Engineering the Kinetics of Directed Self-Assembly of Block Copolymers Toward Fast and Defect-Free Assembly.

Directed self-assembly (DSA) of block copolymers (BCPs) can achieve perfectly aligned structures at thermodynamic equilibrium, but the self-assembling morphology can become kinetically trapped in defective states. Understanding and optimizing the kinetic pathway toward domain alignment is crucial for enhancing process throughput and lowering defectivity to levels required for semiconductor manufacturing, but there is a dearth of experimental, three-dimensional studies of the kinetic pathways in DSA. Here, we combined arrested annealing and TEM tomography to probe the kinetics and structural evolution in the chemoepitaxy DSA of PS-b-PMMA with density multiplication. During the initial stages of annealing, BCP domains developed independently at first, with aligned structures at the template interface and randomly oriented domains at the top surface. As the grains coarsened, the assembly became cooperative throughout the film thickness and a metastable stitch morphology was formed, representing a kinetic barrier. The stitch morphology had a three-dimensional structure comprised of both perpendicular and parallel lamellae. Based on the mechanistic information, we studied the effect of key design parameters on the kinetics and evolution of structures in DSA. Three types of structural evolutions were observed at different film thicknesses: 1) immediate alignment and fast assembly when thickness < L0 (L0 = BCP natural periodicity); 2) formation of stitch morphology for 1.25 - 1.45L0; 3) fingerprint formation when thickness > 1.64L0. We found that the DSA kinetics can be significantly improved by avoiding the formation of the metastable stitch morphology. Increasing template topography also enhanced the kinetics by increasing the PMMA guiding surface area. A combination of 0.75L0 BCP thickness and 0.50L0 template topography achieved perfect alignment over 100 times faster than the baseline process. This research demonstrates that an improved understanding of the evolution of structures during DSA can significantly improve the DSA process.