Puurunen (on behalf of Järvilehto) oral presentation at ALD 2023 conference

Puurunen and coworkers, ALD 2023, Jul 23-26, 2023, Bellevue, Washington
Jänis Järvilehto, Jorge A. Velasco, Jihong Yim, Christine Gonsalves,
Riikka L. Puurunen
Aalto University, School of Chemical Engineering,
Department of Chemical and Metallurgical Engineering
Simulated Conformality of
ALD Growth Inside
Lateral HAR Channels:
Comparison Between a
Diffusion–Reaction Model
and a Ballistic Transport–
Reaction Model
ALD 2023, July 23-26, 2023, Bellevue,
Washington, USA Järvilehto et al., submitted, in ChemRxiv (2023),
https://doi.org/10.26434/chemrxiv-2023-bnzgr-v2
DR BTR
θ
x = x/H
~
1
AUDIO: https://aalto.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=0fec7dbe-fedf-41de-a576-b06901010532

Conformality: core advantage of ALD
and source of kinetic information
Arts et al., Chem. Mater. 33 (2021) 5002–5009.
https://doi.org/10.1021/acs.chemmater.1c00781
Miikkulainen et al., J. Appl. Phys. 113 (2013)
021301
https://doi.org/10.1063/1.4757907. Continued
at: https://www.atomiclimits.com/alddatabase/
PillarHallTM
Ylilammi et al. J. Appl. Phys. 123, 205301 (2018)
https://doi.org/10.1063/1.5028178
Arts et al., J. Vac. Sci. Tech. A 37,
030908 (2019)
https://doi.org/10.1116/1.5093620
θ
x
~
2

Model B: Machball
Ballistic transport–reaction (BTR) model
Two models,
two sets of fundamentals
Model A: DReaM-ALD
Diffusion–reaction (DR) model
Ylilammi et al.1,2 Yanguas-Gil & Elam3
GPC ∝ q = s0
-1
https://github.com/aldsim/machball
https://github.com/Aalto-
Puurunen/dream-ald
[1] Ylilammi et al., J. Appl. Phys. 123 (2018) 205301.
[2] Yim & Verkama et al., Phys. Chem. Chem. Phys. 24 (2022) 8645–8660.
[3] Yanguas-Gil & J.W. Elam, Theor. Chem. Acc. 133 (2014) 1465.
“macroscopic vs. microscopic”
“chemical engineering vs. physics”
Langmuir adsorption
3

Comparison
conditions
Variable Unit DR BTR Baseline
value
Varied
I. Temperature K T T 573 373-773
II. Reactant
pressure
Pa pA0 p 10 1-20
III. Molar mass kg/mol MA m 0.1 0.05-0.25
IV. Aspect ratio - L/H AR H 0.5 µm*
AR 1000**
H 0.125-2 µm
AR 250-4000
V. Pulse time s tend tc 1 0.01-10
VI. Sticking
coefficient
- c 0 10-3 1 to 10-5
VII.  GPC (nm) q, nm-2 s0, nm2 4, 0.25 0.5-8, 0.125-2
VIII. Exposure
(constant)
pA0, tend p, tc 10 Pa &
1 s
0.08-50 Pa &
0.2-125 s
Knudsen number >>1
Thiele modulus >1
*500 nm typical for PillarHallTM (pillarhall.com). **L kept constant at 500 µm.
θ
x = x/H
~
4

Parameter comparison 1
I. Temperature T, T III. Molar mass of reactant MA, m
II. Partial pressure of reactant pA0, p IV. Aspect ratio L/H, AR
DR
DR
DR
DR
BTR
BTR
BTR
BTR
5

Parameter comparison 1
I. Temperature T, T III. Molar mass of reactant MA, m
II. Partial pressure of reactant pA0, p IV. Aspect ratio L/H, AR
DR
DR
DR
DR
BTR
BTR
BTR
BTR
Differences: slope,
penetration, BTR: trunk
6
✕

Note: Effect of
increasing
simulation
resolution
DR: smoothness improves BTR: shape changes
All simulations presented for
BTR model are with relative
no. of discretization
segments of four (4)
 = ratio of no. of
discretization points or
segments to the AR
H = 0.5 µm, L =
(a,b) 500 µm
(c,d) 1000 µm.
7

Parameter comparison 2/2
V. Exposure time tend, tc VII. ∝ 1/(GPC) q, s0
VI. Sticking coefficient c, 0 VIII. Constant exposure pA0 ✕ tend, p ✕ tc
DR
DR
DR
DR
BTR
BTR
BTR
BTR
8

Comparison
summary
Half-coverage penetration depth |Slope| at half coverage
DR < BTR
0.66 ✕
DR > BTR
1.6-4.2✕
θ
x = x/H
~
9
BTR BTR
DR
DR

Conclusion
● DR and BTR models ~qualitatively
agree, except for trunk
● In BTR model, resolution affects results
● DR and BTR models show quantitative
differences
● Penetration
● slope
● Quantitative differences would lead to
different sticking coefficients when using
a fitting method
θ
x = x/H
~
DR BTR
10

Acknowledgements
Financial support:
● Academy of Finland (renamed: Research Council of
Finland):
ALDI consortium, decision no. 331082 and
COOLCAT consortium, decision no. 329978
● Prof. Puurunen’s starting grant at Aalto University
Personal: Emma Verkama, Aleksi Heikkinen,
Angel Yanguas-Gil, Andreas Werbrouck, Aada
Illikainen
Computational resources: Aalto Science IT-project
https://www.youtube.com/@riikkapuurunen9993/videos
https://www.slideshare.net/RiikkaPuurunen/presentations
(Moodle) https://openlearning.aalto.fi/course/view.php?id=100 →ALD
https://research.aalto.fi/en/persons/riikka-puurunen
Chapter on ALD (2021) in Kirk-Othmer:
https://doi.org/10.1002/0471238961.ko
e00059
Many images with CC
license in Wikimedia Commons
11

Simulated Conformality of ALD Growth Inside Lateral HAR Channels: Comparison Between a Diffusion–Reaction Model and a Ballistic Transport–Reaction Model
Jänis Järvilehto,1 Jorge A. Velasco,1 Jihong Yim,1 Christine Gonsalves1 and Riikka L. Puurunen1
1Aalto University, School of Chemical Engineering, Department of Chemical and Metallurgical Engineering
Atomic layer deposition (ALD) is known for its ability to produce films of controllable thickness, even in narrow, high-aspect-ratio (HAR) structures [1]. These films can be highly
conformal, meaning that the structure is covered by a film of uniform thickness [1,2]. However, when the structure’s aspect ratio is increased sufficiently, deposition becomes
limited by the diffusion of the reactants into the deep end of the structure, potentially resulting in the formation of an adsorption front, followed by a region of lower coverage [3].
Theoretical models have been developed to predict film conformality in HAR structures, as reviewed in [2].
This work presents a comparison of a diffusion–reaction model (DRM) developed by Ylilammi et al. [4,5] (Model A) and a ballistic transport–reaction model (BTRM) by
Yanguas-Gil and Elam [6,7] (Model B). For the comparison, saturation profiles were generated using both models with similar simulation parameters (Knudsen number Kn >>
1).
Qualitatively, both models produced similar trends in terms of half-coverage penetration depth and slope at half-coverage penetration depth. The saturation profiles were similar
in shape, except for the film growth observed at the channel end in Model B. Quantitative examination yielded consistently higher half-coverage penetration depths in Model B.
Model A produced steeper slopes at half-coverage penetration depth. In Model B, the discretization resolution was found to affect the penetration depth.
While the models gave qualitatively similar results, quantitatively extracted parameters differed. This finding is consistent with a previous comparison of a DRM and BTRM in
the context of low pressure chemical vapor deposition [8]. The quantitative differences are relevant, for example, when the models are fitted to experimental data for the
extraction of kinetic parameters, such as the sticking coefficient.
References
[1] J.R. van Ommen, A. Goulas, and R.L. Puurunen, “Atomic layer deposition,” in Kirk Othmer Encyclopedia of Chemical Technology, John Wiley & Sons, Inc., 42 p, (2021).
[2] V. Cremers et al., Appl. Phys. Rev. 6 (2019) 021302.
[3] J. Yim and O.M.E. Ylivaara et al., Phys. Chem. Chem. Phys. 22 (2020) 23107-23120.
[4] M. Ylilammi et al., J. Appl. Phys. 123 (2018) 205301.
[5] J. Yim and E. Verkama et al., Phys. Chem. Chem. Phys. 24 (2022) 8645–8660.
[6] A. Yanguas-Gil and J.W. Elam, Theor. Chem. Acc. 133 (2014) 1465.
[7] A. Yanguas-Gil and J.W. Elam, (2013) https://github.com/aldsim/machball, accessed Feb 13 2023.
[8] M.K. Jain et al., J. Electrochem. Soc. 140 (1993) 242-247.
ABSTRACT,
ALD
2023
12

Original artwork
by RLP 2023
13

Puurunen (on behalf of Järvilehto) oral presentation at ALD 2023 conference

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