Optimized design of block copolymers with covarying properties for nanolithography

Hongbo Feng, Moshe Dolejsi, Ning Zhu, Soonmin Yim, Whitney Loo, Peiyuan Ma, Chun Zhou, Gordon S.W. Craig, Wen Chen, Lei Wan, Ricardo Ruiz, Juan J. de Pablo, Stuart J. Rowan, Paul F. Nealey

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

The ability to impart multiple covarying properties into a single material represents a grand challenge in manufacturing. In the design of block copolymers (BCPs) for directed self-assembly and nanolithography, materials often balance orthogonal properties to meet constraints related to processing, structure and defectivity. Although iterative synthesis strategies deliver BCPs with attractive properties, identifying materials with all the required attributes has been difficult. Here we report a high-throughput synthesis and characterization platform for the discovery and optimization of BCPs with A-block-(B-random-C) architectures for lithographic patterning in semiconductor manufacturing. Starting from a parent BCP and using thiol–epoxy ‘click’ chemistry, we synthesize a library of BCPs that cover a large and complex parameter space. This allows us to readily identify feature-size-dependent BCP chemistries for 8–20-nm-pitch patterns. These blocks have similar surface energies for directed self-assembly, and control over the segregation strength to optimize the structure (favoured at higher segregation strengths) and defectivity (favoured at lower segregation strengths).

Original languageEnglish
Pages (from-to)1426-1433
Number of pages8
JournalNature Materials
Volume21
Issue number12
DOIs
StatePublished - Dec 2022

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