Manufacturing Trade and Connectivity (MTC)

A*STAR researchers develop machine learning models that quickly and accurately simulate chemical reactions involving complex liquid interactions.

Advanced photonic processors boost machine learning efficiency by handling vast data streams in parallel, with potential benefits for enhanced patient monitoring and cloud computing.

The innovative integration of robotics and machine learning accelerates the development of efficient, sustainable hydrogen catalysts.

A breakthrough approach integrates light-responsive molecules into polymers to advance biomedical applications.

Aided by machine learning, researchers develop a novel high-performance steel optimised for more eco-friendly 3D printing.

An innovative method puts a new ‘spin’ on light to offer exciting prospects for quantum computing, telecommunications and security technologies.

Researchers show that a new design element for nanoscale light-bending materials makes them electrically tuneable at room temperature, opening doors to new optical technologies.

A new method for fabricating structures in optical devices improves their ability to capture and emit light, paving the way for advanced communication and sensor technologies.

Researchers reach a new understanding of how synthetic enzymes can be optimised as alternatives to naturally derived metalloenzymes.

A new transparent soft robot uses innovative materials to blend into underwater environments by mimicking the moon jellyfish’s movement and appearance.

A new approach to generating terahertz radiation offers a compact, tuneable and scalable solution for faster data transmission and improved imaging applications.

A breakthrough method for detecting mirror-image molecules with incredible sensitivity promises transformative applications in medicine and chemistry.