LLNL, University of California partner for AI-driven additive manufacturing research

LLNL Early Career Initiative (Download Image)

University of California (UC), Berkeley, mechanical engineering faculty Grace Gu was selected as the inaugural recipient of the LLNL Early Career UC Faculty Initiative for her proposal, "Toward AI-driven additive manufacturing for metal-ceramic composite structures." Image courtesy of Grace Gu and LLNL.

Lawrence Livermore National Laboratory (LLNL) today announced that Grace Gu, a faculty member in mechanical engineering at the University of California (UC), Berkeley, has been selected as the inaugural recipient of the LLNL Early Career UC Faculty Initiative.

The initiative is a joint endeavor between LLNLs Strategic Deterrence Principal Directorate and UC national laboratories at the University of California Office of the President, seeking to foster long-term academic partnerships and provide UC faculty members with funding and Lab support for their research. The winning recipient will receive up to $1 million in funding over five years to support an innovative research project in the fields of artificial intelligence (AI) and machine learning (ML).

Gus winning research proposal, titled Toward AI-driven additive manufacturing for metal-ceramic composite structures, seeks to develop new composite materials with exceptional properties, particularly in ultra-high-temperature ceramics for energy and defense applications. The project will focus on advancing the capabilities of binder jet 3D printing and optimizing composite feedstock development. This work is strategically aligned with applied data science efforts in materials and advanced manufacturing at LLNL.

With technical support from LLNL research staff, Gu and her team plan to integrate AI algorithms for in-situ monitoring and parameter optimization of 3D printing and create a generative design framework for heterogeneous composite structures. By combining metals and ceramic-based materials, the research focuses on achieving specific mechanical properties that were previously unattainable through traditional manufacturing methods. This ambitious undertaking will employ cutting-edge AI and ML techniques, including neural network surrogate models and deep learning, to achieve its objectives.

“Dr. Gu’s research not only pushes the boundaries of materials science but also exemplifies the spirit of our sustained partnership between the University of California, dedicated to propelling innovation and nurturing the next generation of scientific leaders,” said Brad Wallin, LLNL deputy director for Strategic Deterrence. “I look forward to the great research and collaborations that will ensue.

The proposed research promises to advance AI-driven manufacturing technologies while providing opportunities for workforce development, student enrichment and community outreach, Wallin said. The initiative allows LLNL technical researchers to engage directly with the winning project, further strengthening the collaboration between the two institutions.