Process Optimization for Manufacturing Functional Nanosurfaces by Roll-to-Roll Nanoimprint Lithography.

Area of Science:

• Materials Science and Engineering
• Nanotechnology
• Chemical Engineering

Background:

• Roll-to-roll nanoimprint lithography (RTR-NIL) offers a cost-effective method for large-area functional film fabrication.
• Incomplete ultraviolet (UV) resin filling presents a significant bottleneck in continuous RTR-NIL processes.
• Developing precise control over UV resin flow is crucial for successful mass production.

Purpose of the Study:

• To develop and validate a multiphase numerical model for simulating UV resin filling in RTR-NIL.
• To investigate the influence of various processing parameters on the resin filling efficiency.
• To provide insights for optimizing the mass production of nanopatterned functional surfaces.

Main Methods:

• A multiphase numerical model incorporating a sliding mesh method was developed.
• The Volume of Fluid (VOF) scheme was employed to compute resin filling dynamics.
• Open-channel (OC) boundary conditions were used to simulate environmental conditions during filling.
• Numerical simulations were validated against experimental results.

Main Results:

• The numerical model accurately captures the phenomena of imprint mold rotation and UV resin feeding.
• Key processing parameters including imprinting speed, contact angles, viscosity, substrate thickness, and supporting roll diameter were analyzed.
• The study achieved good agreement between simulated and experimental outcomes, confirming model validity.

Conclusions:

• The proposed numerical model provides a powerful tool for understanding and optimizing UV resin filling in RTR-NIL.
• This research facilitates the mass production of functional surfaces with nanopillar and nanopore patterns for diverse industrial applications.
• The findings contribute to advancing the efficiency and scalability of RTR-NIL technology.