Asymptotics of non-minimizing stationary points of the Ohta-Kawasaki energy and its sharp interface version

TL;DR

This paper investigates the asymptotic behavior of non-minimizing stationary points of the non-local Ohta-Kawasaki energy in higher dimensions, revealing uniform distribution and droplet shape regularity under certain conditions.

Contribution

It extends the analysis of stationary points for the Ohta-Kawasaki energy to higher dimensions, establishing force balance and droplet regularity results.

Findings

Stationary points satisfy a force balance condition.

Minority phase distributes uniformly in the majority phase.

Droplets become asymptotically round in 2D with finite number and bounded isoperimetric deficit.

Abstract

We study a non-local Cahn-Hilliard energy arising in the study of di-block copolymer melts, often referred to as the Ohta-Kawasaki energy in that context. In this model, two phases appear, which interact via a Coulombic energy. As in our previous work, we focus on the regime where one of the phases has a very small volume fraction, thus creating "droplets" of the minority phase in a "sea" of the majority phase. In this paper, we address the asymptotic behavior of non-minimizing stationary points in dimensions $n \geq 2$ left open by the study of the $\Gamma$-convergence of the energy established in [23]-[24], which provides information only for almost minimizing sequences when $n=2$. In particular, we prove that (asymptotically) stationary points satisfy a force balance condition which implies that the minority phase distributes itself uniformly in the background majority phase. Our proof uses and generalizes the framework of Sandier-Serfaty [36,37], used in the context of stationary points of the Ginzburg-Landau model, to higher dimensions. When $n=2$, using the regularity results obtained in [25], we also are able to conclude that the droplets in the sharp interface energy become asymptotically round when the number of droplets is constrained to be finite and have bounded isoperimetric deficit.