AI for Materials Initiative
NTU MSE is bringing together interdisciplinary expertise from artificial intelligence and materials science to develop a new initiative focused on an engineering-validation and deployment bridge that turns AI-enabled materials discovery into scenario-ready solutions.
By integrating artificial intelligence, materials science, and experimental platforms, the initiative develops closed-loop workflows and validation systems that translate research breakthroughs into deployment-ready technologies for Singapore’s strategic industries and beyond.
Learn moreWhy This Matters Now
Materials innovation underpins critical sectors — from semiconductors and energy storage to healthcare and sustainable manufacturing. Yet, traditional discovery processes remain time-intensive, costly, and often disconnected from downstream deployment.
At the same time, a new paradigm is emerging worldwide: AI-enabled, closed-loop research systems that integrate design, synthesis, characterisation, and optimisation into accelerated discovery workflows.
In this new landscape, competitive advantage is defined not only by advanced AI models, but by the ability to build application infrastructure — reproducible experimentation pipelines, high-throughput validation platforms, and decision tools that translate research insights into engineered systems.
Singapore is uniquely positioned to lead in this space. National priorities under RIE2030 and the National AI Strategy 2.0 have created strong demand across sectors, including semiconductors, sustainable aviation fuels, green shipping, healthy longevity, and precision agriculture. These industries require faster validation of new materials, robust process windows, and AI-enabled decision support embedded directly within operational environments.
Our Direction
This initiative aims to establish a platform for AI-enabled materials discovery in Asia — connecting fundamental research with translational development and industry collaboration.
Bridging Discovery and Deployment
More About UsThe AI for Materials initiative focuses on translating advances in materials science and AI into scenario-validated workflows, datasets, and tools that R&D teams and industrial partners can adopt.
By bridging discovery and deployment, the initiative helps position Singapore as a global node for AI-driven materials innovation, supporting both national priorities and the competitiveness of future industries.
Learn more about the initiative and leadership team.
Discover our core capabilitiesThe Vertical and Application‑anchored Pillars We Are Developing:
End-to-End Materials Innovation
We integrate capabilities across the full materials lifecycle — from materials discovery and process development to pilot-scale validation and real-world deployment.
Application-Driven AI Solutions
We begin with real industry and field challenges — such as thin-film optimisation for packaging-relevant materials, Zn battery degradation, HEA corrosion under realistic environments, non-invasive biosensing needs, or in-field nutrient monitoring.
Materials‑ and SDL‑centred infrastructure versus generic AI tooling
We bring together materials expertise, experimental platforms, and applied AI tools within a unified environment.
Plug-and-Play Workflows for Singapore’s Materials and Manufacturing Ecosystem
The AI for Materials initiative is explicitly designed to bridge fundamental materials discovery, SDL infrastructure, and manufacturing AI within Singapore’s innovation ecosystem.
Focus Areas
Learn More
Semiconductors and microelectronics
Solar and clean‑energy materials
Functional & structural alloys and inorganics
Soft and bio-materials and devices (health, polymers, elastomers, bio‑interfaces)
Applied‑AI platforms (precision agriculture and cross‑domain sensing)
Modular capability architecture
Learn MoreThe AI for Materials initiative supports a wide range of application scenarios — and is designed to expand into many more — because our work is not built as isolated case studies. Instead, each solution is assembled from a shared capability architecture.
Whether advancing materials discovery or solving materials-in-service challenges, we deploy the same foundational building blocks:
AI brain
The AI brain selects and executes adaptive workflows
Modular algorithms
Modular algorithms interpret data and recommend next actions
Modular hardware
Automated hardware platforms generate the next most informative measurements
Designed for Reuse, Repeatability and Deployment
By recombining these components, we rapidly configure solutions for new materials systems, devices, and deployment environments. This architecture enables the AI for Materials initiative to operate beyond one-off demonstrations. It is deliberately structured to:
Enable cross-domain reuse
Workflows can be redeployed across different instruments and materials systems while retaining common module interfaces and experiment templates.Ensure repeatable optimisation
Objectives, constraints, experiment selection logic, and stopping criteria are explicitly defined to make optimisation systematic and reproducible.Support credible deployment
Safety and quality assurance checkpoints, human-in-the-loop validation, and auditable run logs ensure solutions are robust, traceable, and deployment-ready.
Events
Partner with Us
We welcome collaboration with partners across industry, government, academia, and the broader research ecosystem to shape and advance this initiative.
As this effort develops, there are multiple pathways to engage — from research collaboration and talent development to strategic and philanthropic support.
Industry Partners
Work with us to accelerate materials innovation and translation into real-world applications.
Explore collaborative research opportunities
Co-develop applications and pilot projects
Access emerging capabilities in AI-enabled materials discovery
Engage with a pipeline of future-ready talent
Engage with emerging talent and capabilities
Government & Research Agencies
Partner with us to advance strategic priorities and interdisciplinary research programmes.
Align on national and regional research priorities
Support translational and mission-oriented initiatives
Co-develop platforms that bridge research and deployment
Philanthropy & Strategic Donors
Support the development of frontier research and future talent.
Enable new research and innovation programmes
Contribute to talent development and training initiatives
Support long-term capability building in AI and materials science
Researchers & Fellows
We welcome interest from researchers looking to contribute to or grow with this initiative.
Join us: Opportunities may be available for postdoctoral researchers and research staff as the initiative develops
Apply for fellowships: We support applications to competitive external fellowship schemes aligned with our research focus
Get Involved
We welcome conversations with organisations and individuals interested in contributing to or collaborating on this initiative.
Associate Professor Kedar Hippalgaonkar, Director (email: [email protected])
Assistant Professor Leonard Ng, Deputy Director (email: [email protected])