The astonishing progress achieved in perovskite solar cells in recent years has coincided
with the growing interest in machine learning (ML) for material discovery, and the number of …

Artificial intelligence (AI) is the most important new methodology in scientific research since
the adoption of quantum mechanics and it is providing exciting results in numerous fields of …

We investigate the stability of self-trapped holes (STHs) and the acceptor levels of
substitutional Mg and N impurities in α-, β-, δ-, and ɛ-Ga 2 O 3 using first-principles …

p-Type do** in Cu (I)-based semiconductors is pivotal for solar cell photoabsorbers and
hole transport materials to improve the device performance. Impurity do** is a …

A material's electronic properties and technological utility depend on its band gap value and
the nature of band gap (ie direct or indirect). This nature of band gaps is notoriously difficult …

The great tunability of the properties of halide perovskites presents new opportunities for
optoelectronic applications as well as significant challenges associated with exploring …

Energy storage and modern electronics industries are in essential need of high dielectric
and highly flexible materials. In this study, polyacrylonitrile and reduced graphene oxide …

Oxygen vacancies play significant roles in various properties of oxide materials. Therefore,
insights into the oxygen vacancies can facilitate the discovery of better oxide materials. To …

Materials informatics exploiting machine learning techniques, eg, Bayesian optimization
(BO), have the potential to reduce the number of thin-film growth runs for optimization of thin …

MXenes are excellent electrode materials and have superior photocatalytic activity. The
electronic properties, optical properties, photocatalytic activity and quantum capacitance of …