Modeling the interaction of EUV radiation with photoresist materials from first principles
K. D. Closser1‡ and D. Prendergast1
M. Ahmed3, P. D. Ashby1, S. Bhattarai2, O. Kostko3, Y. Liu1, D. F. Ogletree1, D. L . Olynick1, D. Slaughter3, B. Xu3, P. Naulleau2
1The Molecular Foundry, 2Center for X-Ray Optics, 3Chemical Sciences Division; Lawrence Berkeley National Laboratory‡[email protected]
1
Background
Photolithography is widely used in industry for transferring patterns to silicon
chips
Smaller features are desirable due to lower energy requirements and faster
response times
As the feature size is proportional to the wavelength, shorter wavelengths are
required to reach smaller features while avoiding the extra cost associated with
multiple patterning and extra processing
• Current industrial standard (UV): 193 nm (6.4 eV)
• Next generation sources (EUV): 13.5 nm (92 eV)
High energy EUV radiation interacts with both valence and semi-core electrons
Excitation of these tightly bound electrons may result in fundamentally different
chemistry and potentially result in selective bond breaking
Challenges associated with EUV
• Low optical cross-section for
standard organic photoresists
• # photons/energy unit much
smaller requiring greater
efficiency per photon
• Secondary electrons can
damage material over a large
radius
Need materials with better
controlled chemistry, and larger
cross-sections to improve
efficiency and make new
technology viable for industry
Fig: Illustration of photolithography
with a positive tone resist.
Fig: Absorption cross-section at 92 eV, with halogens and atoms in organic resists highlighted
Project Goals
1. Increase fundamental understanding of EUV interaction with matter using calculations from first principles
• Compute properties of model resist materials such as photon absorption, electron energy loss and Auger emission
• Use molecular dynamics to investigate potential chemistry
• Combine results to create probabilistic model
2. Propose and develop new photoresist materials using insights gained
Acknowledgements
This research was supported by the Laboratory Directed Research and Development Program of Lawrence Berkeley National
Laboratory (LBNL) under U.S. Department of Energy Contract No. DE-AC02-05CH11231
Optical Absorption (Step 1)
Fig: Optical absorption of CH3X (X= H, OH, F, Cl, Br, I)
Fig: Valence and semi-core orbital
energies for CH3X
Compute vertical excitation energies at ground state
geometries (Born-Oppenheimer approximation)
Low energy valence and deep core excitations readily
computed with standard time-dependent density functional
theory (TDDFT)
Not practical when many states are required and valence
electrons can not be neglected; the Lanczos method is used
and does not require explicit computation of excited states
Increased absorption at EUV energies for F and OH due to
presence of deeper valence levels causing slow decay of
valence peak
For I the increased absorption is
primarily due to 4d electron
excitations (Br has similar behavior
but peaks near 200 eV)
At 92 eV absorption is primarily
atomic, but intensity for I is
underestimated
Difference between gas and
normalized condensed phase
absorption is minimal
Fig: Comparison of TDDFT results with
experiment (Chem. Phys. 232, 1998, 211)
Fig: Optical absorption of condensed phase methyl phenols
for two local minima A, B
Fig: Optical absorption of gas phase methyl phenols
XMePh (X= H, F, Cl, Br, I)
Approach
Fig: Cartoon representation of dominant events occurring in EUV
absorption and subsequent electronic and nuclear relaxation.
Consider dominant processes in initial absorption,
electronic relaxation and chemical changes
independently
Use density functional theory (DFT) to compute
electronic structure, including time-dependent DFT for
EUV absorption and electron energy loss spectra
Potential dissociation channels determined through
initial forces and ab initio molecular dynamics
Begin with organic resist model systems:
• Methane, methanol and halogenated methanes for
validation of the methodology (compare to existing
experiment)
• Use halogenated methyl phenols as models for
polymeric organic resists
• Investigate gas phase first and then shift to models
for a condensed phase system
Fig: Representation of timescales of processes
relevant to EUV excitation and decay.
Fig: Example of random block copolymer organic photoresist and monomers used in synthesis (J.
Photopolym. Sci. Tech, 7, 1994, 433) and substituted phenol model (X = H, F, Cl, Br, I)Fig: Condensed phase model with
relaxed geometry
Electronic Scattering (Step 2b)
Fig: Electron energy loss (EEL) for methyl phenols
Compute structure factor for information about electron decay
Most effective energy loss for methyl phenols ~10-35 eV higher and
lower energy electrons more likely to diffuse further
Selecting for electrons most likely to lose energy quickly may provide
a method to limit blur
Strongly dependent on momentum transfer, interpretation for gas
phase is unclear
Future Work
Secondary Electron Generation (Step 2a) High Throughput Screening Monte Carlo Modeling
Auger decay produces dications emits secondary
electrons at specific kinetic energies
Fig: Representation
of screening
process for
new resist
materialsFig: Various Auger processes showing formation of
dications (b), (c), (d) and trications (e), (f), (g)
Determine methodology
to effectively screen for
novel materials
Chemical Rearrangement (Step 3)
Fig: Initial forces for CH3I after ionization from semi-core or valence orbitals
Use initial forces and emptied orbitals to screen for
states that may undergo rearrangement
Use ab initio molecular dynamics to determine potential
products
Fig: Ionization from bonding valence orbital (15b) leads to C-I dissociation
timeFig: Initial forces for IMePh from formation of I (4d)
(a) cation and (b) valence dication
(a) (b)
Probabilistic evaluation of
electron decay pathways
Determination of important
charged species for further study
Fig: Possible pathways for hole
formation and decay
Recommended
