Benchmark Computation of Morphological Complexity in the Functionalized Cahn-Hilliard Gradient Flow

Reductions of the self-consistent mean field theory model of amphiphilic molecule in solvent leads to a singular family of Functionalized Cahn-Hilliard (FCH) energies. We modify the energy, removing singularities to stabilize the computation of the gradient flows and develop a series of benchmark problems that emulate the morphological complexity observed in experiments. These benchmarks investigate the delicate balance between the rate of arrival of amphiphilic materials onto an interface and least energy mechanism to accommodate the arriving mass. The result is a trichotomy of responses in which two-dimensional interfaces grow by a regularized motion against curvature, pearling bifurcations, or curve-splitting directly into networks of interfaces. We evaluate second order predictor-corrector time stepping schemes for spectral spatial discretization. The schemes are based on backward differentiation that are either Fully Implicit, with Preconditioned Steepest Descent (PSD) solves for the nonlinear system, or linearly implicit with standard Implicit-Explicit (IMEX) or Scalar Auxiliary Variable (SAV) approaches to the nonlinearities. All schemes use fixed local truncation error to generate adaptive time-stepping. Each scheme requires proper preconditioning to achieve robust performance that can enhance efficiency by several orders of magnitude. The nonlinear PSD scheme achieves the smallest global discretization error at fixed local truncation error, however the IMEX scheme is the most computationally efficient as measured by the number of Fast Fourier Transform calls required to achieve a desired global error. The performance of the SAV scheme performance mirrors IMEX, at roughly half the computational efficiency.