Multiscale simulation of ion beam impacts on a graphene surface

Dybyspayeva, Kumiszhan; Zhuldassov, Abat; Ainabаyev, Ardak; Vyatkin, A.F.; Alekseev, K. P.; Insepov, Z.

doi:10.1088/1742-6596/751/1/012029

Cited by 4 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, a multiscale modeling approach has been proposed as a suitable compromise. This strategy is not new, as numerous of such models have already been developed and applied for different plasma processes [47][48][49][50][51][52][53][54]. Additionally, multiscale modeling of plasma-surface interaction has been discussed on a general level in the minireview by Schneider and the reviews by Most commonly, the standard simulation methods are classified according to the considered physical time and length scales.…”

Section: Multiscale Modeling -Coupling Classical and Quantum Mattermentioning

confidence: 99%

Multiscale modeling of plasma–surface interaction—General picture and a case study of Si and SiO2 etching by fluorocarbon-based plasmas

Vanraes

Venugopalan

Bogaerts

2021

Applied Physics Reviews

View full text Add to dashboard Cite

The physics and chemistry of plasma-surface interaction is a broad domain relevant to various applications and several natural processes, including plasma etching for microelectronics fabrication, plasma deposition, surface functionalization, nanomaterial synthesis, fusion reactors, and some astrophysical and meteorological phenomena. Due to their complex nature, each of these processes are generally investigated in separate subdomains, which are considered to have their own theoretical, modeling and experimental challenges. In this review, however, we want to emphasize the overarching nature of plasma-surface interaction physics and chemistry, by focusing on the general strategy for its computational simulation. In the first half of the review, we provide a menu card with standard and less standardized computational methods to be used for the multiscale modeling of the underlying processes. In the second half, we illustrate the benefits and potential of the multiscale modeling strategy with a case study of Si and SiO2 etching by fluorocarbon plasmas, and identify the gaps in knowledge still present on this intensely investigated plasma-material combination, both on a qualitative and quantitative level. Remarkably, the dominant etching mechanisms remain the least understood. The resulting new insights are of general relevance, for all plasmas and materials, including their various applications. We therefore hope to motivate computational and experimental scientists and engineers to collaborate more intensely on filling the existing gaps in knowledge. In this way, we expect that research will overcome a bottleneck stage in the development and optimization of multiscale models, and thus the fundamental understanding of plasma-surface interaction. TABLE OF CONTENTS wanderlust 3.3.2 Application-specific methods -specialize in the impossible 3.3.3 Machine learning -brainstorming by artificial intelligence 3.3.4 Plasma sheath modeling -matter's aura explained 3.4 Multiscale measuring -because nature is still the best simulation tool 4. PLASMA ETCHING -FROM SCRATCHING THE SURFACE TO GOING IN DEPTH 4.1 The multiscale plasma etching model -one example to represent them all 4.1.1 The need for a bottom-up approach -message in a bottleneck 4.1.2 Hybrid Plasma Equipment Model -example of a hybrid macroscale method 4.1.3 Plasma sheath module -example of a semi-analytical sheath method 4.1.4 Surface kinetics module -example of a deterministic description 4.1.5 Monte Carlo Feature Profile Model -example of a kinetic Monte Carlo method 4.1.6 Experimental benchmarking of the working principle -examples of multiscale measuring 4.1.7 Reactor geometry and operating conditions -example of a case study 4.2 How to implement the surface processes -example of atomistic modeling and measuring data 4.2.1 Elementary plasma-surface mechanisms -simplicity is the ultimate sophistication 4.2.2 Design of the surface chemistry set -a mosaic of quantum data 4.3 Benchmarking the simulation model -bringing uncertainties to the surface 5.

show abstract

Section: Multiscale Modeling -Coupling Classical and Quantum Mattermentioning

confidence: 99%

Multiscale modeling of plasma–surface interaction—General picture and a case study of Si and SiO2 etching by fluorocarbon-based plasmas

Vanraes

Venugopalan

Bogaerts

2021

Applied Physics Reviews

View full text Add to dashboard Cite

show abstract

“…These have achieved varying results, as in most of these cases there is the potential for generation of defects in the graphene layer during the cleaning process. However, in the case of ion beam cleaning, if the energy of the incident ion beam is sufficiently low, it is possible to remove material from the surface of graphene, without modifying the underlying graphene layer. ,,, This energy threshold has been demonstrated to be as low as a few electron-volts per incident atom and as such with a conventional ion beam this is difficult to achieve, as voltages in the kiloelectronvolts range are typically needed . One method of addressing this problem, which can be used at wafer scale and at various stages in a fabrication process, is to use a gas cluster ion beam (GCIB).…”

Section: Introductionmentioning

confidence: 99%

Gas Cluster Ion Beam Cleaning of CVD-Grown Graphene for Use in Electronic Device Fabrication

Brennan

Centeno

Zurutuza

et al. 2021

ACS Appl. Nano Mater.

View full text Add to dashboard Cite

One of the major challenges in the realization of electronic devices consisting of 2D materials produced using chemical vapor deposition (CVD) is the transfer of the 2D material from the growth catalyst to a relevant support material. However, the current steps of removing contamination from the transfer process is rarely fully effective with trace PMMA residue usually remaining. In this study, we explore the use of size selected argon gas clusters to clean polymer residue from CVD-grown commercial graphene samples. The energy per Ar atom can be tuned to <0.5 eV/atom, significantly below the bond strength of the graphene but sufficiently energetic to remove polymer material. Two of the primary techniques for characterizing the quality of graphene materials in terms of both chemical properties and physical properties are X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy, respectively. However, these are typically ex situ measurements and results can be heavily influenced by exposure of the samples to atmospheric conditions prior to measurement. However, by in situ monitoring the cleaning process through the use of a combined XPS and Raman spectroscopy system, coupled with an argon gas cluster ion beam (GCIB) and capable of carrying out each measurement simultaneously, this allows us to explore in detail any modifications to the graphene layer during the GCIB cleaning process. This investigation is further enhanced with additional time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging. Both the presence and removal of surface contamination is shown, and the level of defects being introduced into the graphene layer, as a result of the sputtering process, is monitored in real-time. We show that by keeping the energy per argon atom less than 1 eV, we can prevent the introduction of defects to the graphene layer, as well as efficiently remove contamination present on the graphene surface.

show abstract

“…There are numerous papers with computer simulation results for the bombardment of graphene by gas cluster projectiles, with various kinetic energies and sizes [43][44][45]. Kim et al [42] considered the cleaning, defect engineering and nanopore milling of suspended graphene with argon clusters.…”

Section: Introductionmentioning

confidence: 99%

Crosslinking Multilayer Graphene by Gas Cluster Ion Bombardment

et al. 2021

View full text Add to dashboard Cite

In this paper, we demonstrate a new, highly efficient method of crosslinking multilayer graphene, and create nanopores in it by its irradiation with low-energy argon cluster ions. Irradiation was performed by argon cluster ions with an acceleration energy E ≈ 30 keV, and total fluence of argon cluster ions ranging from 1 × 109 to 1 × 1014 ions/cm2. The results of the bombardment were observed by the direct examination of traces of argon-cluster penetration in multilayer graphene, using high-resolution transmission electron microscopy. Further image processing revealed an average pore diameter of approximately 3 nm, with the predominant size corresponding to 2 nm. We anticipate that a controlled cross-linking process in multilayer graphene can be achieved by appropriately varying irradiation energy, dose, and type of clusters. We believe that this method is very promising for modulating the properties of multilayer graphene, and opens new possibilities for creating three-dimensional nanomaterials.

show abstract

Multiscale simulation of ion beam impacts on a graphene surface

Cited by 4 publications

References 12 publications

Multiscale modeling of plasma–surface interaction—General picture and a case study of Si and SiO2 etching by fluorocarbon-based plasmas

Multiscale modeling of plasma–surface interaction—General picture and a case study of Si and SiO2 etching by fluorocarbon-based plasmas

Gas Cluster Ion Beam Cleaning of CVD-Grown Graphene for Use in Electronic Device Fabrication

Crosslinking Multilayer Graphene by Gas Cluster Ion Bombardment

Contact Info

Product

Resources

About