2020/05/31 by Sheng Mao, Milena Chakraverti-Wuerthwein, Milena S. Chakraverti-Wuerthwein +3
Engineering · Materials Science · Mathematics · Physics and Astronomy · #Chemical physics #Combinatorics #Computer science #Crystallization and Solubility Studies #Function (biology) #Geology #Geometry #Innovative Microfluidic and Catalytic Techniques Innovation #Materials science #Mathematics #Morphology (biology) #Phase (matter) #Physics #Process Optimization and Integration #Quantum mechanics #Ranging #Statistical physics #Surface (topology) #Topology (electrical circuits) #cond-mat.soft
paper · pdf · doi:10.1103/physrevlett.125.218003
published as Phys. Rev. Lett. 125, 218003 (2020) · 6 pages, 4 figures + Supplemental Material (5 pages, 4 figures). Videos available at http://www.princeton.edu/~akosmrlj/papers/phase_separation_design/videos/
arxiv created 2020/06/11 · openalex publication_date 2020/11/19 · arxiv updated 2020/11/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Phase separation of multicomponent liquid mixtures plays an integral part in many processes ranging from industry to cellular biology. In many cases the morphology of coexisting phases is crucially linked to the function of the separated mixture, yet it is unclear what determines the morphology when multiple phases are present. We developed a graph theory approach to predict the topology of coexisting phases from a given set of surface energies, enumerate all topologically distinct morphologies, and reverse engineer conditions for surface energies that produce the target morphology.