  Given the facts of the extensiveness of multi-material diffusion problems and
the inability of the standard PINN(Physics-Informed Neural Networks) method for
such problems, in this paper we present a novel PINN method that can accurately
solve the multi-material diffusion equation. The new method applies continuity
conditions at the material interface derived from the property of the diffusion
equation, and combines the distinctive spatial separation strategy and the loss
term normalization strategy to solve the problem that the residual points
cannot be arranged at the material interface, the problem that it is difficult
to express non-smooth functions with a single neural network, and the problem
that the neural network is difficult to optimize the loss function with
different magnitudes of loss terms, which finally provides the available
prediction function for a class of multi-material diffusion problems. Numerical
experiments verify the robustness and effectiveness of the new method.
