With the development of artificial intelligence and the intersection of machine learning (ML)
and materials science, the reclamation of ML technology in the realm of lithium ion batteries …

The development of fast synthesis methods and accurate engineering of the shapes and
characteristics of inorganic solid electrolytes has been substantially aided by the …

Solid-state ion conductors (SSICs) have emerged as a promising material class for
electrochemical storage devices and novel compounds of this kind are continuously being …

The vast amount of computational studies on electrical conduction in solid state electrolytes
is not mirrored by comparable efforts addressing thermal conduction, which has been …

First-principles approaches for phonon-limited electronic transport are typically based on
many-body perturbation theory and transport equations. With that, they rely on the validity of …

Statistical learning algorithms provide a generally-applicable framework to sidestep time-
consuming experiments, or accurate physics-based modeling, but they introduce a further …

We present for the first time a multiscale machine learning approach to jointly simulate
atomic structure and dynamics with the corresponding solid state Nuclear Magnetic …

Solid-state sodium batteries require effective electrolytes that conduct at room temperature.
The Na3PnCh4 (Pn= P, Sb; Ch= S, Se) family has been studied for their high Na ion …

Understanding the ionic conduction mechanisms in solid electrolyte glasses and glass-
ceramics is an important task for improving the performance of next-generation all-solid …

We perform static and dynamic ab initio simulations to investigate the structural and the
thermodynamic properties of Li6PS5Cl, a solid electrolyte actively considered for solid-state …