Manufacturing Trade and Connectivity (MTC)

A new streamlined method for purifying lab-grown viruses could accelerate vaccine production, allowing manufacturers to respond rapidly to emerging viral threats

A*STAR’s steady investments in R&D and talent create the ideal conditions for impactful science, says its Chief Executive Officer Frederick Chew.

A fresh design approach to high-performing variable-stiffness rotating joints could enable humans to work safely alongside robots in industrial manufacturing environments.

Scientists have developed a faster, more energy-efficient method for 3D printing magnesium alloys, creating new opportunities for biomedical applications.

A novel 3D printing method developed by A*STAR researchers fabricates soft support for tissue growth, with embedded channels that ensure nutrient supply.

Deep learning algorithms for predicting machine failures in industrial settings can be compressed without compromising their performance, say A*STAR researchers.

Compact nanochain waveguides that can efficiently transmit infrared light and even slow light down to a fraction of its usual speed could take photonics mainstream.

By giving algorithms the ability to generalize, researchers are expanding the range of problems that can be tackled with artificial intelligence.

A machine learning method that finds defects or dimensional deviation on 3D-printed surfaces ‘on-the-fly’ is paving the way for smart, fully automated systems.

New research shows that titanium alloys joined by 3D-printed curved interlayers are stronger and less likely to crack.

Artificial neural networks are now being used to make 3D-printed metal structures more accurately—and stronger—than ever before.

An integrated simulation model provides a clearer picture of what happens when a water droplet comes in contact with a hydrophobic surface.