Urban Solutions and Sustainability (USS)

Researchers tune the distance between atoms in single-atom catalysts, allowing them to speed up complex chemical reactions.

Researchers develop a polymer-based bioelectronic transistor that could power tomorrow’s point-of-care diagnostic devices.

Despite the hype, State-of-the-art machine learning challenges one of the toughest problems in systems biology.

Scalable and cost-effective methods for growing fat cells pose a commercialisation barrier for cultivated meat products.

Researchers create a new recyclable, eco-friendly class of plastics derived from natural sugar molecules to address the plastic waste crisis.

Artificial intelligence could help speed up the discovery and development of materials towards a greener future.

Researchers identify an easy-to-recycle plastic alternative for use in electronics, making strides towards a circular economy.

A new compression method developed at A*STAR shrinks energy and hardware requirements for complex computational platforms on everyday devices.

A purpose-built machine learning platform takes the guesswork out of catalyst formulations for green energy generation.

A*STAR scientists develop a process for transforming coconut waste into strong and biodegradable bioplastics.

Researchers developed a new technique for manufacturing powerful and versatile synthetic catalysts.

Materials science and computational techniques come together to advance new design schemes for aerospace alloys.