A*STAR Institute of High Performance Computing (A*STAR IHPC)

A*STAR researchers have developed a computational technique that allows them to predict the properties of MXene alloys.

Computational fluid dynamics models and 3D printing are changing the way artificial ocean basins are designed.

Machine learning could pave the way for the creation of novel alloys for a range of practical applications, say scientists at A*STAR.

Factoring in the conservation of mass makes simulations of two-phase flows more stable and accurate.

With a sound understanding of polymers, their properties and the methods to synthesize them, scientists can create novel materials for a wide range of practical applications.

Simulating building-cooling louvers need not be computationally expensive, say A*STAR researchers.

A*STAR researchers have devised a machine learning strategy that can be applied to translation and other complex classification problems.

A*STAR scientists have designed foldable sound barriers by borrowing concepts from origami, the art of paper folding.

Using computational tools, A*STAR researchers are learning how best to deploy air treatment systems across large urban areas.

A spin injection technique that is more than 10,000 times more efficient than existing methods could allow for the development of ultrafast spintronic computers

In shape memory alloys, the right combination of crystal grains can achieve high strength and still retain memory

The tiny diamond pyramid tips used for atomic force microscopy may also prove to be highly useful for nanoscale, quantum sensing