(109b) Integration of experiment and computation towards design of block copolymers materials for use in the directed self-assembly (DSA) of high-resolution lithographic patterns

Methodologies and tools for the accelerated discovery and design of materials for use in manufacturing have been transformed over the past decade through the combination and integration of experiment, theory, and computation. Here we build on the integration of experiment and molecular simulation to specify design rules for block copolymer (BCP) materials for use in the directed self-assembly (DSA) of ultra-high resolution lithographic patterns for semiconductor manufacturing. Fundamental properties of block copolymers (BCPs) that determine performance in directed self-assembly (DSA) applications include the Flory-Huggins interaction parameter, the degree of polymerization, and the surface energy and etch selectivity of blocks. These properties are co-varying, and the optimized balance in properties will be different at each resolution and for each application such as DSA plus EUV lithography compared to DSA plus 193i lithography. Here we report a high throughput strategy to mix and match components in (A-block-(B-random-C)) architectures to create libraries of BCPs from which materials can be selected for each different resolution and degree of feature density multiplication.