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Title: Organic contaminants and atmospheric nitrogen at the graphene–water interface: a simulation study
Ordered nanoscale patterns have been observed by atomic force microscopy at graphene–water and graphite–water interfaces. The two dominant explanations for these patterns are that (i) they consist of self-assembled organic contaminants or (ii) they are dense layers formed from atmospheric gases (especially nitrogen). Here we apply molecular dynamics simulations to study the behavior of dinitrogen and possible organic contaminants at the graphene–water interface. Despite the high concentration of N 2 in ambient air, we find that its expected occupancy at the graphene–water interface is quite low. Although dense (disordered) aggregates of dinitrogen have been observed in previous simulations, our results suggest that they are stable only in the presence of supersaturated aqueous N 2 solutions and dissipate rapidly when they coexist with nitrogen gas near atmospheric pressure. On the other hand, although heavy alkanes are present at only trace concentrations (micrograms per cubic meter) in typical indoor air, we predict that such concentrations can be sufficient to form ordered monolayers that cover the graphene–water interface. For octadecane, grand canonical Monte Carlo suggests nucleation and growth of monolayers above an ambient concentration near 6 μg m −3 , which is less than some literature values for indoor air. The thermodynamics of the formation of these alkane monolayers includes contributions from the hydration free-energy (unfavorable), the free-energy of adsorption to the graphene–water interface (highly favorable), and integration into the alkane monolayer phase (highly favorable). Furthermore, the peak-to-peak distances in AFM force profiles perpendicular to the interface (0.43–0.53 nm), agree with the distances calculated in simulations for overlayers of alkane-like molecules, but not for molecules such as N 2 , water, or aromatics. Taken together, these results suggest that ordered domains observed on graphene, graphite, and other hydrophobic materials in water are consistent with alkane-like molecules occupying the interface.  more » « less
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Journal Name:
Nanoscale Advances
Page Range / eLocation ID:
1741 to 1757
Medium: X
Sponsoring Org:
National Science Foundation
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    Version: 2.0

    Changes versus version 1.0 are the addition of the free energy of folding, adsorption, and pairing calculations (Sim_Figure-7) and shifting of the figure numbers to accommodate this addition.

    Conventions Used in These Files

    Structure Files
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    - namd/min_*.0.namd

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    Log Files
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    Files with the .sh extension can be found throughout. These usually provide the highest level control for submission of simulations and analysis. Look to these as a guide to what is happening. If there are scripts with step1_*.sh and step2_*.sh, they are intended to be run in order, with step1_*.sh first.


    The directory contents are as follows. The directories Sim_Figure-1 and Sim_Figure-8 include README.txt files that describe the files and naming conventions used throughout this data set.

    Sim_Figure-1: Simulations of N-acetylated C-amidated amino acids (Ac-X-NHMe) at the graphite–water interface.

    Sim_Figure-2: Simulations of different peptide designs (including acyclic, disulfide cyclized, and N-to-C cyclized) at the graphite–water interface.

    Sim_Figure-3: MM-GBSA calculations of different peptide sequences for a folded conformation and 5 misfolded/unfolded conformations.

    Sim_Figure-4: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 370 K.

    Sim_Figure-5: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 295 K.

    Sim_Figure-5_replica: Temperature replica exchange molecular dynamics simulations for the peptide cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) with 20 replicas for temperatures from 295 to 454 K.

    Sim_Figure-6: Simulation of the peptide molecule cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) in free solution (no graphite).

    Sim_Figure-7: Free energy calculations for folding, adsorption, and pairing for the peptide CHP1404 (sequence: cyc(GTGSGTG-GPGG-GCGTGTG-SGPG)). For folding, we calculate the PMF as function of RMSD by replica-exchange umbrella sampling (in the subdirectory Folding_CHP1404_Graphene/). We make the same calculation in solution, which required 3 seperate replica-exchange umbrella sampling calculations (in the subdirectory Folding_CHP1404_Solution/). Both PMF of RMSD calculations for the scrambled peptide are in Folding_scram1404/. For adsorption, calculation of the PMF for the orientational restraints and the calculation of the PMF along z (the distance between the graphene sheet and the center of mass of the peptide) are in Adsorption_CHP1404/ and Adsorption_scram1404/. The actual calculation of the free energy is done by a shell script ("") in the 1_free_energy/ subsubdirectory. Processing of the PMFs must be done first in the 0_pmf/ subsubdirectory. Finally, files for free energy calculations of pair formation for CHP1404 are found in the Pair/ subdirectory.

    Sim_Figure-8: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) where the peptides are far above the graphene–water interface in the initial configuration.

    Sim_Figure-9: Two replicates of a simulation of nine peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 370 K.

    Sim_Figure-9_scrambled: Two replicates of a simulation of nine peptide molecules with the control sequence cyc(GGTPTTGGGGGGSGGPSGTGGC) at the graphite–water interface at 370 K.

    Sim_Figure-10: Adaptive biasing for calculation of the free energy of the folded peptide as a function of the angle between its long axis and the zigzag directions of the underlying graphene sheet.


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