scholarly journals Area-Selective Deposition of Ruthenium by Area-Dependent Surface Diffusion

2020 ◽  
Author(s):  
Fabio Grillo ◽  
Job Soethoudt ◽  
Esteban A. Marques ◽  
Lilian de Martin ◽  
Kaat Van Dongen ◽  
...  
Keyword(s):  
Surface Diffusion ◽  
Surface Composition ◽  
Kinetic Monte Carlo ◽  
Chemical Vapor ◽  
Fold Increase ◽  
Atomic Layer ◽  
Selective Deposition ◽  
Layer Deposition ◽  
Kinetic Monte Carlo Simulations ◽  
Precursor Molecules

<div> <div> <p>Area-selective deposition (ASD) enables the growth of materials on target regions of patterned substrates for applications in fields ranging from microelectronics to catalysis. Selectivity is often achieved through surface modifications aimed at suppressing or promoting the adsorption of precursor molecules. Here we show, instead, that varying the surface composition can enable ASD by affecting surface diffusion rather than adsorption. Ru deposition from (carbonyl)- (alkylcyclohexadienyl)Ru and H<sub>2</sub> produces smooth films on metal nitrides and nanoparticles on SiO<sub>2</sub>. The latter form by surface diffusion and aggregation of Ru adspecies. Kinetic modeling shows that changing the surface termination of SiO<sub>2</sub> from -OH to -CH<sub>3</sub>, and thus its surface energy, leads to larger and fewer nanoparticles because of a 1000-fold increase in surface diffusion rates. Kinetic Monte Carlo simulations show that even surface diffusion alone can enable ASD because adspecies tend to migrate from high- to low-diffusivity regions. This is corroborated by deposition experiments on 3D TiN-SiO<sub>2</sub> nanopatterns, which are consistent with Ru migrating from SiO<sub>2</sub> to TiN. Such insights not only have implications for the interpretation of experimental results but may also inform new ASD protocols, based on chemical vapor and atomic layer deposition, that take advantage of surface diffusion.</p></div></div>

scholarly journals Area-Selective Deposition of Ruthenium by Area-Dependent Surface Diffusion

2020 ◽  
Author(s):  
Fabio Grillo ◽  
Job Soethoudt ◽  
Esteban A. Marques ◽  
Lilian de Martin ◽  
Kaat Van Dongen ◽  
...  
Keyword(s):  
Surface Diffusion ◽  
Surface Composition ◽  
Kinetic Monte Carlo ◽  
Chemical Vapor ◽  
Fold Increase ◽  
Atomic Layer ◽  
Selective Deposition ◽  
Layer Deposition ◽  
Kinetic Monte Carlo Simulations ◽  
Precursor Molecules

<div> <div> <p>Area-selective deposition (ASD) enables the growth of materials on target regions of patterned substrates for applications in fields ranging from microelectronics to catalysis. Selectivity is often achieved through surface modifications aimed at suppressing or promoting the adsorption of precursor molecules. Here we show, instead, that varying the surface composition can enable ASD by affecting surface diffusion rather than adsorption. Ru deposition from (carbonyl)- (alkylcyclohexadienyl)Ru and H<sub>2</sub> produces smooth films on metal nitrides and nanoparticles on SiO<sub>2</sub>. The latter form by surface diffusion and aggregation of Ru adspecies. Kinetic modeling shows that changing the surface termination of SiO<sub>2</sub> from -OH to -CH<sub>3</sub>, and thus its surface energy, leads to larger and fewer nanoparticles because of a 1000-fold increase in surface diffusion rates. Kinetic Monte Carlo simulations show that even surface diffusion alone can enable ASD because adspecies tend to migrate from high- to low-diffusivity regions. This is corroborated by deposition experiments on 3D TiN-SiO<sub>2</sub> nanopatterns, which are consistent with Ru migrating from SiO<sub>2</sub> to TiN. Such insights not only have implications for the interpretation of experimental results but may also inform new ASD protocols, based on chemical vapor and atomic layer deposition, that take advantage of surface diffusion.</p></div></div>

scholarly journals Area-Selective Deposition of Ruthenium by Area-Dependent Surface Diffusion

2020 ◽  
Author(s):  
Fabio Grillo ◽  
Job Soethoudt ◽  
Esteban A. Marques ◽  
Lilian de Martin ◽  
Kaat Van Dongen ◽  
...  
Keyword(s):  
Surface Diffusion ◽  
Surface Composition ◽  
Kinetic Monte Carlo ◽  
Chemical Vapor ◽  
Fold Increase ◽  
Atomic Layer ◽  
Selective Deposition ◽  
Layer Deposition ◽  
Kinetic Monte Carlo Simulations ◽  
Precursor Molecules

<div> <div> <p>Area-selective deposition (ASD) enables the growth of materials on target regions of patterned substrates for applications in fields ranging from microelectronics to catalysis. Selectivity is often achieved through surface modifications aimed at suppressing or promoting the adsorption of precursor molecules. Here we show, instead, that varying the surface composition can enable ASD by affecting surface diffusion rather than adsorption. Ru deposition from (carbonyl)- (alkylcyclohexadienyl)Ru and H<sub>2</sub> produces smooth films on metal nitrides and nanoparticles on SiO<sub>2</sub>. The latter form by surface diffusion and aggregation of Ru adspecies. Kinetic modeling shows that changing the surface termination of SiO<sub>2</sub> from -OH to -CH<sub>3</sub>, and thus its surface energy, leads to larger and fewer nanoparticles because of a 1000-fold increase in surface diffusion rates. Kinetic Monte Carlo simulations show that even surface diffusion alone can enable ASD because adspecies tend to migrate from high- to low-diffusivity regions. This is corroborated by deposition experiments on 3D TiN-SiO<sub>2</sub> nanopatterns, which are consistent with Ru migrating from SiO<sub>2</sub> to TiN. Such insights not only have implications for the interpretation of experimental results but may also inform new ASD protocols, based on chemical vapor and atomic layer deposition, that take advantage of surface diffusion.</p></div></div>

scholarly journals Area-Selective Deposition of Ruthenium by Area-Dependent Surface Diffusion

2020 ◽  
Author(s):  
Fabio Grillo ◽  
Job Soethoudt ◽  
Esteban A. Marques ◽  
Lilian de Martin ◽  
Kaat Van Dongen ◽  
...  
Keyword(s):  
Surface Diffusion ◽  
Surface Composition ◽  
Kinetic Monte Carlo ◽  
Chemical Vapor ◽  
Fold Increase ◽  
Atomic Layer ◽  
Selective Deposition ◽  
Layer Deposition ◽  
Kinetic Monte Carlo Simulations ◽  
Precursor Molecules

<div> <div> <p>Area-selective deposition (ASD) enables the growth of materials on target regions of patterned substrates for applications in fields ranging from microelectronics to catalysis. Selectivity is often achieved through surface modifications aimed at suppressing or promoting the adsorption of precursor molecules. Here we show, instead, that varying the surface composition can enable ASD by affecting surface diffusion rather than adsorption. Ru deposition from (carbonyl)- (alkylcyclohexadienyl)Ru and H<sub>2</sub> produces smooth films on metal nitrides and nanoparticles on SiO<sub>2</sub>. The latter form by surface diffusion and aggregation of Ru adspecies. Kinetic modeling shows that changing the surface termination of SiO<sub>2</sub> from -OH to -CH<sub>3</sub>, and thus its surface energy, leads to larger and fewer nanoparticles because of a 1000-fold increase in surface diffusion rates. Kinetic Monte Carlo simulations show that even surface diffusion alone can enable ASD because adspecies tend to migrate from high- to low-diffusivity regions. This is corroborated by deposition experiments on 3D TiN-SiO<sub>2</sub> nanopatterns, which are consistent with Ru migrating from SiO<sub>2</sub> to TiN. Such insights not only have implications for the interpretation of experimental results but may also inform new ASD protocols, based on chemical vapor and atomic layer deposition, that take advantage of surface diffusion.</p></div></div>

scholarly journals Influence of the Geometric Parameters on the Deposition Mode in Spatial Atomic Layer Deposition: A Novel Approach to Area-Selective Deposition

Coatings ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 5 ◽  
Author(s):  
César Masse de la Huerta ◽  
Viet Nguyen ◽  
Jean-Marc Dedulle ◽  
Daniel Bellet ◽  
Carmen Jiménez ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Atomic Layer Deposition ◽  
Chemical Vapor ◽  
Atomic Layer ◽  
Dynamics Simulation ◽  
Selective Deposition ◽  
Temporal Separation ◽  
Present Contribution ◽  
Chemical Vapor Deposition Growth ◽  
Layer Deposition

Within the materials deposition techniques, Spatial Atomic Layer Deposition (SALD) is gaining momentum since it is a high throughput and low-cost alternative to conventional atomic layer deposition (ALD). SALD relies on a physical separation (rather than temporal separation, as is the case in conventional ALD) of gas-diluted reactants over the surface of the substrate by a region containing an inert gas. Thus, fluid dynamics play a role in SALD since precursor intermixing must be avoided in order to have surface-limited reactions leading to ALD growth, as opposed to chemical vapor deposition growth (CVD). Fluid dynamics in SALD mainly depends on the geometry of the reactor and its components. To quantify and understand the parameters that may influence the deposition of films in SALD, the present contribution describes a Computational Fluid Dynamics simulation that was coupled, using Comsol Multiphysics®, with concentration diffusion and temperature-based surface chemical reactions to evaluate how different parameters influence precursor spatial separation. In particular, we have used the simulation of a close-proximity SALD reactor based on an injector manifold head. We show the effect of certain parameters in our system on the efficiency of the gas separation. Our results show that the injector head-substrate distance (also called deposition gap) needs to be carefully adjusted to prevent precursor intermixing and thus CVD growth. We also demonstrate that hindered flow due to a non-efficient evacuation of the flows through the head leads to precursor intermixing. Finally, we show that precursor intermixing can be used to perform area-selective deposition.

scholarly journals 2D Semiconductor Nanomaterials and Heterostructures: Controlled Synthesis and Functional Applications

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Hongyan Xu ◽  
Mohammad Karbalaei Akbari ◽  
Serge Zhuiykov
Keyword(s):  
Liquid Metals ◽  
Chemical Vapor ◽  
Atomic Layer ◽  
First Century ◽  
2D Semiconductors ◽  
Layer Deposition ◽  
Semiconductor Nanomaterials ◽  
2D Nanomaterials ◽  
Novel Applications ◽  
Electronic Technologies

AbstractTwo-dimensional (2D) semiconductors beyond graphene represent the thinnest stable known nanomaterials. Rapid growth of their family and applications during the last decade of the twenty-first century have brought unprecedented opportunities to the advanced nano- and opto-electronic technologies. In this article, we review the latest progress in findings on the developed 2D nanomaterials. Advanced synthesis techniques of these 2D nanomaterials and heterostructures were summarized and their novel applications were discussed. The fabrication techniques include the state-of-the-art developments of the vapor-phase-based deposition methods and novel van der Waals (vdW) exfoliation approaches for fabrication both amorphous and crystalline 2D nanomaterials with a particular focus on the chemical vapor deposition (CVD), atomic layer deposition (ALD) of 2D semiconductors and their heterostructures as well as on vdW exfoliation of 2D surface oxide films of liquid metals.

Facile rearrangement of molecular layer deposited metalcone thin films by electron beam irradiation for area selective atomic layer deposition

2021 ◽  
Author(s):  
Seunghwan Lee ◽  
GeonHo Baek ◽  
Hye-mi Kim ◽  
Yong-Hwan Kim ◽  
Jin-Seong Park
Keyword(s):  
Thin Films ◽  
Electron Beam ◽  
Atomic Layer Deposition ◽  
Electron Beam Irradiation ◽  
Molecular Layer ◽  
Atomic Layer ◽  
Beam Irradiation ◽  
Selective Deposition ◽  
Layer Deposition ◽  
Amorphous Structures

Metalcone films can be rearranged from amorphous structures to 2D-like carbon by electron beam irradiation. The irradiated indicone (HQ) film can be used as an inhibitor for selective deposition delaying 20 cycles of ALD of ZnO.

scholarly journals Kinetic Monte Carlo Study of the Atomic Layer Deposition of Zinc Oxide

2018 ◽  
Vol 122 (47) ◽  
pp. 27044-27058 ◽  
Author(s):  
Timo Weckman ◽  
Mahdi Shirazi ◽  
Simon D. Elliott ◽  
Kari Laasonen
Keyword(s):  
Monte Carlo ◽  
Zinc Oxide ◽  
Atomic Layer Deposition ◽  
Kinetic Monte Carlo ◽  
Monte Carlo Study ◽  
Atomic Layer ◽  
Layer Deposition

scholarly journals Atomic layer deposited V2O5 coatings: a promising cathode for Li-ion batteries

2019 ◽  
Vol 10 (1) ◽  
pp. 21-28
Author(s):  
Martyn Pemble ◽  
Ian Povey ◽  
Dimitra Vernardou
Keyword(s):  
Vanadium Pentoxide ◽  
Coulombic Efficiency ◽  
Lithium Ion ◽  
Chemical Vapor ◽  
Atomic Layer ◽  
Deposition Process ◽  
Chemical Vapor Deposition Growth ◽  
Layer Deposition ◽  
Specific Discharge ◽  
Cathodic And Anodic Processes

A modified, thermal atomic layer deposition process was employed for the pulsed chemical vapor deposition growth of vanadium pentoxide films using tetrakis (dimethylamino) vanadium and water as a co-reagent.Depositions were carried out at 350oC for 400 pulsed CVD cycles, and samples were subsequently annealed for 1hour at 400°C in air to form materials with enhanced cycling stability during the continuous lithium-ion intercala­tion/deintercalation processes. The diffusion coefficient was estimated to be 2.04x10-10 and 4.10x10-10 cm2 s-1 for the cathodic and anodic processes, respectively. These values are comparable or lower than those reported in the literature, indicating the capability of Li+ of getting access into the vanadium pentoxide framework at a fast rate. Overall, it presents a specific discharge capacity of 280 mAh g-1, capacity retention of 75 % after 10000 scans, a coulombic efficiency of 100 % for the first scan, dropping to 85 % for the 10000th scan, and specific energy of 523 Wh g-1.

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