Stabilization of aqueous graphene dispersions utilizing a biocompatible dispersant: a molecular dynamics study

Huang, Shirong; Bezugly, Viktor; Cuniberti, Gianaurelio

doi:10.1039/c9cp04742e

Cited by 10 publications

(6 citation statements)

References 67 publications

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“…Reaching the equilibrium state, CuPc molecules were attached on graphene surface via π–π stacking. [ 60 ] In the second part, the graphene flakes functionalized by CuPc molecules from the previous box were introduced into a new simulation box. In addition, analyte gas (NH 3 or PH 3 ) molecules and nitrogen gas were present in the simulation system.…”

Section: Methodsmentioning

confidence: 99%

“…Reaching the equilibrium state, all NH 3 molecules are adsorbed by the CuPc molecules, which are attached to the graphene flake via π-π stacking interactions. [59,60] In the PH 3 case, only a part of the PH 3 molecule population is adsorbed, of which some PH 3 molecules are attached to graphene surface and others to CuPc.…”

Section: Gas Sensing Mechanism Analysis Via Mdsmentioning

confidence: 99%

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Machine Learning‐Enabled Smart Gas Sensing Platform for Identification of Industrial Gases

Huang

Panes-Ruiz

Khavrus³

et al. 2022

Advanced Intelligent Systems

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Both ammonia and phosphine are widely used in industrial processes, and yet they are noxious and exhibit detrimental effects on human health. Despite the remarkable progress on sensors development, there are still some limitations, for instance, the requirement of high operating temperatures, and that most sensors are solely dedicated to individual gas monitoring. Herein, an ultrasensitive, highly discriminative platform is demonstrated for the detection and identification of ammonia and phosphine at room temperature using a graphene nanosensor. Graphene is exfoliated and successfully functionalized by copper phthalocyanine derivate. In combination with highly efficient machine learning techniques, the developed graphene nanosensor demonstrates an excellent gas identification performance even at ultralow concentrations: 100 ppb NH3 (accuracy—100.0%, sensitivity—100.0%, specificity—100.0%) and 100 ppb PH3 (accuracy—77.8%, sensitivity—75.0%, and specificity—78.6%). Molecular dynamics simulation results reveal that the copper phthalocyanine derivate molecules attached to the graphene surface facilitate the adsorption of ammonia molecules owing to hydrogen bonding interactions. The developed smart gas sensing platform paves a path to design a highly selective, highly sensitive, miniaturized, low‐power consumption, nondedicated, smart gas sensing system toward a wide spectrum of gases.

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Section: Methodsmentioning

confidence: 99%

Section: Gas Sensing Mechanism Analysis Via Mdsmentioning

confidence: 99%

Machine Learning‐Enabled Smart Gas Sensing Platform for Identification of Industrial Gases

Huang

Panes-Ruiz

Khavrus³

et al. 2022

Advanced Intelligent Systems

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“…As showed by Huang et al, in a study using all-atom molecular dynamics simulations, stability of mono-layer graphene with Rib is strongly dependent upon the amount of surfactant absorbed on the surface, showing that low or high concentrations lead to agglomeration and loss of stability in water. [65] However, the study did not investigate the interactions of G-Rib complex in the presence of other molecules or salt.…”

Section: Biochemical Analysesmentioning

confidence: 99%

Toxicological evaluation of highly water dispersible few-layer graphene in vivo

Ruiz

Lucherelli

Murera

et al. 2020

Carbon

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In the last decade, graphene-based materials have received increasing attention for both academic research and industrial uses. However, products containing graphene must meet the same standards for quality, safety and efficacy as products not containing nanomaterials. Our aim is to shed light on the toxicological characterization of few-layer graphene (FLG) dispersions. In the present study, graphene was easily dispersed in water using biocompatible riboflavin-5′-phosphate sodium salt (Rib). A highly concentrated FLG dispersion (G-Rib) was stable for months. G-Rib suspension was characterized by HR-TEM, Raman spectroscopy and ζ-potential. Our results showed that even at high concentration of G-Rib, cell survival was always above 85%. Then, we investigated the tissue distribution and toxic effects of G-Rib in mice up to 30 days after intravenous injections. Histological analysis of the tissues revealed hepatic accumulation and excretion through the kidneys. The biochemical and hematological parameters remained within the reference range showing no hematotoxicity. Finally, no signs of inflammation were detected in the cells isolated from the lymph nodes and spleen. The results of the study show that highly water dispersed FLG is a material with a very low toxic profile, which is one of the first requirements for the future development of biomedical applications.

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“…Pull codes can now be routinely called by most molecular dynamics programs. The method is increasingly being applied to better understand a range of molecular interactions and allow one to describe the free energy profile along a particular reaction coordinate [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48].…”

Section: Introductionmentioning

confidence: 99%

Pulling Simulations and Hydrogen Sorption Modelling on Carbon Nanotube Bundles

Gotzias

Sapalidis

2020

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Recent progress in molecular simulation technology has developed an interest in modernizing the usual computational methods and approaches. For instance, most of the theoretical work on hydrogen adsorption on carbon nanotubes was conducted a decade ago. It should be insightful to reinvestigate the field and take advantage of code improvements and features implemented in contemporary software. One example of such features is the pulling simulation modules now available in many molecular dynamics programs. We conduct pulling simulations on pairs of carbon nanotubes and measure the inter-tube distance before they dissociate in water. We use this distance to set the interval size between adjacent nanotubes as we arrange them in bundle configurations. We consider bundles with triangular, intermediate and honeycomb patterns, and armchair nanotubes with a chiral index from n = 5 to n = 10. Then, we simulate low pressure hydrogen adsorption isotherms at 77 K, using the grand canonical Monte Carlo method. The different bundle configurations adsorb great hydrogen amounts that may exceed 2% wt at ambient pressures. The computed hydrogen capacities are considered large for physisorption on carbon nanostructures and attributed to the ultra-microporous network and extraordinary high surface area of the configured models.

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Stabilization of aqueous graphene dispersions utilizing a biocompatible dispersant: a molecular dynamics study

Abstract: Investigation of the high efficiency of flavin mononucleotide sodium salt (FMNS) for the stabilization of aqueous graphene dispersions using all-atom molecular dynamics simulations.

Cited by 10 publications

References 67 publications

Machine Learning‐Enabled Smart Gas Sensing Platform for Identification of Industrial Gases

Machine Learning‐Enabled Smart Gas Sensing Platform for Identification of Industrial Gases

Toxicological evaluation of highly water dispersible few-layer graphene in vivo

Pulling Simulations and Hydrogen Sorption Modelling on Carbon Nanotube Bundles

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