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Explores the use of Green functions for solving electrostatic problems with different boundary conditions, emphasizing the importance of choosing the correct function.
Explores atomic descriptors, emphasizing symmetry, locality, and the challenges of incorporating electrostatics in machine learning models for chemistry.
