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

Enhancing ReaxFF for molecular dynamics simulations of lithium-ion batteries: an interactive reparameterization protocol

Lithium-ion batteries (LIBs) have become an essential technology for the green economy transition, as they are widely used in portable electronics, electric vehicles, and renewable energy systems. The solid-electrolyte interphase (SEI) is a key component for the correct operation, performance, and safety of LIBs. The SEI arises from the initial thermal metastability of the anode-electrolyte interface, and the resulting electrolyte reduction products stabilize the interface by forming an electrochemical buffer window. This article aims to make a first-but important-step towards enhancing the parametrization of a widely-used reactive force field (ReaxFF) for accurate molecular dynamics (MD) simulations of SEI components in LIBs. To this end, we focus on Lithium Fluoride (LiF), an inorganic salt of great interest due to its beneficial properties in the passivation layer. The protocol relies heavily on various Python libraries designed to work with atomistic simulations allowing robust automation of all the reparameterization steps. The proposed set of configurations, and the resulting dataset, allow the new ReaxFF to recover the solid nature of the inorganic salt and improve the mass transport properties prediction from MD simulation. The optimized ReaxFF surpasses the previously available force field by accurately adjusting the diffusivity of lithium in the solid lattice, resulting in a two-order-of-magnitude improvement in its prediction at room temperature. However, our comprehensive investigation of the simulation shows the strong sensitivity of the ReaxFF to the training set, making its ability to interpolate the potential energy surface challenging. Consequently, the current formulation of ReaxFF can be effectively employed to model specific and well-defined phenomena by utilizing the proposed interactive reparameterization protocol to construct the dataset. Overall, this work represents a significant initial step towards refining ReaxFF for precise reactive MD simulations, shedding light on the challenges and limitations of ReaxFF force field parametrization. The demonstrated limitations emphasize the potential for developing more versatile and advanced force fields to upscale ab initio simulation through our interactive reparameterization protocol, enabling more accurate and comprehensive MD simulations in the future.

Accurate Quantum Chemical Reaction Energies for Lithium-Mediated Electrolyte Decomposition and Evaluation of Density Functional Approximations

An important concern related to the performance of Li-ion batteries is the formation of a solid electrolyte interphase on the surface of the anode. This film is formed from the decomposition of electrolytes and can have important effects on the stability and performance. Here, we evaluate the decomposition pathway of ethylene carbonate and related organic electrolyte molecules using a series of density functional approximations and correlated wave function (WF) methods, including the coupled-cluster theory with single, double, and perturbative triple excitations [CCSD(T)] and auxiliary-field quantum Monte Carlo (AFQMC). We find that the transition state barrier associated with ring opening varies widely across different functionals, ranging from 3.01 to 17.15 kcal/mol, which can be compared to the value of 12.84 kcal/mol predicted by CCSD(T). This large variation underscores the importance of benchmarking against accurate WF methods. A performance comparison of all of the density functionals used in this study reveals that the M06-2X-D3 (a meta-hybrid GGA), CAM-B3LYP-D3 (a range-separated hybrid), and B2GP-PLYP-D3 (a double hybrid) perform the best, with average errors of about 1.50-1.60 kcal/mol compared to CCSD(T). We also compared the performance of the WF methods that are more scalable than CCSD(T), finding that DLPNO-CCSD(T) and phaseless AFQMC with a DFT trial wave function exhibit average errors of 1.38 and 1.74 kcal/mol, respectively.

Controlling Gas Generation of Li-Ion Battery through Divinyl Sulfone Electrolyte Additive

The focus of mainstream lithium-ion battery (LIB) research is on increasing the battery’s capacity and performance; however, more effort should be invested in LIB safety for widespread use. One aspect of major concern for LIB cells is the gas generation phenomenon. Following conventional battery engineering practices with electrolyte additives, we examined the potential usage of electrolyte additives to address this specific issue and found a feasible candidate in divinyl sulfone (DVSF). We manufactured four identical battery cells and employed an electrolyte mixture with four different DVSF concentrations (0%, 0.5%, 1.0%, and 2.0%). By measuring the generated gas volume from each battery cell, we demonstrated the potential of DVSF additives as an effective approach for reducing the gas generation in LIB cells. We found that a DVSF concentration of only 1% was necessary to reduce the gas generation by approximately 50% while simultaneously experiencing a negligible impact on the cycle life. To better understand this effect on a molecular level, we examined possible electrochemical reactions through ab initio molecular dynamics (AIMD) based on the density functional theory (DFT). From the electrolyte mixture’s exposure to either an electrochemically reductive or an oxidative environment, we determined the reaction pathways for the generation of CO₂ gas and the mechanism by which DVSF additives effectively blocked the gas’s generation. The key reaction was merging DVSF with cyclic carbonates, such as FEC. Therefore, we concluded that DVSF additives could offer a relatively simplistic and effective approach for controlling the gas generation in lithium-ion batteries.

Applying Classical, Ab Initio, and Machine-Learning Molecular Dynamics Simulations to the Liquid Electrolyte for Rechargeable Batteries

Rechargeable batteries have become indispensable implements in our daily life and are considered a promising technology to construct sustainable energy systems in the future. The liquid electrolyte is one of the most important parts of a battery and is extremely critical in stabilizing the electrode-electrolyte interfaces and constructing safe and long-life-span batteries. Tremendous efforts have been devoted to developing new electrolyte solvents, salts, additives, and recipes, where molecular dynamics (MD) simulations play an increasingly important role in exploring electrolyte structures, physicochemical properties such as ionic conductivity, and interfacial reaction mechanisms. This review affords an overview of applying MD simulations in the study of liquid electrolytes for rechargeable batteries. First, the fundamentals and recent theoretical progress in three-class MD simulations are summarized, including classical, ab initio, and machine-learning MD simulations (section 2). Next, the application of MD simulations to the exploration of liquid electrolytes, including probing bulk and interfacial structures (section 3), deriving macroscopic properties such as ionic conductivity and dielectric constant of electrolytes (section 4), and revealing the electrode-electrolyte interfacial reaction mechanisms (section 5), are sequentially presented. Finally, a general conclusion and an insightful perspective on current challenges and future directions in applying MD simulations to liquid electrolytes are provided. Machine-learning technologies are highlighted to figure out these challenging issues facing MD simulations and electrolyte research and promote the rational design of advanced electrolytes for next-generation rechargeable batteries.

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.

Atomistic Insights into H2O2 Direct Synthesis of Ni-Pt Nanoparticle Catalysts under Water Solvents by Reactive Molecular Dynamics Simulations

In computational catalysis, density-functional theory (DFT) calculations are usually utilized, although they suffer from high computational costs. Thus, it would be challenging to explicitly predict the catalytic properties of nanoparticles (NPs) at the nanoscale under solvents. Using molecular dynamics (MD) simulations with a reactive force field (ReaxFF), we investigated the catalytic performance of Ni-Pt NPs for the direct synthesis of hydrogen peroxide (H₂O₂), in which water solvents were explicitly considered along with the effects of the sizes (1.5, 2.0, 3.0, and 3.5 nm) and compositions (Ni₉₀Pt₁₀, Ni₈₀Pt₂₀, and Ni₅₀Pt₅₀) of the NPs. Among the Ni-Pt NPs, 3.0 nm NPs show the highest activity and selectivity for the direct synthesis of H₂O₂, revealing that the catalytic performance is not well correlated with the surface areas of NPs. The superior catalytic performance results from the high H₂ dissociation and low O₂ dissociation properties, which are correlated with the numbers of NiNiPt-fcc and NiNi-bridge sites on the surface of Ni-Pt NPs, respectively. The ReaxFF-MD simulations propose the optimum composition (Ni₈₀Pt₂₀) of 3.0 nm Ni-Pt NPs, which is also explained by the numbers of NiNiPt-fcc and NiNi-bridge sites. Furthermore, from the ReaxFF-MD simulations, the direct synthesis of H₂O₂ for the Ni-Pt NPs can be achieved not only with the Langmuir-Hinshelwood mechanism, which has been conventionally considered, but also with the water-induced mechanism, which is unlikely to occur on pure Pd and Pd-based alloy catalysts; these results are supported by DFT calculations. These results reveal that the ReaxFF-MD method provides significant information for predicting the catalytic properties of NPs, which could be difficult to provide with DFT calculations; thus, it can be a useful framework for the design of nanocatalysts through complementation with a DFT method.

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.

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.

Molecular Simulations of the Microstructure Evolution of Solid Electrolyte Interphase during Cyclic Charging/Discharging

Lithium (Li) metal is regarded as one of the most promising anode materials for use in next-generation high-energy-density rechargeable batteries because of its high volumetric and gravimetric specific capacity, as well as low reduction potential. Unfortunately, uncontrolled dendritic Li growth during cyclic charging/discharging leads to low columbic efficiency and critical safety issues. Hence, comprehensive understanding of the formation mechanism for Li-dendrite growth, particularly at the onset of dendrite formation, is essential for developing Li-metal anode batteries. In this study, reactive molecular dynamics (MD) simulations in combination with the electrochemical dynamics with implicit degrees of freedom (EChemDID) method were performed to investigate the formation and evolution of solid electrolyte interphase (SEI) films for a Li-metal anode under cyclic charging/discharging processes in two distinct dimensions, namely, electrolyte compositions and initial surface morphologies. Our simulations indicated that regardless of the electrolyte compositions and initial anode morphologies, inhomogeneous Li reduction, namely, the formation of Li-reduction "hotspots" during cyclic charging cycles, took place and could serve as the seed for subsequent dendrite growth. The fluorine-containing electrolyte additives could notably mitigate the Li-anode roughening processes by forming dense-SEI-layer products or suppressing electrolyte decomposition. A series of Li-ion-drifting simulations suggest that Li ions navigate through the SEI layer via pathways composed of low-density atoms and become reduced at these reduction hotspots, promoting inhomogeneous deposition and subsequent dendrite growth. The present study reveals atomistic details of the early stage of dendrite growth during cyclic loadings under different electrolyte compositions and anode morphologies, thereby providing insights for designing artificial SEI layers or electrolytes for long-life, high-capacity Li-ion batteries.

An Iterative Fragment Scheme for the ACKS2 Electronic Polarization Model: Application to Molecular Dimers and Chains

The treatment of electrostatic interactions is a key ingredient in the force field-based simulation of condensed phase systems. Most approaches used fixed, site-specific point charges. Yet, it is now clear that many applications of force fields (FFs) demand more sophisticated treatments, prompting the implementation of charge equilibration methods in polarizable FFs to allow the redistribution of charge within the system. One approach allowing both, charge redistribution and site-specific polarization, while at the same time solving methodological shortcomings of earlier methods, is the first-principles-derived atom-condensed Kohn-Sham density functional theory method approximated to the second order (ACKS2). In this work, we present two fragment approaches to ACKS2, termed f-ACKS2 and a self-consistent version, scf-ACKS2, that treat condensed phase systems as a collection of electronically polarizable molecular fragments. The fragmentation approach to ACKS2 not only leads to a more transferable and less system-specific collection of electronic response parameters but also opens up the method to large condensed phase systems. We validate the accuracies of f-ACKS2 and scf-ACKS2 by comparing polarization energies and induced dipole moments for a number of charged hydrocarbon dimers against DFT reference calculations. Finally, we also apply both fragmented ACKS2 variants to calculate the polarization energy for electron-hole pair separation along a chain of anthracene molecules and find excellent agreement with reference DFT calculations.

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.

Designing superior solid electrolyte interfaces on silicon anodes for high-performance lithium-ion batteries

The solid electrolyte interface (SEI) is a passivation layer formed on the surface of lithium-ion battery (LIB) anode materials produced by electrolyte decomposition. The quality of the SEI plays a critical role in the cyclability, rate capacity, irreversible capacity loss and safety of lithium-ion batteries (LIBs). The stability of the SEI is especially important for Si anodes which experience tremendous volume changes during cycling. Therefore, in this review we discuss the effect of the SEI on Si anodes. Firstly, the mechanism of formation, composition, and component properties of solid electrolyte interfaces (SEIs) are introduced, and the SEI of native-oxide-terminated Si is emphasized. Then the growth model and mechanical failure of SEIs are analyzed in detail, and the challenges facing SEIs of Si anodes are proposed. Moreover, we highlight several modification methods for SEIs on Si anodes, including electrolyte additives, surface-functionalization of Si, coating artificial SEIs or protective layers, and the structural design of Si-based composites. We believe that designing a high-quality SEI is of great significance and is beneficial for the improved electrochemical performance of Si anodes.

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.

In-situ Cutting of Graphene into Short Nanoribbons with Applications to Ni-Zn Batteries

Rechargeable Ni–Zn batteries, with high safety, low cost and nontoxicity, can be expected to compete with lithium-ion batteries for market share. However, the issue of dissolution of zinc electrode largely limit the battery cycle life and remains unsolved. We designed a kind of graphene-ZnO hybrid electrode in which in-situ cutting of graphene into short nanoribbons can effectively anchor plenty of zinc atoms onto the surface of graphene. This not only thoroughly fixes the issue of dissolution of zinc electrode but also increases the specific surface areas of zinc and promotes chemical reaction rate of the charge-discharge processes. By performing experimental measurements, we found that the discharge capacity of the new designed Ni-Zn batteries can be as high as 2603 mAh/g_Zno, and the superior electrochemical performance can be kept in 10,000 test cycles, suggesting that the new developed in-situ cutting technique is very useful in electrochemical fields.