Autonomous discovery of emergent morphologies in directed self-assembly of block copolymer blends

Doerk, Gregory S.; Stein, Aaron; Bae, Suwon; Noack, Marcus M.; Fukuto, Masafumi; Yager, Kevin G.

doi:10.1126/sciadv.add3687

Title: Autonomous discovery of emergent morphologies in directed self-assembly of block copolymer blends

Journal Article · Fri Jan 13 00:00:00 EST 2023 · Science Advances

DOI:https://doi.org/10.1126/sciadv.add3687· OSTI ID:1922720

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^[1]; Bae, Suwon ^[1];

^[2]; Fukuto, Masafumi ^[3];

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Brookhaven National Laboratory (BNL), Upton, NY (United States). Center for Functional Nanomaterials (CFN)
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Brookhaven National Laboratory (BNL), Upton, NY (United States). National Synchrotron Light Source II (NSLS-II)

The directed self-assembly (DSA) of block copolymers (BCPs) is a powerful approach to fabricate complex nanostructure arrays, but finding morphologies that emerge with changes in polymer architecture, composition, or assembly constraints remains daunting because of the increased dimensionality of the DSA design space. Here, we demonstrate machine-guided discovery of emergent morphologies from a cylinder/lamellae BCP blend directed by a chemical grating template, conducted without direct human intervention on a synchrotron x-ray scattering beamline. This approach maps the morphology-template phase space in a fraction of the time required by manual characterization and highlights regions deserving more detailed investigation. These studies reveal localized, template-directed partitioning of coexisting lamella- and cylinder-like subdomains at the template period length scale, manifesting as previously unknown morphologies such as aligned alternating subdomains, bilayers, or a “ladder” morphology. This work underscores the pivotal role that autonomous characterization can play in advancing the paradigm of DSA.

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Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: SC0012704; AC02-05CH11231

OSTI ID:: 1922720

Alternate ID(s):: OSTI ID: 2293525

Report Number(s):: BNL-223938-2023-JAAM

Journal Information:: Science Advances, Vol. 9, Issue 2; ISSN 2375-2548

Publisher:: AAASCopyright Statement

Country of Publication:: United States

Language:: English

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