Recent advances in computational modelling of atomic systems, spanning molecules,
proteins, and materials, represent them as geometric graphs with atoms embedded as …

Achieving a balance between computational speed, prediction accuracy, and universal
applicability in molecular simulations has been a persistent challenge. This paper presents …

The energy landscape represents a high‐dimensional mapping of the configurational states
of an atomic system with their respective energies. Under isobaric conditions, enthalpy …

Conformer ranking is a crucial task for drug discovery, with methods for generating
conformers often based on molecular (meta) dynamics or sophisticated sampling …

Recent equivariant models have shown significant progress in not just chemical property
prediction, but as surrogates for dynamical simulations of molecules and materials. Many of …

The accuracy of atomistic simulations depends on the precision of force fields. Traditional
numerical methods often struggle to optimize the empirical force field parameters for …

Materials discovery and development are critical for addressing global challenges. Yet, the
exponential growth in materials science literature comprising vast amounts of textual data …

In density functional theory, charge density is the core attribute of atomic systems from which
all chemical properties can be derived. Machine learning methods are promising in …

Modeling inorganic glasses requires an accurate representation of interatomic interactions,
large system sizes to allow for intermediate-range structural order, and slow quenching rates …

The development of artificial intelligence (AI) has significantly impacted our daily lives and
even driven new scientific discoveries. However, the modern AI models based on deep …