Vibrational Properties of Metastable Polymorph Structures by Machine Learning.

Despite vibrational properties being critical for the ab initio prediction of finite-temperature stability as well as thermal conductivity and other transport properties of solids, their inclusion in ab initio materials repositories has been hindered by expensive computational requirements. Here we tackle the challenge, by showing that a good estimation of force constants and vibrational properties can be quickly achieved from the knowledge of atomic equilibrium positions using machine learning. A random-forest algorithm trained on 121 different mechanically stable structures of KZnF reaches a mean absolute error of 0.

Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus ab Initio Methods.

Machine learning (ML) is increasingly becoming a helpful tool in the search for novel functional compounds. Here we use classification via random forests to predict the stability of half-Heusler (HH) compounds, using only experimentally reported compounds as a training set. Cross-validation yields an excellent agreement between the fraction of compounds classified as stable and the actual fraction of truly stable compounds in the ICSD.

A first-principles comparative study of lithium, sodium, and magnesium storage in pure and gallium-doped germanium: Competition between interstitial and substitutional sites.

Thermodynamics and kinetics of Li, Na, and Mg storage in Ge are studied ab initio. The most stable configurations can consist of tetrahedral, substitutional, or a combination of the two types of sites. In the dilute limit, Li and Na prefer interstitial, while Mg prefers substitutional sites.

Comparison of alpha and beta tin for lithium, sodium, and magnesium storage: An ab initio study including phonon contributions.

We present a comparative ab initio study of Li, Na, and Mg storage in tin, including phononic effects and phase competition between α and β Sn. Mg doping at low concentration is found to stabilize the β phase. On the contrary, Li and Na doping is shown to reverse the stability of the phases at room temperature: Li/Na-doped α-Sn is more stable than Li/Na-doped β-Sn up to a temperature of around 380/400 K.