Tunable Percolation in Semiconducting Binary Polymer Nanoparticle Glasses
Author(s) -
Lawrence A. Renna,
Monojit Bag,
Timothy S. Gehan,
Xu Han,
Paul M. Lahti,
Dimitrios Maroudas,
D. Venkataraman
Publication year - 2016
Publication title -
the journal of physical chemistry b
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.864
H-Index - 392
eISSN - 1520-6106
pISSN - 1520-5207
DOI - 10.1021/acs.jpcb.5b11716
Subject(s) - percolation (cognitive psychology) , materials science , nanoparticle , percolation threshold , polymer , nanotechnology , binary number , nanoscopic scale , scaling , percolation theory , amorphous solid , conductivity , electrical resistivity and conductivity , physics , composite material , chemistry , arithmetic , mathematics , geometry , quantum mechanics , neuroscience , biology , organic chemistry
Binary polymer nanoparticle glasses provide opportunities to realize the facile assembly of disparate components, with control over nanoscale and mesoscale domains, for the development of functional materials. This work demonstrates that tunable electrical percolation can be achieved through semiconducting/insulating polymer nanoparticle glasses by varying the relative percentages of equal-sized nanoparticle constituents of the binary assembly. Using time-of-flight charge carrier mobility measurements and conducting atomic force microscopy, we show that these systems exhibit power law scaling percolation behavior with percolation thresholds of ∼24-30%. We develop a simple resistor network model, which can reproduce the experimental data, and can be used to predict percolation trends in binary polymer nanoparticle glasses. Finally, we analyze the cluster statistics of simulated binary nanoparticle glasses, and characterize them according to their predominant local motifs as (p(i), p(1-i))-connected networks that can be used as a supramolecular toolbox for rational material design based on polymer nanoparticles.
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