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P Ventzek December 2003MOTOROLA and the Stylized M Logo are registered in the US Patent & Trademark Office. All other product or service names are the property of their respective owners. © Motorola, Inc. 2002.
Integration of Modeling and Simulation into Process Development
P.L.G. VentzekS. RaufP.J. Stout
Northern California AVS Section Joint • Plasma Etch Users Group • Thin Films Users Group
Meeting
AGENDA
• Perspective on how modeling and simulation fit as a value propositions in the semiconductor industry.
• Computational process integration– Process integration tool-kit at Motorola– Plasma Chemistry– Surfaces
• FEOL Example• BEOL Example
Simulation and the Manufacturing Life-Cycle
• New Materials– New devices and new materials. Understanding material behavior
dependencies on unit processes. – “Materials science calculations”
• Concept and Feasibility– Tool design and the mating of tools to next technology nodes– “Equipment simulation”
• New Product Development– Unit process development– Process integration – “Linked equipment and feature scale models”
• Manufacturing– Yield enhancement, troubleshooting– “Calibrated models”
• Re-use
Turn-key Models
SpecializedModels
Barriers to Integration of Modeling and Simulation into Development Culture
• Credibility and timeliness issues– Late results, replication vs. truly predictive
• Not quantitative enough• Undersized development groups in industry and university
– Downsize of traditional research sources– Small nature of many end users of M&S
• Communication gap between interested parties: chip makers, vendors
• Communication gap between funding agencies that would fund research , researchers and “customers”.
Means to Integration of Modeling and Simulation into Development Culture
• Focus on predictive work (as much as possible)• Strive to be quantitative – no corner cutting from
fundamental physics data to tool details.• Critical mass group or extended group• As much as possible, engage vendors in joint projects• Take an international view regarding research partners
• Aim where need is greatest: integration.– Point process studies while insight providing have limited value
add potential.– The ensemble of unit processes or process integration is
our view of where impact is greatest.
Process Integration
Unit Process ModelA
Feature Scale ModelA
Unit Process Model B
Feature Scale ModelB
Unit Process ModelC
Feature Scale ModelC
Unit Process Model D
Feature Scale ModelD
Yield Enhancement andSuperior Reliability, Electrical Performance
Materials Science Models
Concept Flow/Device
Sequences of unit process models threaded together can replicate what is observed on Silicon.
Computational Integration Tool Kit
• Models for most commercial tools (AMAT, Lam, TEL) developed in-house.
• Plasma chemistry database assembled through internal computational environment.
• Plasma-surface interaction database developed through internal and external efforts.
• In-house simulations for both chamber and feature scale simulations.
Computational Infrastructure
• Following codes have been utilized for the studies reported here:– IO:1 2-d fluid model for capacitive plasma simulation,– HPEM:2 2-d fluid model for inductive plasma simulation,– Papaya:1 3-d Monte Carlo based feature scale model.
1Motorola; 2University of Illinois
IO HPEM
Papaya
Reactor GeometryOperating Conditions
Plasma Chemistry
Feature Profile
Surface Chemistry
Species FluxesEnergy/Angular Distributions
Reactor GeometryOperating Conditions
Initial Profile
Electron Impact Processes In SF6 Plasmas
SF5 SF5+
SF4+SF4
SF3 SF3+
SF2 SF2+
SF SF+
5
F
SF5 SF4
SF3 SF2 SF S
SF6
F-
SF5-
SF6-
SF5+
SF3+
1
2 3
4
Needed to be calculated!
Processes (4) were calculated by us in 2000 to be bale to optimize critical deep Sietch processes used for e-beam lithography.
C4F6 Plasma Chemistry in Detail
C4F6 + e
+ eNeutral dissociation
+ 2e
[C4F6-] Attachment
Ionization C3F3+, C4F6
+, CF+, C3F4+,
C3F2+, C4F5
+, CF3+, C4F4
+,C2F2
+, C3F+, CF2+
C4F6
C3F4
C4F5
C2F3
CF2
C2F2 C3F3CF
C4F4
C3F2
C4F3
C2F
C, F, C2
Not only electron impact processes for the parent but also the plethora of radicals present in the system must be considered.
Neutral Dissociation Processes in C5F8 plasmas
c-C5F8
C5F7
Direct dissociation
C5F8 Isomerization
C5F8
Ringopening,
FCF2 C2F3
CF C2F2C2F4+ C4F6
Previously calculated data
3
4
5 1
2
Like C4F8 which is cyclic, the cross-sections depend on the bond that opens and where the electron hits.
e.g., Co reduced energy level scheme“Effective”
Relevant Metastable Short-LivedLevels Levels Levels
Ta >300 4 4Fe >480 6 4Co >320 3 4Ni >200 3 4Sn >100 4 3Mg >80 1 3B >40 1 3
Metallization: Complex Excited State Plasma Chemistry
By Product: Data for Plasma Diagnostics
929.06
931.38
942.62
905.48
938.73
0
1
2
3
4
5
6
7
1100 1000 900 800 700
938.03
Wavenumber (cm-1)
Inte
nsity
Synthetic, RuO3
Synthetic, RuO4
Synthetic, RuO
Synthetic, RuO2
Experimental, suspect RuO4
Experimental, unknown feature
FTIR spectra/cross section study for RuOx Etch:
Plasma-Surface Interactions
• We are using molecular dynamics following the approach of Graves and Hamaguchi to develop plasma-surface interaction datasets.
Crystal Passivated with CF2
+ IonsCrystal with Polymer
Layer
Red – Si, blue – oxygen, light gray – F, dark gray - C
Plasma-Surface Interactions: Thermal Processes• Very complex problem!• We seek relative sticking coefficients and reactions and try to cover a large
parameter space using quantum chemistry calculations and small clusters. The final arbiter on these parameters is ultimately comparison of feature scale predictions with experiment.
SiO2
CFx
Direct barrierlessreactions
SiO2
CFx
Transition state
( )θγ −= 1s
Plasma-Surface Interactions: Yields
• An example of macroscopic parameters that are inserted into our models. This constitutes a part of an ever-evolving array of species-surface parameters.
Si atoms removed per incident CF2+ ion
0 10 20 30 40 50 60 70 80 90θ , degrees
Si/C
F 2
E = 50 eVE = 150 eVE = 300 eV
Plasma-Surface Interactions: Kinetics• Example angular and energy distribution functions for SiF associated with
polymer bombardment. Both are needed for feature scale simulations. Understanding the energetics of ejected species (even apart from their nature) is important for the thermal and chemical properties of the plasma.
0
0.01
0.02
0.03
0 10 20 30 40 50 60 70 80 90θ, degrees
0
0.05
0.1
0.15
0.2
0.25
0.3
0 2 4 6 8 10 12 14 16 18 2Ek, eV
Dry Etch Achievements- Transistors
• At the heart of a CMOS transistor’s performance is the gate patterning process. Product requirements demand innovative patterning techniques which produce gate lengths far smaller than the theoretical limits of lithography wavelengths.
Supernominal, nominal, and subnominal Poly-Si lines patterned with conventional 193nm lithography, and etched down to <20nm Lpoly. Gate dielectric is <13Å oxynitride.
Supernominal, nominal, and subnominal Poly-Si lines patterned with conventional 193nm lithography, and etched down to <20nm Lpoly. Gate dielectric is <13Å oxynitride.
Supernominal
Nominal
Subnominal
Top-down
Advent of novel structures and new materials brings huge challenges
FEOL Computational Integration
• Calculated (w/ Papaya) evolution of an SRAM gate after 7 etch steps.• Shown here is an over aggressive trim blows out the gates. These would
be dealt with through lithographic adjustments or etch engineering.
trim oeARCinitial
PRARC poly Si oxide
Applications to Process Development for Novel Devices
An example of fin process step gone awry!
Computational Process Integration (FEOL)MASK
LITHOGRAPHY-ST-LITH
TRIM ETCH-PAPAYA
Ma s
k-to
-Etc
h ed
F eat
ure
P re d
i ct io
n s
Ma s
k M
anu f
a ct u
re a
nd D
e si g
n0 nm
500 nm
Initial Height500 nm 200 nm
time
Example of Trim Etch for Different Initial Resist Heights
Dry Etch Achievements- Interconnect
• Advanced technologies bring a new host of challenges in interconnect processing: more metallization layers using novel materials, dual-inlaid metallization integrations for cost savings, as well as further shrinking of the feature dimensions.
Motorola’s HiPerMOS7 SOI product features nine levels of metal utilizing low-K dielectrics, implementing dual-inlaid processing at every layer.
Motorola’s HiPerMOS7 SOI product features nine levels of metal utilizing low-K dielectrics, implementing dual-inlaid processing at every layer.
Etch-Metallization Integration: Text-book view
Dual-inlaid structure with straight side-walls and well defined sidewall angles. Fill is as-expected.
Scaling for idealized cases is well defined as a function of via side-wall angle and aspect ratio.
BUT!
No resputter
sputter
BEOL Computational Integration
Less polymerizing chemistry vs More polymerizing chemistry
bow
Larger open area
Smalleropen area
BEOL Computational Integration
PhotoresistBARC
cap
dielectricetch stop
metalvia mask BARC etch via etch
trench mask Slug etch
trench etch ash
• See Next Slide
First Stab at BT Process from Vendor
• Slow etch that attacks PRdimension.
• Lost sidewall (CD) cannot be recovered in subsequent steps!
• 7 degrees of freedom.
Wide CD-190 nm before even breaking through.
Photoresist (PR)
BARC
TEOS (BT or Breakthrough)
Photoresist at 224 nm
SiCOH (Main Etch)
Subsequently ashed away
CuCap
Two Tools - Two Processes
5.0
0.0
Hei
ght (
cm)
Radius (cm)0.0 21.8
[CF2] (Max = 2.1 × 1011 cm-3)5.0
0.0
Hei
ght (
cm)
Radius (cm)0.0 21.8
[CF2] (Max = 2.1 × 1011 cm-3)
TEOS Etch in Tool A
21.70.00.0
12.0
Hei
ght (
cm)
Radius (cm)
[CF3] (Max = 9.2×1011 cm-3)
21.70.00.0
12.0
Hei
ght (
cm)
Radius (cm)
[CF3] (Max = 9.2×1011 cm-3)
TEOS Etch in Tool B
PR
BARC
TEOS
“Polymer”
O2 mix and pressure varied
Gas Mix, Power and Gap Varied
Suggested path
Minimum oxygenReplicates Tool B process best.
O2 in Process Critical to CD Control
TEOS etch rate slows PR eroded
Experimental Verification
Slow
Poor CDsSlowDemonstrates
O2 need
Needs Ar and more polymerOptimal
Summary
• Fundamentals based simulations can and do have an engineering impact in unit process and process integration development.
• The physics, chemistry and materials interactions problems remain complex but are tractable enough to warrant tackling theminside the semiconductor manufacturing industry.
• Developmental activities remain critical to making the leap to “predictive” simulation and fulfilling the promise of simulation adding value.