In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …

Rechargeable batteries have become indispensable implements in our daily life and are
considered a promising technology to construct sustainable energy systems in the future …

In recent years, the Transformer architecture has proven to be very successful in sequence
processing, but its application to other data structures, such as graphs, has remained limited …

Hydrogen is emerging as one of the most promising energy carriers for a decarbonised
global energy system. Transportation and storage of hydrogen are critical to its large-scale …

The first step in the construction of a regression model or a data-driven analysis, aiming to
predict or elucidate the relationship between the atomic-scale structure of matter and its …

Conventional optical components such as lenses, waveplates and holograms rely on light
propagation over distances much larger than the wavelength to shape wavefronts. In this …

Bone remodeling replaces old and damaged bone with new bone through a sequence of
cellular events occurring on the same surface without any change in bone shape. It was …

The integration of data and scientific computation is driving a paradigm shift across the
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …

Many aspects of the large-scale structure of the Universe can be described successfully
using cosmological models in which 27±1% of the critical mass-energy density consists of …

A core challenge for both physics and artificial intelligence (AI) is symbolic regression:
finding a symbolic expression that matches data from an unknown function. Although this …