Physics-Informed Learning Machines for Multiscale and Multiphysics Problems

An image of various science-based visuals rolling out from a film reel labeled "philms."

(Image courtesy of Cortland Johnson | Pacific Northwest National Laboratory)

The PhILMs ("films") Center is a collaboration among Pacific Northwest National Laboratory and Sandia Laboratories, with academic partners at Brown University, Massachusetts Institute of Technology, Stanford University, and the University of California, Santa Barbara.

PhILMs is uncovering hidden physics based on new developments in deep learning, a computing technique that harnesses the power of machine learning and big data.

PhILMs investigators are developing physics-informed learning machines by encoding physics knowledge into deep learning networks to:

  • Design functional materials with tunable properties.
  • Solve longstanding problems in combustion, subsurface and earth systems, all exhibiting scaling cascades.
  • Establish probabilistic scientific computing as a new discipline at the interface of computational mathematics, multifidelity data, information fusion, and deep learning.

This work is supported by the Applied Mathematics Program within the U.S. Department of Energy Office of Advanced Scientific Computing Research.

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Awards and Recognition

De Yoreo and Karniadakis Elected to the National Academy of Engineering

The two researchers are among the 111 new members elected in 2022.

Karniadakis interviewed for deeponet features in quanta magazine and

George Em Karniadakis talks about his DeepONet research in two new articles from Quanta Magazine and TechXplore.