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

Through a blend of simulation, machine learning and advanced data analytics, digital twins are emerging as one of AI’s most powerful applications, transforming innovation cycles across a diverse range of industries.

A new material uses raindrops to power the production of fuel from carbon dioxide in the air.

A newly developed additive for magnesium-based batteries brings them a step forward as safer, high-performance alternatives to lithium-ion systems.

From biomedical research to generative AI models, scientific progress depends on strong ethical standards that maintain integrity, transparency and accountability.

The power plants of tomorrow could tap into fusion energy, as scientists gain insight into how to control the reactions and suppress turbulence.

A new computer modelling approach lends a hand with designing lighter, sturdier aircraft components from next-generation composite materials.

Through machine learning, a new mathematical model aims to reduce fuel costs and improve the timeliness of tugboat services in high-traffic ports.

A closer look at aluminium battery electrolytes sheds light on the complex mechanics that set them apart from lithium-ion systems.

Dual-atom catalysts overcome a significant barrier in lithium-sulfur battery performance, opening a new paradigm for catalyst design in next-generation batteries.

Inspired by sponges and trees, a novel hydrogel design paves the way for a new generation of multi-functional electronic soft sensors.

Through machine learning-aided design, A*STAR scientists discover new additives to suppress hazardous metal deposits in high-performance lithium metal batteries.

A big data study reveals that shifts in emotional expressions on social media can predict changes in demand for mental health care services.