The transition to solid-state Li-ion batteries will enable progress toward energy densities of 1000 W·hour/liter and beyond. Composites of a mesoporous oxide matrix filled with nonvolatile ionic liquid electrolyte fillers have been explored as a solid electrolyte option. However, the simple confinement of electrolyte solutions inside nanometersized pores leads to lower ion conductivity as viscosity increases. Here, we demonstrate that the Li-ion conductivity of nanocomposites consisting of a mesoporous silica monolith with an ionic liquid electrolyte filler can be several times higher than that of the pure ionic liquid electrolyte through the introduction of an interfacial ice layer. Strong adsorption and ordering of the ionic liquid molecules render them immobile and solid-like as for the interfacial ice layer itself. The dipole over the adsorbate mesophase layer results in solvation of the Li + ions for enhanced conduction. The demonstrated principle of ion conduction enhancement can be applied to different ion systems. Mees, P. M. Vereecken, Silica gel solid nanocomposite electrolytes with interfacial conductivity promotion exceeding the bulk Li-ion conductivity of the ionic liquid electrolyte filler. Sci. Adv. 6, eaav3400 (2020).

Monte Carlo (MC) methods have a long-standing history as partners of molecular dynamics (MD) to simulate the evolution of materials at the atomic scale. Among these techniques, the uniform-acceptance force-bias Monte Carlo (UFMC) method [G. Dereli, Mol. Simul. 8, 351 (1992)] has recently attracted attention [M. Timonova et al., Phys. Rev. B 81, 144107 (2010)] thanks to its apparent capacity of being able to simulate physical processes in a reduced number of iterations compared to classical MD methods. The origin of this efficiency remains, however, unclear. In this work we derive a UFMC method starting from basic thermodynamic principles, which leads to an intuitive and unambiguous formalism. The approach includes a statistically relevant time step per Monte Carlo iteration, showing a significant speed-up compared to MD simulations. This time-stamped force-bias Monte Carlo (tfMC) formalism is tested on both simple one-dimensional and three-dimensional systems. Both test-cases give excellent results in agreement with analytical solutions and literature reports. The inclusion of a time scale, the simplicity of the method, and the enhancement of the time step compared to classical MD methods make this method very appealing for studying the dynamics of many-particle systems.

Transition metal oxide-based resistor random access memory (RRAM) takes advantage of oxygen-related defects in its principle of operation. Since the change in resistivity of the material is controlled by the oxygen deficiency level, it is of major importance to quantify the kinetics of the oxygen diffusion, key factor for oxide stoichiometry. Ab initio accelerated molecular dynamics techniques are employed to investigate the oxygen diffusivity in amorphous hafnia (HfOx, x = 1.97, 1.0, 0.5). The computed kinetics is in agreement with experimental measurements.