Funding
We appreciate financial support from the National Science Foundation and Department of Energy.
National Science Foundation, Chemical Theory, Models and Computational Methods 20 22-2024
"EAGER: ADAPT: Machine learning thermodynamic speed limits for dynamic materials"
"EAGER: ADAPT: Machine learning thermodynamic speed limits for dynamic materials"
National Science Foundation, Dynamics, Control and Systems Diagnostics 2021-2024
"Speed limits on pattern formation in dynamic materials"
"Speed limits on pattern formation in dynamic materials"
Department of Energy, Office of Basic Energy Sciences, Biomolecular Materials Program, 2023-2026
"Data-driven learning of dissipation from microscopy of chemically active materials" (Co-PI Joseph Patterson, University of California Irvine)
"Data-driven learning of dissipation from microscopy of chemically active materials" (Co-PI Joseph Patterson, University of California Irvine)