1. Simulation of feature profile evolution for thin film processes involving simultaneous deposition and etching Nathan Marchack, Calvin Pham, John Hoang Prof. Jane P. Chang, University of California, Los Angeles
2010 Main Objectives
Essential Elements
Motivation
Back End of Line (BEOL)
Cu ionized PVD
Via etch: top view
Gas flow rate
Profile evolution
Plasma 3. Simulation of Feature Profile Evolution – Use experimental beam systems to measure the pertinent kinetics parameters (such as sticking and recombination coefficients and formulate reaction mechanisms) as well as reactor scale models (to determine plasma parameters, such as wafer flux and ionization fractions) to be incorporated into a Monte Carlo simulator to account for surface evolution, especially with competing etching/deposition processes
Expand kinetic database for profile evolution; validate using model systems: Cu IPVD & High-k etch in Cl2 containing chemistries
Henrik Schumacher, CMOS Chip Structure.
Singer, Peter, Semi. Int. 2008
Front end of Line (FEOL)
Current Generation MOSFET Structure
Selective High k Gate Etch
TEM Micrography of Current Generation High k Devices Si
SiO2
Poly
High k
After Poly Etch
After High k Etch
High k
NiSi, NiSi(Pt)
Porous Low k
Metal
Adapted from
Braun, A.E. Semi. Int. (2000)
Reactor scale model and PIC/analytical model provide fluxes, IED and IAD
Surface normal determines the direction of surface advancement
Translated mixed layer (TML) kinetics extracted from MD and beam data
Auth, C. et al. Intel Tech. Journal (2008)
Stringent control of feature shape and geometry as dimensions decrease
Lower process and development cost by predicting profile evolution
Method of Approach
Cu IPVD: Overview
Cu IPVD: Effect of Fluxes
Reactor scale flux ratios with varying power
SEM Courtesy of Novellus Systems
Total Ion Flux (Ar+ and Cu+) vs. Power
Vyas, V., Kushner, M. JVST A 24(5) 2006
Total Cu flux and ionization fraction vs. Power
HCM IPVD Reactor
Simulation Domain
Physics Models
Kinetic Models
Surface normal is calculated using polynomial fitting + q
Ion Scattering
Ar+ on Cu (111) 45° off normal scattering
Liu, X.-Y. et al. Thin Film Solids 422, 2002
Ion Etching
Cu+ Sputtering of Cu (111) Angular Dependence
Coronell et al. APL 73(26), 1998
Neutral Adsorption
Ion Adsorption
Physical Sputtering
Ion Induced Production
Spontaneous Removal by incoming C flux
Large bottom to top coverage ratio indicates high Cu ionization fraction
Singer, Peter. Semiconductor International 2002
10 kW Power
30 kW Power
50 kW Power
Sample simulations with flux ratios from above
High Neutral to Ion ratio results in very low bottom deposition
21% Cu+, 16% Cu 63% Ar, Eion = 25, sE = 10
11% Cu+, 33% Cu 56% Ar , Eion = 25, sE = 10
7% Cu+, 42% Cu 51% Ar , Eion = 25, sE = 10
Simulations with higher ionization ratios
75% Cu+, 20% Cu, 5% Ar+ Eion = 50, sE = 10
85% Cu+, 20% Cu, 5% Ar+, Eion = 50, sE = 10
Higher ionization ratio and energy yields higher bottom coverage and faceting
Top View
Vyas, V., Kushner, M. JVST A 24(5) 2006
The TML model allows for individual reactions to be modeled and provides information about the surface composition.
Robust model can easily incorporate complex kinetics and composition
Reactor scale model can be used to generate normalized flux ratios and ionization fractions that can be implemented to feature scale model
Cu IPVD: Effect of Ion Angle/Energy
Application of TML Model
Cu IPVD: Effect of TaN Barrier
SEM Courtesy of Novellus Systems
Cu IPVD Data
Sticking on sidewalls
No Sticking on sidewalls
Ar+ on Cu(111)
Cu+ on Cu(111)
Angular Dependencies of Ion etch yield Kress, J. D. et al. JVST A 17(5), 1999
Angular dependency
Angular dependent etching
Eion M B Cl O
Adsorption Flux
Removal Flux + +
Γion + + + +
Γneutral
Movement Flux
Faceting observed due to angle dependant etching
Perform experiments with selected materials and chemistry to obtain data.
Test parameter accuracy by comparing to surface composition data, etc.
Final verification involves using TML parameters in feature scale model and comparing profile evolution.
Increasing RF Power
Energy dependency
Increasing Energy (Flux ratio constant 75% Cu+, 20% Cu, 5% Ar+
E=15 eV, sE = 10
25 eV, sE = 10
35 eV, sE = 10
45 eV, sE = 10
Overhang from sputter
SEM Courtesy of Novellus Systems
Hoang et al. JVST B 26(8) 2008
SEM images show low sidewall deposition on TaN diffusion barrier layer, possibly as a result of lacking surface interactions with ions
Modeled profiles with and without sidewall sticking
The TML model is built from experimentally obtained data and allows for a realistic physical description of a process to be constructed.
Sticking coefficient and etch yield is a function of impact angle and energy
Compare Models in Etching Complex Oxide
Compare Models in Etching Complex Oxide
Future Goals
Continue to refine surface evolution algorithms in feature scale model
Apply more complicated Translated Mixing Layer kinetics in order to simulate feature profile evolution of high-k dielectric material
Special Acknowledgements
Herbert Sawin at MIT
Ron Kinder at Novellus
Goal 1
Goal 2
Eion M B Cl O
Adsorption Flux
Removal Flux
Eion M B Cl O
Adsorption Flux
Removal Flux + + + +
Γion + + + +
Γion + + + +
Γneutral
Γneutral
Movement Flux
Movement Flux
Balance Surface Sites
Translating Mixed Layer
Balance Surface Sites
Translating Mixed Layer
Funded by
For a Cl2 process dominated by etching, there is good agreement between the models.
For BCl3 chemistry, both etching and deposition regimes can be modeled.