Supercapacitors such as electric double‐layer capacitors (EDLCs) and pseudocapacitors are becoming increasingly important in the field of electrical energy storage. Theoretical study of energy storage in EDLCs focuses on solving for the electric double‐layer structure in different electrode geometries and electrolyte components, which can be achieved by molecular simulations such as classical molecular dynamics (MD), classical density functional theory (classical DFT), and Monte‐Carlo (MC) methods. In recent years, combining first‐principles and classical simulations to investigate the carbon‐based EDLCs has shed light on the importance of quantum capacitance in graphene‐like 2D systems. More recently, the development of joint density functional theory (JDFT) enables self‐consistent electronic‐structure calculation for an electrode being solvated by an electrolyte. In contrast with the large amount of theoretical and computational effort on EDLCs, theoretical understanding of pseudocapacitance is very limited. In this review, we first introduce popular modeling methods and then focus on several important aspects of EDLCs including nanoconfinement, quantum capacitance, dielectric screening, and novel 2D electrode design; we also briefly touch upon pseudocapactive mechanism in RuO2. We summarize and conclude with an outlook for the future of materials simulation and design for capacitive energy storage.

Room-temperature ionic liquids (RTILs) are a class of organic salts that are liquid at room temperature. Their physiochemical properties, including low vapor pressure and wide electrochemical stability window, have driven their use as electrolytes in many electrochemical applications; however, the slow transport properties of many RTILs have limited their utility in some applications. This issue is often mitigated by solvating ionic liquids in neutral organic solvents. To date, however, solvent interactions have only been explored for a small number of solvents, particularly acetonitrile and propylene carbonate, at only a few compositions. In this work, we use molecular dynamics simulations in the context of a computational screening approach to study mixtures of ionic liquids in many different solvents at a range of concentrations. Building on prior work, we again find that ionic liquid diffusivity increases monotonically with greater solvent concentration. In contrast to prior work, we find that pure solvent diffusivity, not polarity, is the most influential solvent property on mixture behavior. We also explore the concentration dependence of ionic conductivity and find maxima at intermediate concentrations. Experimental conductivity measurements, inspired by the computational screening study, support this observation with qualitatively consistent results. These results can further guide the selection of solvents for electrochemical applications of RTILs.

We explore the influence of the solvent dipole moment on cation-anion interactions and transport in 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl), [BMIM][Tf2N]. Free energy profiles derived from atomistic molecular dynamics (MD) simulations show a correlation of the cation-anion separation and the equilibrium depth of the potential of mean force with the dipole moment of the solvent. Correlations of the ion diffusivity with the dipole moment and the concentration of the solvent were further demonstrated by classical MD simulations. Quasi-elastic neutron scattering experiments with deuterated solvents reveal a complex picture of nanophase separation into the ionic liquid-rich and solvent-rich phases. The experiment corroborates the trend of concentration- and dipole moment-dependent enhancement of ion mobility by the solvent, as suggested by the simulations. Despite the considerable structural complexity of ionic liquid-solvent mixtures, we can rationalize and generalize the trends governing ionic transport in these complex electrolytes.

Most polar solvent molecules are unstable toward electrode materials used in Li-based batteries. Solid electrolytes and ionic liquids are far more stable; however, they have relatively low conductivity, and therefore electrical energy storage devices based on them would suffer from low power. Solvent-in-salt (SIS) systems combine chemical stability with relatively high conductivity. Here, we show how the nature of the employed anion affects the structure and dynamics of SIS systems. The transport of ions in lithium bis(fluorosulfonyl)imide (Li-FSI) systems was determined to be always faster than that in lithium bis(trifluoromethanesulfonyl)imide (Li-TFSI) systems. Moreover, we found that viscosity does not solely control conductivity and that the lower conductivity of TFSI − solutions is related to their stronger interaction with the solvent. This restricts solvent dynamics and slows down ion motions compared to that of FSI − . Interestingly, the TFSI−solvent interaction also leads to better charge separation (weaker ion−ion correlations) and a higher transference number for Li. Our results suggest that the ability to tune the solvent network formed around the anions may further improve electrolyte conductivity and Li transference number for safer and more efficient energy storage devices.

A key component to enhancing reproducibility in the molecular simulation community is reducing ambiguity in the parameterization of molecular models. Ambiguity in molecular models often stems from the dissemination of molecular force fields in a format that is not directly usable or is ambiguously documented via a non-machine readable mechanism. Specifically, the lack of a general tool for performing automated atom-typing under the rules of a particular force field facilitates errors in model parameterization that may go unnoticed if other researchers are unable reproduce this process. Here, we present Foyer, a Python tool that enables users to define force field atom-typing rules in a format that is both machine-and human-readable thus eliminating ambiguity in atom-typing and additionally providing a framework for force field dissemination. Foyer defines force fields in an XML format, where SMARTS strings are used to define the chemical context of a particular atom type. Herein we describe the underlying methodology of the Foyer package, highlighting its advantages over typical atom-typing approaches and demonstrate is application in several use-cases.