Blending Linear and Cyclic Block Copolymers to Manipulate Nanolithographic Feature Dimensions

Area of Science:

• Polymer Science
• Materials Science
• Nanotechnology

Background:

• Block copolymers (BCPs) self-assemble into nanoscale structures for applications in photonics, membranes, and nanolithography.
• Cyclic BCPs theoretically offer smaller features and improved stability compared to linear analogs.
• Challenges in synthesizing pure cyclic BCPs hinder large-scale manufacturing.

Purpose of the Study:

• To investigate the self-assembly behavior of cyclic/linear BCP blends using simulations.
• To evaluate the impact of blend composition on nanofeature size and interfacial width.
• To explore the potential of BCP blends for advanced nanolithography applications.

Main Methods:

• Dissipative particle dynamics simulations were employed to model BCP blend self-assembly.
• Analysis focused on nanofeature dimensions and interfacial width critical for nanopatterning.
• Simulated domain spacings were compared against strong segregation theory predictions.

Main Results:

• Mixtures of symmetric cyclic and linear BCPs showed minimal impact on feature dimensions and roughness with up to 10% impurity.
• Blending cyclic BCPs with linear BCPs enables fine-tuning of feature sizes.
• Significant deviations from strong segregation theory were observed due to molecular packing effects.

Conclusions:

• Cyclic/linear BCP blends offer a viable strategy for controlling nanofeature size in nanopatterning.
• The presence of cyclic BCPs in blends minimally affects performance even with impurities.
• Simulation insights provide a foundation for designing BCP materials for next-generation nanolithography.