S&AS: INT: Autonomous Experimentation Platform for Accelerating Manufacturing of Advanced Materials Grant uri icon


  • Discovering and manufacturing new materials is a laborious and time-consuming process. Historically this process takes significant effort from material scientists and manufacturing engineers as they explore many different ingredient compositions and process conditions to find the right combination leading to a material with the desired properties. This project is developing an autonomous experimentation platform to replace a significant amount of this human effort in experimentation and thus accelerate the discovery and manufacturing of advanced materials. Such an autonomous experimental testbed could have significant impacts on engineering practice and revolutionize the material discovery and advanced manufacturing landscape. This would in turn accelerate discovery in materials for a great number of industries and applications. Students to be involved in the project will receive training with a blend of data science and material/manufacturing science.This project introduces artificial intelligence and autonomy modules into an autonomous experimentation platform to mimic a human scientist''s ability to handle surprising observations, synthesize diverse bodies of knowledge, and explore a complex and large design space. The key research components in this platform are organized around three capabilities themes: (1) exploitation to efficiently determine the most promising regions of a design space, (2) exploration to recognize and reason about surprises arising from unusual designs, and (3) expansion of newly-discovered design space based on mining new knowledge from literature and databases, preferentially gaining knowledge in regions likely to contain superior material design solutions. The proposed system is cognizant, adaptive, knowledge-rich and taskable, interacting with human scientists by way of simple commands and executing an autonomous discovery process with a minimal and appropriate degree of human intervention.This award reflects NSF''s statutory mission and has been deemed worthy of support through evaluation using the Foundation''s intellectual merit and broader impacts review criteria.

date/time interval

  • 2019 - 2022