CF : A first-principles study of structural patterns arising during synthetic growth

Gueorguiev, Gueorgui Kostov; Goyenola, Cecilia; Schmidt, Susann; Hultman, Lars

doi:10.1016/j.cplett.2011.09.045

Cited by 44 publications

(52 citation statements)

References 31 publications

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“…These results also agree very well with the observation that the incorporation of F in a graphene network gradually degrades its three-coordinated sp 2 -hybridized planar structure, by promoting interlocking and amorphousness (previous subsection, and Ref. 30 ).…”

Section: Resultssupporting

confidence: 80%

“…As the F content is further increased, the CF x networks become progressively more disrupted and usually, only a small fraction of them retain regularly looking defects, such as large rings and branching. 30 Features like interlocking and amorphousness strongly prevail. These observations are explained considering the fact that F is chemically very different from C, and thus, the changing impact of its incorporation in a graphene-like network is substantial.…”

Section: Resultsmentioning

confidence: 99%

“…Instead, incorporated F tends to stick out of the network and to provoke a local disruption, leading to characteristic patterns such as large rings and branching. 30 As the amount of F incorporated in the network increases, these disruption patterns densify and start to interact with each other. Some of them prevail (i.e., preserve their initial structural identity), while others recombine to form structural features at a larger size scale.…”

Section: Resultsmentioning

confidence: 99%

“…Higher F concentrations were expected to lead to higher concentration of defects tending to amorphization and to polymerization. 25,30 In pursuit of further understanding the structure of fluorinated carbon-based thin films and the mechanism of their formation, in this work we explore the structural and energetic implications of different concentrations of fluorine in graphene-like sheets. While in our previous work we studied the effects of a substitutional fluorine atom in pure carbon model systems, now we approach the structural evolution of essentially binary systems CF x with fluorine contents ranging between 0 at.% and 30 at.%.…”

Section: Introductionmentioning

confidence: 99%

“…In our previous work carried out by SGC, 25,30 we studied the substitution of a C atom by a F atom in graphene-like model systems. This study resulted in a classification of structural patterns in F-doped graphene-like networks (0-7 at.% of F): (i) large N members rings (N=8-12),…”

Section: Introductionmentioning

confidence: 99%

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Carbon Fluoride, CF_x: Structural Diversity as Predicted by First Principles

et al. 2014

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Fluorinated carbon-based thin films offer a wide range of properties for many technological applications that depend on the microstructure of the films. To gain a better understanding on the role of fluorine in the structural formation of these films, CF x systems based on graphenelike fragments were studied by first principles calculations. Generally, the F concentration determines the type of film that can be obtained. For low F concentrations (up to ∼ 5 at.%), films with fullerene-like as well as graphite-like features are expected. Larger F concentrations (≥ 10 at.%) give rise to increasingly amorphous carbon films. Further increasing the F concentration in the films leads to formation of a polymer-like microstructure. In order to aid characterization of CF x systems generated by computational methods, a statistical approach is developed.

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Section: Resultssupporting

confidence: 80%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Carbon Fluoride, CF_x: Structural Diversity as Predicted by First Principles

et al. 2014

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Data‐Driven Strategies for Accelerated Structural Exploration of High‐Performance 2D Carbon‐Based Seawater Desalination Membranes

Niu,

Xu,

Meng

et al. 2024

Physica Rapid Research Ltrs

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The insufficiency of freshwater supplies has posed a serious threat to sustainable socio‐economic growth, and seawater desalination is considered to be the most promising solution to alleviate such pressure. Currently, two‐dimensional (2D) carbon membranes are identified as deserving candidates since their high permeability and multiple tunable properties. However, they remain challenging to systematically uncover the potential relationships between structures and properties in various 2D carbon materials. For this, we trained a machine learning (ML) model based on feature datasets of 2D carbon materials effecting desalination properties. The results suggest that structures with a maximum pore size of 10‐12 atoms and atomic densities between 0.28 and 0.41 are more likely to achieve high properties. We selected the Cml‐MOR based on MOR type mordenite zeolite for validation. Further, Cml‐MOR is demonstrated to feature remarkable salt ion adsorption. The effective water flux of Cml‐MOR is 113.51 L·cm‐2·day‐1·MPa‐1, and the salt rejection at 110 MPa could reach to 98.9%. This work is expected to apply this efficient method to investigate the structure and properties of 2D carbon membranes with great structural diversity; this will attract more people to focus on them and explore their important potential for practical applications.This article is protected by copyright. All rights reserved.

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