tno tpd tno science and industry, 12 may 20051 simulation of processing influence of secondary...

TNO Science and Industry, 12 May 2005

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TNO TPD

Simulation of processingInfluence of secondary electron statistics

More Moore SP3WP6.4


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Simulations of processing

• Rough aerial image in resist represented with white noise• PEB acid diffusion represented by ‘blurring’ edge outward• Subsequent etch represented by ‘blurring’ edge inward

DPS 2004, Leunissen et al.


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Animation of acid diffusion 0 to 10 nm


• High frequency components mitigated by acid diffusion


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Animation of acid diffusion 0 to 30 nm


• Decrease of high frequency components reduces total

spectral power


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• Simulation matches shape familiar from typical

experimental results

Power Spectrum

y ~ x-1.46

1 10 100 1000

litho(30nm)

white noise edge


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Animation of etch 0 to 30 nm


• Not so much influence on spectral power since high

frequency components are already ‘blurred away’


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• LER decreases during etch, but it depends on amount of

LER that is already ‘blurred away’ during acid diffusion

0

25

50

75

100

0 2 4 6 8 10LER 3 [nm]

CD

etc

h bi

as [

nm]

40nm30nm20nm


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h < 20 eV h > 20 eV

Statistics of secondary electrons

• Secondary electron blur• Super-Poissonian noise

• DUV lithography: pure photochemistry• EUV lithography: secondary electron generation


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• Model predicting SE blur from excitations, ionizations,

plasmon loss and elastic scattering (MNE 2004)

• Mean number of chemical activation events: AE 3

• (S. Tagawa: 1~3 e.g. MNE 2004)"single photon noise"

0 5 10 15

# chemical excitation events

MC simulation

Poisson distributionAE=3.2


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• Resist sensitivity according to the ITRS Litho Roadmap

EUV: 2 – 15 mJ/cm2 1.4 – 10 /nm2 • Shot noise induced dose variation can be reduced using

higher dose• Statistics in chemical activation events leads to “effective

dose variations”:

For AE=2, effective dose variations have to be compensated

with 50% higher dose


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Determination of dose induced LER

3.00

4.00

5.00

6.00

7.00

8.00

9.00

0.200 0.300 0.400 0.500 0.600 0.700 0.800

exposure dose [arb. units]

unco

rrre

late

d LE

R [n

m]

Measurement

Poisson model

vary dose / line width

526

528

530

532

534

536

0 200 400 600 800 1000i

Yi

• Need high contrast and good dose control: preferably MET


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Experimental artifacts

• Environmental vibrations• Source uniformity (temporal)

• Source uniformity (spatial)• Optics / mask errors

• CD measurement

• Resist contrast

repeat exposures with different illumination time; source characteristics

repeat with different masks

repeat CD measurements

repeat exposures with different resist contrast


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Procedure to correct for artifacts

• Line edge Yi,j = Ai + Bj + Ei,j• i is index of photo• j is index of line within a photo• A is measure for variation due to SEM imaging• B is measure for variation due to mask error, source uniformity• E is measurement error and shot noise

• E = dose dependent noise + residual noise• This elaborate procedure proves necessary at the desired

extreme sensitivities, to discriminate true shot noise from

experimental artifacts


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Experimental setup• Multiple CDs on mask• Multiple gratings• Multiple wafer positions• Multiple illuminations• Multiple photon energies (for SE blur measurement)• Multiple CD SEM imaging

CD

redundancymask errorsmultiple illumination

wafer / PEB variations


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Summary

• Transfer of LER during etch better understood• Additional effective “dose variation” due to statistics in

chemical activation possible point of concern• Determination of dose induced high frequency LER could

be seriously hampered by experimental artifacts

tno tpd tno science and industry, 12 may 20051 simulation of processing influence of secondary...

Documents

effective dose variations

good dose control

high frequency ler

nmanimation of acid

white noisepeb acid

true shot noise

source uniformitye

measurement error