Defectivity prediction for droplet-dispensed UV nanoimprint lithography, enabled by fast simulation of resin flow at feature, droplet, and template scales

Hayden K. Taylor

doi:10.1117/12.2218757

22 March 2016 Defectivity prediction for droplet-dispensed UV nanoimprint lithography, enabled by fast simulation of resin flow at feature, droplet, and template scales

Hayden K. Taylor

Author Affiliations +

Proceedings Volume 9777, Alternative Lithographic Technologies VIII; 97770E (2016) https://doi.org/10.1117/12.2218757
Event: SPIE Advanced Lithography, 2016, San Jose, California, United States

Abstract

Full-field, physically-based simulation of nanoimprint lithography (NIL) is needed to address the throughput-versus-yield challenges that are currently faced by NIL. We demonstrate a simulation framework that can track the spreading and coalescence of tens of thousands of picoliter-volume resin droplets beneath a nanoimprint template, predicting evolution of feature filling and residual layer thickness (RLT) uniformity during the imprinting of geometrically complex designs such as found in solid-state memory. We have used the framework to explore directionality of droplet spreading beneath patterned templates, the role of template curvature in mitigating gas entrapment, and detrimental elastic deflections at wafer-edge partial imprint fields.

Citation Download Citation

Hayden K. Taylor "Defectivity prediction for droplet-dispensed UV nanoimprint lithography, enabled by fast simulation of resin flow at feature, droplet, and template scales", Proc. SPIE 9777, Alternative Lithographic Technologies VIII, 97770E (22 March 2016); https://doi.org/10.1117/12.2218757

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