Both area selective atomic layer deposition (ALD) and area selective molecular layer deposition (MLD) are demonstrated on Cu/SiO 2 patterns using octadecylphosphonic acid (ODPA) self-assembled monolayers as a resist layer. X-ray photoelectron spectroscopy and Auger electron spectroscopy confirm that during a metal oxide ALD process, no growth occurs on ODPA-protected Cu, whereas the metal oxide grows on SiO 2 regions of the substrate, for up to 36 nm of metal oxide. The results also show that ODPA blocks the Cu surface from MLD, preventing polyurea deposition for up to 6 nm of film thickness.

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.

Titania thin film system containing noble metallic nanoparticles such as Au, Ag, and Cu have been prepared by utilizing radio frequency reactive magnetron cosputtering method. The structural and morphological properties of the thin films were characterized by X-ray diffraction (XRD) and atomic force microscopy (AFM). Surface chemical composition of the films was determined by X-ray photoelectron spectroscopy (XPS). Optical properties of the TiO2 annealed films containing Au, Ag, and Cu metallic nanoparticles were investigated by UV−visible spectrophotometry showing surface plasmon resonance of the metals. The photocatalytic activity of all synthesized samples annealed at 600 °C in an Ar + H2(80 + 20%) environment was evaluated by measuring the rate of photodegradation reaction of methylene blue (MB) under similar conditions in the presence of UV and visible light irradiation. The Au:TiO2 and Cu:TiO2 thin film systems significantly enhanced photodecomposition of MB resulting in 80 and 90% of its initial concentration after 200 min photoirradiation, respectively. The increase in the surface roughness measured by AFM observation and the presence of the Ti3+ oxygen vacancy in the photoirradiated thin films were found responsible for the enhancement of the MB photodegradation reaction. The photoenhancement of the studied was determined in the following order: Cu:TiO2 > Au:TiO2 > Ag:TiO2 > TiO2.

Next generation 3D electronic devices will require novel processing methods. Area selective atomic layer deposition (ALD) of robust films has the opportunity to play an important role in significantly reducing complexities associated with current top‐down fabrication processes of patterned structures. An all‐vapor process is demonstrated for depositing and regenerating thiol self‐assembled monolayers (SAMs) on copper between ALD cycles. It is shown that by redosing SAM precursors, the SAM quality can be restored after it begins to degrade. It is also shown that this approach is effective in improving the blocking properties of the SAMs against ZnO ALD. This process allows selective deposition of dielectric films on dielectric regions of patterned Cu/SiO2 substrates more than three times thicker than approaches that do not regenerate the SAM. In addition, this all‐vapor strategy provides the ability to integrate the selective deposition process into the ALD reactor, reduces artifacts associated with depositing the SAMs on porous or 3D structures, and decreases the required deposition time for the passivation layer, opening up the possibility for new applications in next generation electronic devices.

Nanoscale patterning of materials is widely used in a variety of device applications. Area selective atomic layer deposition (ALD) has shown promise for deposition of patterned structures with subnanometer thickness control. However, the current process is limited in its ability to achieve good selectivity for thicker films formed at higher number of ALD cycles. In this report, we demonstrate a strategy for achieving selective film deposition via a self-correcting process on patterned Cu/SiO2 substrates. We employ the intrinsically selective adsorption of octadecylphosphonic acid self-assembled monolayers on Cu over SiO2 surfaces to selectively create a resist layer only on Cu. ALD is then performed on the patterns to deposit a dielectric film. A mild etchant is subsequently used to selectively remove any residual dielectric film deposited on the Cu surface while leaving the dielectric film on SiO2 unaffected. The selectivity achieved after this treatment, measured by compositional analysis, is found to be 10 times greater than for conventional area selective ALD.

Area selective atomic layer deposition has the potential to significantly improve current fabrication approaches by introducing a bottom-up process in which robust and conformal thin films are selectively deposited onto patterned substrates. In this paper, we demonstrate selective deposition of dielectrics on metal/dielectric patterns by protecting metal surfaces using alkanethiol blocking layers. We examine alkanethiol self-assembled monolayers (SAMs) with two different chain lengths deposited both in vapor and in solution and show that in both systems, thiols have the ability to block surfaces against dielectric deposition. We show that thiol molecules can displace Cu oxide, opening possibilities for easier sample preparation. A vapor-deposited alkanethiol SAM is shown to be more effective than a solution-deposited SAM in blocking ALD, even after only 30 s of exposure. The vapor deposition also results in a much better thiol regeneration process and may facilitate deposition of the SAMs on porous or three-dimensional structures, allowing for the fabrication of next generation electronic devices.

Area selective molecular layer deposition (MLD) is a promising technique for achieving micro- or nanoscale patterned organic structures. However, this technique still faces challenges in attaining high selectivity, especially at large MLD cycle numbers. Here, we illustrate a new strategy for achieving high quality patterns in selective film deposition on patterned Cu/Si substrates. We employed the intrinsically selective adsorption of an octadecylphosphonic acid self-assembled monolayer (SAM) on Cu over Si surfaces to selectively create a resist layer only on Cu. MLD was then performed on the patterns to deposit organic films predominantly on the Si surface, with only small amounts growing on the Cu regions. A negative potential bias was subsequently applied to the pattern to selectively desorb the layer of SAMs electrochemically from the Cu surface while preserving the MLD films on Si. Selectivity could be enhanced up to 30-fold after this treatment.

We consider the context of "simulation-based recursions," that is, recursions that involve quantities needing to be estimated using a stochastic simulation. Examples include stochastic adaptations of fixed-point and gradient descent recursions obtained by replacing function and derivative values appearing within the recursion by their Monte Carlo counterparts. The primary motivating settings are Simulation Optimization and Stochastic Root Finding problems, where the low-point and the zero of a function are sought, respectively, with only Monte Carlo estimates of the functions appearing within the problem. We ask how much Monte Carlo sampling needs to be performed within simulation-based recursions in order that the resulting iterates remain consistent, and more importantly, efficient, where "efficient" implies convergence at the fastest possible rate. Answering these questions involves trading-off two types of error inherent in the iterates: the deterministic error due to recursion and the "stochastic" error due to sampling. As we demonstrate through a characterization of the relationship between sample sizing and convergence rates, efficiency and consistency are intimately coupled with the speed of the underlying recursion, with faster recursions yielding a wider regime of "optimal" sampling rates. The implications of our results to practical implementation are immediate since they provide specific guidance on optimal simulation expenditure within a variety of stochastic recursions.