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Register a new userDynamical properties across different coarse-grained models for ionic liquids
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Room-temperature ionic liquids (RTILs) stand out among molecular liquids for their rich physicochemical characteristics, including structural and dynamic heterogeneity. The significance of electrostatic interactions in RTILs results in long characteristic length- and timescales, and has motivated the development of a number of coarse-grained (CG) simulation models. In this study, we aim to better understand the connection between certain CG parametrization strategies and the dynamical properties and transferability of the resulting models. We systematically compare five CG models: a model largely parametrized from experimental thermodynamic observables; a refinement of this model to increase its structural accuracy; and three models that reproduce a given set of structural distribution functions by construction, with varying intramolecular parametrizations and reference temperatures. All five CG models display limited structural transferability over temperature, and also result in various effective dynamical speedup factors, relative to a reference atomistic model. On the other hand, the structure-based CG models tend to result in more consistent cation-anion relative diffusion than the thermodynamic-based models, for a single thermodynamic state point. By linking short- and long-timescale dynamical behaviors, we demonstrate that the varying dynamical properties of the different coarse-grained models can be largely collapsed onto a single curve, which provides evidence for a route to constructing dynamically-consistent CG models of RTILs.
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A first-principle multiscale modeling approach is presented, which is derived from the solution of the Ornstein-Zernike equation for the coarse-grained representation of polymer liquids. The approach is analytical, and for this reason is transferable. It is here applied to determine the structure of several polymeric systems, which have different parameter values, such as molecular length, monomeric structure, local flexibility, and thermodynamic conditions. When the pair distribution function obtained from this procedure is compared with the results from a full atomistic simulation, it shows quantitative agreement. Moreover, the multiscale procedure accurately captures both large and local scale properties while remaining computationally advantageous.
A coarse-grained simulation model eliminates microscopic degrees of freedom and represents a polymer by a simplified structure. A priori, two classes of coarse-grained models may be distinguished: those which are designed for a specific polymer and reflect the underlying atomistic details to some extent, and those which retain only the most basic features of a polymer chain (chain connectivity, short-range excluded-volume interactions, etc.). In this review we mainly focus on the second class of generic polymer models, while the first class of specific coarse-grained models is only touched upon briefly.
We present a detailed derivation and testing of our approach to rescale the dynamics of mesoscale simulations of coarse-grained polymer melts (I. Y. Lyubimov et al. J. Chem. Phys. textbf{132}, 11876, 2010). Starting from the first-principle Liouville equation and applying the Mori-Zwanzig projection operator technique, we derive the Generalized Langevin Equations (GLE) for the coarse-grained representations of the liquid. The chosen slow variables in the projection operators define the length scale of coarse graining. Each polymer is represented at two levels of coarse-graining: monomeric as a bead-and-spring model and molecular as a soft-colloid. In the long-time regime where the center-of-mass follows Brownian motion and the internal dynamics is completely relaxed, the two descriptions must be equivalent. By enforcing this formal relation we derive from the GLEs the analytical rescaling factors to be applied to dynamical data in the coarse-grained representation to recover the monomeric description. Change in entropy and change in friction are the two corrections to be accounted for to compensate the effects of coarse-graining on the polymer dynamics. The solution of the memory functions in the coarse-grained representations provides the dynamical rescaling of the friction coefficient. The calculation of the internal degrees of freedom provides the correction of the change in entropy due to coarse-graining. The resulting rescaling formalism is a function of the coarse-grained model and thermodynamic parameters of the system simulated. The rescaled dynamics obtained from mesoscale simulations of polyethylene, represented as soft colloidal particles, by applying our rescaling approach shows a good agreement with data of translational diffusion measured experimentally and from simulations. The proposed method is used to predict self-diffusion coefficients of new polyethylene samples.
Ionic liquids are a special category of molten salts with melting points near ambient temperatures or by convention below 100 C. Owing to their numerous valuable physicochemical properties as bulk liquids, solvents, at surfaces and in confined environments, ILs have attracted increasing attention in both academic and industrial communities in a variety of application areas involving physics, chemistry, material science and engineering. Due to their nearly limitless number of combinations of cation and anion pairs and mixtures with cosolvents, a molecular level understanding of their hierarchical structures and dynamics, requiring strategies to connect several length and time scales, is of crucial significance for rational design of ILs with desired properties, and thereafter refining their functional performance in applications. As an invaluable compliment to experiments from synthesis to characterization, computational modelling and simulations have significantly increased our understanding on how physicochemical and structural properties of ILs can be controlled by their underlying chemical and molecular structures. In this chapter, we will give examples from our own modelling work based on selected IL systems, with focus on imidazolium based and tetraalkylphosphonium orthoborate ILs, studied at several spatiotemporal scales in different environments and with particular attention to applications of high technological interest.
Ionic Liquids (ILs) are organic molten salts characterized by the total absence of solvent. They show remarkable properties: low vapor pressure, high ionic conductivity, high chemical, thermal and electrochemical stability. These electrolytes meet therefore key criteria for the development of safe energy storage systems. Due to a competition between electrostatic and van der Walls interactions, ILs show an uncommon property for neat bulk liquids: they self-organize in transient nanometric domains. In ILs-based electrochemical devices, this fluctuating nano-segregation acts as energy barriers to the long range diffusional processes and hence to the ionic conductivity. Here, we show how the ionic conductivity of ILs can be increased by more than one order of magnitude by exploiting one dimensional (1D) confinement effects in macroscopically oriented carbon nanotube (CNT) membranes. We identify 1D CNT membranes as promising separators for high instant power batteries.
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