Large-scale computational molecular models provide scientists a means to investigate the
effect of microscopic details on emergent mesoscopic behavior. Elucidating the relationship …

The choice of simulation methods in computational materials science is driven by a
fundamental trade-off: bridging large time-and length-scales with highly accurate …

Various physics-and data-driven sequence-dependent protein coarse-grained models have
been developed to study biomolecular phase separation and elucidate the dominant …

In recent years, we have been witnessing a paradigm shift in computational materials
science. In fact, traditional methods, mostly developed in the second half of the XXth century …

Propelled partly by the Materials Genome Initiative, and partly by the algorithmic
developments and the resounding successes of data-driven efforts in other domains …

The use of supervised machine learning to develop fast and accurate interatomic potential
models is transforming molecular and materials research by greatly accelerating atomic …

While a complete understanding of organic semiconductor (OSC) design principles remains
elusive, computational methods─ ranging from techniques based in classical and quantum …

Ionic liquids (ILs) offer a wide range of promising applications because of their much
enhanced properties. However, further development of such materials depends on the …

Over the last few years, coarse-grained molecular dynamics has emerged as a way to model
large and complex systems in an efficient and inexpensive manner due to its lowered …

The traditional computational modeling of protein structure, dynamics, and interactions
remains difficult for many protein systems. It is mostly due to the size of protein …