Abstract Machine learning (ML) is rapidly revolutionizing many fields and is starting to
change landscapes for physics and chemistry. With its ability to solve complex tasks …

Progress in the discovery of new materials has been accelerated by the development of
reliable quantum-mechanical approaches to crystal structure prediction. The properties of a …

Thanks to the development of experimental high-pressure techniques and methods for
crystal-structure prediction based on quantum mechanics, in the past decade, numerous …

In the search for new functional materials, quantum mechanics is an exciting starting point.
The fundamental laws that govern the behaviour of electrons have the possibility, at the …

For decades, borides have been primarily studied as crystallographic oddities. With such a
wide variety of structures (a quick survey of the Inorganic Crystal Structure Database counts …

Single crystals of the ternary borides Cr2AlB2, Cr3AlB4, Cr4AlB6, MoAlB, WAlB, Mn2AlB2,
and Fe2AlB2 were grown from the elements with an excess of Al. Structures were refined by …

Large language models (LLMs) such as generative pretrained transformers (GPTs) have
shown potential for various commercial applications, but their applicability for materials …

Transition-metal boron-rich compounds exhibit favorable synthesis conditions and
mechanical properties that hold great promise for wide-ranging applications. However, the …

As the proliferation of high-throughput approaches in materials science is increasing the
wealth of data in the field, the gap between accumulated-information and derived …

Structurally ordered intermetallic borides are a large family of inorganic solids with rich
bonding schemes, and huge compositional and structural diversity. The family members …