Year: 2025
Type: article
Abstract: Block copolymer (BCP) self-assembly - neat, or in a homopolymer/second BCP containing molecular blend - enables complex nanostructures including spherical micelles, co-continuous cubic gyroids and Frank-Kasper phases. Emergent properties in metallic and high entropy alloys inspire a paradigm shift: treating chemically distinct BCP micelles as functional building blocks to pave a path for multicomponent assemblies with molecularly engineered property profiles. Slowing current progress are challenges associated with the structural characterization of such BCP assemblies with poor atomic contrast. Here, we demonstrate how film surface self-assemblies of binary and ternary BCP micelle alloys can be phase inverted to generate porosity. This, combined with machine-learning assisted image segmentation, allows component classification via routine scanning electron microscopy. Results are supported by mechanistic insights from Voronoi analysis, cluster analysis and Monte Carlo/Brownian Dynamics simulations, revealing rich and controllable non-equilibrium surface structural behavior. Such multicomponent materials are expected to enable emergent properties for a range of applications.
Source: Nature Communications
Institution: Cornell University
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,990
Awards: G1134277896, G1647655023, G1836977401, G1957224027, G2415270547, G3631263731, Cornell Center for Materials Research - MRSEC, G5253097061, G5917061246, Graduate Research Fellowship Program (GRFP), G6311559428, Graduate Research Fellowship Program (GRFP), Block Copolymer Based Multicomponent Self-assembly of Porous Nanostructures From Non-equilibrium Processes, MRI: Acquisition of a Cryogenic Probe and Modern Console for Outstanding NMR Sensitivity to Benefit Research and Education at Cornell University, G8229174675, G8389919011, Mesophase Engineering through Coarse-to-fine Grained Modeling
OpenAlex ID: W4416177149