, e.g., on atomic polarizabilities-in order to correctly render their structural and dynamic properties. Yet, despite great advances most approaches tend to be based on ad hoc assumptions and often insufficiently capture the dielectric response of the system to external perturbations, such as, e.g., charge carriers in semiconducting materials. A possible remedy was recently introduced with the atom-condensed Kohn-Sham density-functional theory approximated to second order (ACKS2), which is fully derived from first principles. Unfortunately, specifically its reliance on first-principles derived parameters so far precluded the widespread adoption of ACKS2. Opening up ACKS2 for general use, we here present a reformulation of the method in terms of Gaussian basis functions, which allows us to determine many of the ACKS2 parameters analytically. Two sets of parameters depending on exchange-correlation interactions are still calculated numerically, but we show that they could be straightforwardly parametrized owing to the smoothness of the new basis. Our approach exhibits three crucial benefits for future applications in force fields: i) efficiency, ii) accuracy, and iii) transferability. We numerically validate our Gaussian augmented ACKS2 model for a set of small hydrocarbons which shows a very good agreement with density-functional theory reference calculations. To further demonstrate the method's accuracy and transferability for realistic systems, we calculate polarization responses and energies of anthracene and tetracene, two major building blocks in organic semiconductors.

Thermal Boundary Characteristics of Homo-/Heterogeneous Interfaces

The interface of two solids in contact introduces a thermal boundary resistance (TBR), which is challenging to measure from experiments. Besides, if the interface is reactive, it can form an intermediate recrystallized or amorphous region, and extra influencing phenomena are introduced. Reactive force field Molecular Dynamics (ReaxFF MD) is used to study these interfacial phenomena at the (non-)reactive interface. The non-reactive interfaces are compared using a phenomenological theory (PT), predicting the temperature discontinuity at the interface. By connecting ReaxFF MD and PT we confirm a continuous temperature profile for the homogeneous non-reactive interface and a temperature jump in case of the heterogeneous non-reactive interface. ReaxFF MD is further used to understand the effect of chemical activity of two solids in contact. The selected Si/SiO 2 materials showed that the TBR of the reacted interface is two times larger than the non-reactive, going from 1 . 65 × 10 - 9 to 3 . 38 × 10 - 9 m 2 K/W. This is linked to the formation of an intermediate amorphous layer induced by heating, which remains stable when the system is cooled again. This provides the possibility to design multi-layered structures with a desired TBR.

Boosting Rechargeable Batteries R&D by Multiscale Modeling: Myth or Reality?

This review addresses concepts, approaches, tools, and outcomes of multiscale modeling used to design and optimize the current and next generation rechargeable battery cells. Different kinds of multiscale models are discussed and demystified with a particular emphasis on methodological aspects. The outcome is compared both to results of other modeling strategies as well as to the vast pool of experimental data available. Finally, the main challenges remaining and future developments are discussed.

Mechanisms of Iodide⁻Triiodide Exchange Reactions in Ionic Liquids: A Reactive Molecular-Dynamics Exploration

Efficient charge transport has been observed in iodine-doped, iodide-based room-temperature ionic liquids, yielding high ionic conductivity. To elucidate preferred mechanistic pathways for the iodide ( I - )-to-triiodide ( I 3 - ) exchange reactions, we have performed 10 ns reactive molecular-dynamics calculations in the liquid state for 1-butyl-3-methylimidazolium iodide ([BMIM][I]) at 450 to 750 K. Energy-barrier distributions for the iodine-swapping process were determined as a function of temperature, employing a charge-reassignment scheme drawn in part from electronic-structure calculations. Bond-exchange events were observed with rate-determining energy barriers ranging from ~0.19 to 0.23 ± 0.06 eV at 750 and 450 K, respectively, with an approximately Arrhenius temperature dependence for iodine self-diffusivity and reaction kinetics, although diffusion dominates/limits the bond-exchange events. This charge transfer is not dissimilar in energetics to those in solid-state superionic conductors.

Development of a Charge-Implicit ReaxFF Potential for Hydrocarbon Systems

Molecular dynamics (MD) simulations continue to make important contributions to understanding chemical and physical processes. Concomitant with the growth of MD simulations is the need to have interaction potentials that both represent the chemistry of the system and are computationally efficient. We propose a modification to the ReaxFF potential for carbon and hydrogen that eliminates the time-consuming charge equilibration, eliminates the acknowledged flaws of the electronegativity equalization method, includes an expanded training set for condensed phases, has a repulsive wall for simulations of energetic particle bombardment, and is compatible with the LAMMPS code. This charge-implicit ReaxFF potential is five times faster than the conventional ReaxFF potential for a simulation of keV particle bombardment with a sample size of over 800 000 atoms.

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. The 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.

Simulation Protocol for Prediction of a Solid-Electrolyte Interphase on the Silicon-based Anodes of a Lithium-Ion Battery: ReaxFF Reactive Force Field

We propose the ReaxFF reactive force field as a simulation protocol for predicting the evolution of solid-electrolyte interphase (SEI) components such as gases (C₂H₄, CO, CO₂, CH₄, and C₂H₆), and inorganic (Li₂CO₃, Li₂O, and LiF) and organic (ROLi and ROCO₂Li: R = -CH₃ or -C₂H₅) products that are generated by the chemical reactions between the anodes and liquid electrolytes. ReaxFF was developed from ab initio results, and a molecular dynamics simulation with ReaxFF realized the prediction of SEI formation under real experimental conditions and with a reasonable computational cost. We report the effects on SEI formation of different kinds of Si anodes (pristine Si and SiO_x), of the different types and compositions of various carbonate electrolytes, and of the additives. From the results, we expect that ReaxFF will be very useful for the development of novel electrolytes or additives and for further advances in Li-ion battery technology.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.