A National Science Foundation (NSF) grant will help lay the foundation for an interdisciplinary institute that encourages the use of artificial intelligence-enabled materials discovery, design, and synthesis, including for biosensors.
AI offers an important suite of tool for scientists, across many domains. The focus of the NSF-funded project is on accelerating materials design and synthesis methods that would take years or even decades of effort through traditional means. Researchers often must resort to methodical, painstaking trial-and-error processes as they seek to make advances in materials design. By automating some of that work, AI and machine learning could help speed up discoveries, helping the scientists produce innovations that serve science and society.
The emergence of big data and advances in machine learning have dramatically accelerated some of the key steps in science, for example, fitting complex models to data and predictive modeling. However, other key elements of the scientific process — such as generating hypotheses; designing, prioritizing and executing experiments; integrating data, models and simulations; and communicating across disciplines — remain largely untouched by the advances in artificial intelligence (AI).
The resulting advances in AI-enabled materials discovery can help meet the demand for new materials for a number of critical applications, such as biosensors, next-generation computing, and energy.
Among the goals, the institute will serve as a catalyst to establish collaborations that will transcend institutional and organizational boundaries. The planning project will organize a seminar series, workshops and idea labs to further develop the vision, initiate interdisciplinary research at the nexus between AI and materials science, identify the AIMS infrastructure needs, develop education and outreach plans, establish cohesive partnerships and develop the requisite organizational structure and processes for realizing the AIMS vision.