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Nanografting: Modeling and Simulation

Authors: Seol, Ryu; George C, Schatz;

Nanografting: Modeling and Simulation

Abstract

We present a simple phenomenological model of the nanografting process with an emphasis on the formation of binary self-assembled monolayers. This model includes dynamical processes that are involved in natural growth experiments, including molecular deposition, surface diffusion, and the phase transition from physisorption to chemisorption, and we show that it predicts domain formation in ungrafted deposition that matches experiment. The one-order-of-magnitude faster kinetics that is found in the nanografting experiments compared to natural self-assembly (or unconstrained self-assembly) is described with a key assumption that the deposition rate is greatly enhanced in the small region confined between the back side of the AFM tip and the edge of the previously deposited self-assembled monolayer. Monte Carlo simulations based on this model reproduce experimental observations concerning the variation of SAM heterogeneity with AFM tip speed. Our simulations demonstrate that the faster the AFM tip displaces adsorbed molecules in a monolayer, the more heterogeneous are the monolayers formed behind the tip, as this allows space and time for the formation of phase-segregated domains.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Top 10%
Top 10%
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