Tunable Percolation in Semiconducting Binary Polymer Nanoparticle Glasses

Renna, Lawrence A.; Bag, Monojit; Gehan, Timothy S.; Han, Xu; Lahti, Paul M.; Maroudas, Dimitrios; Venkataraman, D.

doi:10.1021/acs.jpcb.5b11716

Cited by 3 publications

(7 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…data is R 2 = 0.98, yielding as fitting parameters a = 0.16, p c = 18%, and t = 2.9. We have previously shown that conducting/insulating polymer nanoparticle assemblies follow predictions of the classical lattice‐model percolation theory . However, the power‐law parameters in MIEC systems yield parameters that deviate from lattice‐model percolation theory predictions.…”

Section: Resultsmentioning

confidence: 92%

“…Based on recent studies in MIECs, we used poly(3‐hexylthiophene) (P3HT, Rieke Metals, M̅ W = 36 kDa, regioregularity = 96%, and polydispersity Đ = 2.3) nanoparticles for electronic conduction . We chose to study Li‐ion transport because of its relevance in energy storage applications.…”

Section: Resultsmentioning

confidence: 99%

“…We studied four poly(vinylpyridine) (PVP) based polymers, which have been shown to be good solid‐state Li‐ion conductors . Surfactant stabilized polymer nanoparticles were fabricated via a previously reported method of postpolymerization miniemulsion, which is detailed in the Experimental Section. It has been previously shown that surfactants used in nanoparticle synthesis do not dope P3HT, which is not easily doped.…”

Section: Resultsmentioning

confidence: 99%

“…and G ion. , respectively) as power‐law scaling percolation behavior, using Equation

G (η) = a {(η - p_{normalc})}^{t} for η > p_{normalc}

where a is a scaling parameter, η is the percentage of the electronic or ionic conducting nanoparticle, p c is the percolation threshold concentration for long range connectivity, and t is the critical exponent, a descriptor of the fractal properties of the system. From percolation theory for a randomly‐packed sphere with only isotropic short‐range correlations, the predicted values of t are t ≈ 1.3 for systems having percolation pathways in two dimensions and t ≈ 2 for systems having percolating pathways in three dimensions .…”

Section: Resultsmentioning

confidence: 99%

“…Nanoparticle Synthesis : Polymer nanoparticles were fabricated via a previously reported method of postpolymerization miniemulsion . Briefly, a 0.5 mL of a 30 mg mL −1 solution of polymer in chloroform was added to 3 mL of 10 × 10 −3 m sodium dodecyl sulfate in NanoPure water.…”

Section: Methodsmentioning

confidence: 99%

See 4 more Smart Citations

Mixed Ionic–Electronic Conduction in Binary Polymer Nanoparticle Assemblies

Renna

Lenef

Bag

et al. 2017

Adv Materials Inter

Self Cite

View full text Add to dashboard Cite

transistors. [5] Polymer-based MIECs contain two principal components, one for electronic conduction and the other for ionic conduction. Each of these components should meet the molecular packing requirements for charge transport and both components should arrange in cocontinuous morphologies with percolation pathways for charge transport in three dimensions. Yet, achieving such structures relevant for MIECs has not been straightforward. At present, several different strategies are used to design and fabricate MIECs. They are: (1) mixing of conjugated polymers and polyelectrolytes [e.g., poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)], [5,6,8,9] (2) imbibing ionic fluids in conjugated polymer films, [11] (3) incorporating ion conducting side chains on conjugated polymers, [12][13][14][15][16] (4) ion-doped [17][18][19][20] or oxidized [21] conjugated polymers, and (5) diblock copoly mer with ion conducting and electronic conducting polymers as the constituent blocks [e.g., poly(3-hexylthiophene)-bpoly(ethylene oxide) (P3HT-b-PEO)]. [2,3] However, these methods do not afford separate and systematic control over the morphology and properties of the ionic and electronic conducting phases while keeping the overall morphology constant. The central problem is the lack of a general approach to control the molecular packing and morphology in MIECs. We report here an approach, based on polymer nanoparticle selfassembly, to fabricate polymer-based MIECs. This approach provides a pathway to achieve tailored molecular order for each component on the nanoscale (<100 nm) and targeted assembly of the components on the mesoscale (>100 nm-100 µm). We demonstrate the efficacy of this approach for fabricating MIECs through binary nanoparticle assemblies of electronically conducting and Li-ion conducting polymer nanoparticles (see Figure 1a).Nanoparticle self-assembly is emerging as a powerful tool to design and fabricate mesoscale assemblies and interfaces. [22][23][24][25] For polymer-based materials, they provide a unique pathway to generate complex structures and co-assemblies under nonequilibrium processing conditions with macroscopic homogeneity and compositional flexibility. In this strategy, we first fabricate polymer components as nanoparticles, and then use them as building blocks for further assembly to create Polymer-based mixed ionic-electronic conductors (MIECs) are desired for both bulk and interfacial materials in next-generation energy storage and electronic devices. Polymer-based MIECs contain two principal components, one for electronic conduction and the other for ionic conduction. The central problem is the lack of a general approach to control the molecular packing and morphology of the constituent components that will afford the ability to easily tune transport properties. This study demonstrates the efficacy of a modular method based on polymer nanoparticle self-assembly to achieve MIECs with tunable conductivity. This work uses poly(3-hexylthiophene) nanoparticles as the electronic conductor and li...

show abstract

Section: Resultsmentioning

confidence: 92%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…and G ion. , respectively) as power‐law scaling percolation behavior, using Equation

G (η) = a {(η - p_{normalc})}^{t} for η > p_{normalc}

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Mixed Ionic–Electronic Conduction in Binary Polymer Nanoparticle Assemblies

Renna

Lenef

Bag

et al. 2017

Adv Materials Inter

Self Cite

View full text Add to dashboard Cite

show abstract

Controllable Bulk Heterojunction Morphology by Self-Assembly of Oppositely Charged Nanoparticles

2017

View full text Add to dashboard Cite

Using kinetic Monte Carlo simulations of a simple coarse-grained model, we demonstrate that the self-assembly of oppositely charged nanoparticles is a promising approach to design efficient bulk heterojunction (BHJ) solar cells. Simulations are performed starting from a random configuration of oppositely charged nanoparticles in solution for a range of concentrations. Interconnected percolated morphologies form at high nanoparticle concentrations, when the aggregate growth ceases after certain time. If only Coulombic interactions are present, the observed morphologies have very high interfacial area but too small domain size, whereas optimum values of both the interfacial area and domain size are desired for BHJ. We therefore propose and establish that an additional hydrophobic attraction between nanoparticles of same type is desired to obtain the ideal BHJ morphology. We also discuss the effects of solvent dielectric constant and the size- and charge-asymmetry of nanoparticles, which may provide additional means to control the BHJ morphology.

show abstract