Fig. 1. Photoresist exposure process and origin of EUV stochastics in different lithography processes
Fig. 2. Differences between traditional and stochastic failures
[5]. (a) Stochastic failures; (b) traditional types of defects
Fig. 3. Scheme showing the radiation chemistry mechanisms of EUV resists
[14-15] Fig. 4. Absorption cross sections of elements (
Z=1‒86) at EUV
[24] Fig. 5. Line-edge roughness (LER) values after the entire CAR patterning process in low
Tg and high
Tg[85]. (a) LER as a function of the protected site ratio
fp when the number of beads
N=64; (b) LER as a function of the number of beads
N at fixed
fp=0.5; (c) 3D image of residual polymer from (a) for low
Tg resist; (d) 3D image of residual polymer from (b) for low
Tg resist
Fig. 6. Sequence controlled resists based on polypeptoid
[86]. (a) Scheme showing monomer structures and polymer sequence; (b) patterns produced from polypeptoid of different sequences under DUV exposure
Fig. 7. Concept and lithographic results of novel functionalized materials
[74] Fig. 8. Defect analysis for BQ variation
[75]. (a) Total post litho defect density with e-beam; (b) nanobridge defect density; (c) line break defect density
Fig. 9. Process flow of PTD (positive-tone development) and NTI (negative-tone imaging) lithography
[89-90] Fig. 10. Process windows for line/space between EUV PTD and EUV NTD
[92] Fig. 11. Distribution of light intensity on high reflective substrate and a baking step smoothens this concentration pattern by diffusion (from the left to the right shows the chronological sequence of a numerical modelling)
[94] Fig. 12. Simulation results of LCDU (3
σ) variation of 20 nm half pitch (HP) dense hole pattern with cluster diameter (same imaging conditions)
[95] Fig. 13. Schematic of the fully coupled Monte Carlo simulation for calculating reaction distributions in resist films
[120] Fig. 14. Stochastic effect analysis based on Monte Carlo method
[15,120]. (a) Monte Carlo simulated photon adsorption (red ball), secondary electron generation (blue ball), and acid-induced deprotection reaction (green dot) in DUV and EUV CAR; (b) probability model of the stochastic effect for statistical analysis
Fig. 15. Framework of the multiscale computation simulation model
[124]. (a) Density functional theory (DFT), molecular dynamics (MD), and finite difference method (FDM) combined computational study of the exposure process of EUV photoresist materials; (b) simulating the effect of PEB time on exposed morphology
Name | Structure | Formula | Density / (g·cm-3) | Calculated linear absorption coefficient /μm-1 | Measured linear absorption coefficient /μm-1 |
---|
PMMA | | C5H8O2 | 1.18 | 5.19 | 5.03 | PNB | | C7H10 | 0.92 | 2.55 | 2.58 | PSt | | C8H8 | 1.05 | 2.95 | 2.70 | PHOSt | | C8H8O | 1.16 | 4.05 | 3.88 | PTMSSt | | C11H16Si | 1.14 | 2.78 | 2.14 | PMPS | | C7H8Si | 1.12 | 2.60 | 2.82 | PPSSQ | | C24H20Si4O4 | 1.50 | 4.52 | 4.45 | PAF | | C15H14O3F12 | 1a | 6.97 | 10.75 |
|
Table 1. Structure, density and linear absorption coefficient of selected polymers
[23]