Solids that are also liquids: elastic tensors of superionic materials

Superionics are fascinating materials displaying both solid- and liquid-like characteristics: as solids, they respond elastically to shearstress;as liquids, they display fast-ion diffusion at normal conditions. In addition to such scientific interest, superionics aretechnologically relevant for energy, electronics, and sensing applications. Characterizing and understanding their elastic propertiesis, e.g., urgently needed to address their feasibility as solid-state electrolytes in all-solid-state batteries. However, static approachesto elasticity assume well-defined reference positions around which atoms vibrate, in contrast with the quasi-liquid motion of themobile ions in fast ionic conductors. Here, we derive the elastic tensors of superionics from ensemble fluctuations in the isobaric-isothermal ensemble, exploiting extensive Car-Parrinello simulations. We apply this approach to paradigmatic Li-ion conductors,and complement with a block analysis to compute statistical errors. Static approaches sampled over the trajectories oftenoverestimate the response, highlighting the importance of a dynamical treatment in determining elastic tensors in superionics.

Infrared-active phonons in one-dimensional materials and their spectroscopic signatures

Dimensionality provides a clear fingerprint on the dispersion of infrared-active,polar-optical phonons.For these phonons,the local dipoles parametrized by the Born effective charges drive the LO-TO splitting of bulk materials;this splitting actually breaks down in two-dimensional materials.Here,we develop the theory for one-dimensional(1D)systems—nanowires,nanotubes,and atomic and polymeric chains.Combining an analytical model with the implementation of density-functional perturbation theory in 1D boundary conditions,we show that the dielectric splitting in the dispersion relations collapses as x^(2) log(x)at the zone center.The dielectric properties and the radius of the 1D materials are linked by the present work to these red shifts,opening infrared and Raman characterization avenues.

Projectability disentanglement for accurate and automated electronic-structure Hamiltonians

Maximally-localized Wannier functions(MLWFs)are broadly used to characterize the electronic structure of materials.Generally,one can construct MLWFs describing isolated bands(e.g.valence bands of insulators)or entangled bands(e.g.valence and conduction bands of insulators,or metals).Obtaining accurate and compact MLWFs often requires chemical intuition and trial and error,a challenging step even for experienced researchers and a roadblock for high-throughput calculations.Here,we present an automated approach,projectability-disentangled Wannier functions(PDWFs),that constructs MLWFs spanning the occupied bands and their complement for the empty states,providing a tight-binding picture of optimized atomic orbitals in crystals.Key to the algorithm is a projectability measure for each Bloch state onto atomic orbitals,determining if that state should be kept identically,discarded,or mixed into the disentanglement.We showcase the accuracy on a test set of 200 materials,and the reliability by constructing 21,737 Wannier Hamiltonians.

Automated mixing of maximally localized Wannier functions into target manifolds

Maximally localized Wannier functions(MLWFs)are widely used in electronic-structure calculations.We have recently developed automated approaches to generate MLWFs that represent natural tight-binding sets of atomic-like orbitals;these describe accurately both the occupied states and the complementary unoccupied ones.For many applications,it is required to use MLWFs that describe instead certain target groups of bands:the valence or the conduction bands,or correlated manifolds.Here,we start from these tight-binding sets of MLWFs,and mix them using a combination of parallel transport and maximal localization to construct manifold-remixed Wannier functions(MRWFs):these are orthogonal sets of MLWFs that fully and only span desired target submanifolds.The algorithm is simple and robust,and is showcased here in reference applications(silicon,MoS_(2),and SrVO_(3))and in a mid-throughput study of 77 insulators.