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Explaining the Transition from Diffusion Limited to Reaction Limited Surface Assembly of Molecular Species through Spatial Variations
Author(s) -
Keith M. Carroll,
Armin W. Knoll,
Heiko Wolf,
Urs Duerig
Publication year - 2017
Publication title -
langmuir
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.042
H-Index - 333
eISSN - 1520-5827
pISSN - 0743-7463
DOI - 10.1021/acs.langmuir.7b03050
Subject(s) - diffusion , statistical physics , reaction–diffusion system , heuristic , surface diffusion , surface (topology) , molecular diffusion , chemical physics , particle (ecology) , chemistry , biological system , physics , thermodynamics , mathematics , geometry , mathematical optimization , metric (unit) , operations management , adsorption , biology , economics , oceanography , geology
Surface assembly is often decomposed into two classes: diffusion and reaction limited processes. The transition between the two cases is complex because the dynamics are so different. In this article, we simulate, explain, and experimentally discuss the evolution of the spatial distribution for surface assemblies with diffusion limited and reaction limited processes. Explicitly, we demonstrate that diffusion limited and reaction limited processes show some temporal differences, but more importantly, we show that the spatial arrangements are different enough to discriminate between the two cases. Using fundamental properties, such as the diffusion constant, we calculate the evolution of the spatial profile and derive from physical, heuristic models the assembly rate for reaction and diffusion limited processes based on the individual particle's interactions with the surface. Finally, we confirm the spatial profile differences between diffusion and reaction limited cases by experimentally measuring the surface assembly between two molecules of similar size, but having different assembly routes. Unique to our description is that we have derived and simulated everything through the particle picture in place of ensemble descriptions such as the diffusion equation, and we show the equivalence between our heuristic formulas and those derived from the diffusion equation.

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