Singapore Launches $10M AI Lab to Accelerate Semiconductor and Clean Hydrogen Discovery
Source: The Straits Times
Singapore has launched a $10 million AI-powered lab called the Materials Data Foundry, designed to accelerate the discovery and mass production of next-generation semiconductors and clean hydrogen. The facility, jointly set up by the National University of Singapore (NUS) and the.
Singapore has launched a $10 million AI-powered lab called the Materials Data Foundry, designed to accelerate the discovery and mass production of next-generation semiconductors and clean hydrogen. The facility, jointly set up by the National University of Singapore (NUS) and the University of Toronto, uses artificial intelligence to autonomously design and run thousands of experiments — collapsing what traditionally takes years of research into dramatically shorter timelines.
The lab is one of eight projects unveiled at the AI4X-Accelerate Conference 2026 under Singapore's national AI-for-Science (AI4S) programme, backed by S$120 million from the National Research Foundation (NRF). Professor Tan Chorh Chuan, Permanent Secretary of National Research and Development who chairs A*STAR, said the goal is to "move faster and more innovatively in terms of discovery." The eight projects span three domains: advanced manufacturing and materials, biomedical and health sciences, and aviation and maritime technologies.
Other projects funded under the same programme include an AI agent that automates mRNA vaccine design, digital twins that predict farmland conditions across Southeast Asia, and an AI system that predicts disease from a routine full blood count test. The research draws on Singapore's dense network of global research outposts, including Imperial Global Singapore, the Illinois Advanced Research Centre in Singapore, and the Cambridge Centre for Advanced Research and Education in Singapore.
What makes the Materials Data Foundry strategically significant is its explicit focus on solving the "valley of death" in materials commercialisation — the gap between lab-scale discovery and industrial-scale manufacturing. By coupling AI with high-throughput experimentation, the lab aims to generate production-ready "recipes" that can be directly adopted by manufacturers. For semiconductors, this means faster iteration on chip materials for AI and high-performance computing. For clean hydrogen, it means cheaper catalysts and more efficient production pathways.
Why it matters for Singapore: This is a direct bet on AI as a scientific accelerator, not just a business tool. Singapore's S$120 million AI4S programme positions the city-state to compete in the high-value intersection of AI and materials science — a domain where Applied Materials, NUS, and A*STAR are already collaborating. With the semiconductor industry investing heavily in Singapore (Applied Materials just opened a S$600M campus here), AI-accelerated materials discovery could become a significant competitive advantage for the country's manufacturing ecosystem.
