Login / Signup

Spatial modulation of nanopattern dimensions by combining interference lithography and grayscale-patterned secondary exposure.

Zhuofei GanHongtao FengLiyang ChenSiyi MinChuwei LiangMenghong XuZijie JiangZhao SunChuying SunDehu CuiWen-Di Li
Published in: Light, science & applications (2022)
Functional nanostructures are exploited for a variety of cutting-edge fields including plasmonics, metasurfaces, and biosensors, just to name a few. Some applications require nanostructures with uniform feature sizes while others rely on spatially varying morphologies. However, fine manipulation of the feature size over a large area remains a substantial challenge because mainstream approaches to precise nanopatterning are based on low-throughput pixel-by-pixel processing, such as those utilizing focused beams of photons, electrons, or ions. In this work, we provide a solution toward wafer-scale, arbitrary modulation of feature size distribution by introducing a lithographic portfolio combining interference lithography (IL) and grayscale-patterned secondary exposure (SE). Employed after the high-throughput IL, a SE with patterned intensity distribution spatially modulates the dimensions of photoresist nanostructures. Based on this approach, we successfully fabricated 4-inch wafer-scale nanogratings with uniform linewidths of <5% variation, using grayscale-patterned SE to compensate for the linewidth difference caused by the Gaussian distribution of the laser beams in the IL. Besides, we also demonstrated a wafer-scale structural color painting by spatially modulating the filling ratio to achieve gradient grayscale color using SE.
Keyphrases
  • high throughput
  • machine learning
  • deep learning
  • air pollution
  • signaling pathway
  • high intensity
  • neural network
  • high resolution