Area-selective atomic layer deposition (AS-ALD) is a promising "bottom-up" alternative to current nanopatterning techniques. Self-assembled monolayers (SAM) have been successfully employed as deactivating agents to achieve AS-ALD. In this work, the formation of octadecylphosphonic acid (ODPA) SAMs is studied on four technologically important metal substrates: Cu, Co, W, and Ru. The SAM quality is shown to be dependent on temperature, solvent, and the nature of the substrate. The blocking ability of the ODPA-treated substrates is evaluated using ZnO and Al 2 O 3 model ALD processes. Spectroscopic analyses reveal that ODPA-assisted ALD blocking can be achieved to varying degrees of success on each metal. ODPAprotected W showed >90% selectivity after 32 nm ZnO and 8 nm Al 2 O 3 ALD, exhibiting the best blocking overall. For all substrates, ZnO ALD proved consistently easier to block than Al 2 O 3 , indicating the importance of precursor chemistry. Additionally, we show that the self-correcting process previously reported for Cu using an acetic acid etchant can be extended to Co. This process improves selective deposition of Al 2 O 3 on patterned Co/SiO 2 with feature sizes as small as 25 nm. Additional studies reveal that feature size and density affect the apparent selectivity in SAM-based AS-ALD, highlighting the importance of such considerations in future process developments.
Area-selective atomic layer deposition (AS-ALD) is attracting increasing interest because of its ability to enable both continued dimensional scaling and accurate pattern placement for next-generation nanoelectronics. Here we report a strategy for depositing material onto three-dimensional (3D) nanostructures with topographic selectivity using an ALD process with the aid of an ultrathin hydrophobic surface layer. Using ion implantation of fluorocarbons (CFx), a hydrophobic interfacial layer is formed, which in turn causes significant retardation of nucleation during ALD. We demonstrate the process for Pt ALD on both blanket and 2D patterned substrates. We extend the process to 3D structures, demonstrating that this method can achieve selective anisotropic deposition, selectively inhibiting Pt deposition on deactivated horizontal regions while ensuring that only vertical surfaces are decorated during ALD. The efficacy of the approach for metal oxide ALD also shows promise, though further optimization of the implantation conditions is required. The present work advances practical applications that require area-selective coating of surfaces in a variety of 3D nanostructures according to their topographical orientation.
For
years, many efforts in area selective atomic layer deposition
(AS-ALD) have focused on trying to achieve high-quality self-assembled
monolayers (SAMs), which have been shown by a number of studies to
be effective for blocking deposition. Herein, we show that in some
cases where a densely packed SAM is not formed, significant ALD inhibition
may still be realized. The formation of octadecylphosphonic acid (ODPA)
SAMs was evaluated on four metal substrates: Cu, Co, W, and Ru. The
molecular orientation, chain packing, and relative surface coverage
were evaluated using near-edge X-ray absorption fine structure (NEXAFS),
Fourier transform infrared (FTIR) spectroscopy, and electrochemical
impedance spectroscopy (EIS). ODPA SAMs formed on Co, Cu, and W showed
strong angular dependence of the NEXAFS signal whereas ODPA on Ru
did not, suggesting a disordered layer was formed on Ru. Additionally,
EIS and FTIR spectroscopy confirmed that Co and Cu form densely packed,
“crystal-like” SAMs whereas Ru and W form less dense
monolayers, a surprising result since W-ODPA was previously shown
to inhibit the ALD of ZnO and Al2O3 best among
all the substrates. This work suggests that multiple factors play
a role in SAM-based AS-ALD, not just the SAM quality. Therefore, metrological
averaging techniques (e.g., WCA and FTIR spectroscopy) commonly used
for evaluating SAMs to predict their suitability for ALD inhibition
should be supplemented by more atomically sensitive methods. Finally,
it highlights important considerations for describing the mechanism
of SAM-based selective ALD.
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