Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 316

The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.

Predicting Morphologies of Solution Processed Polymer:Fullerene Blends

Kouijzer, Sandra, Michels, Jasper J., van den Berg, Mauricio, Gevaerts, Veronique S., Turbiez, Mathieu, Wienk, Martijn M., Janssen, René A. J.·2013·Journal of the American Chemical Society

Abstract

The performance of solution processed polymer:fullerene thin film photovoltaic cells is largely determined by the nanoscopic and mesoscopic morphology of these blends that is formed during the drying of the layer. Although blend morphologies have been studied in detail using a variety of microscopic, spectroscopic, and scattering techniques and a large degree of control has been obtained, the current understanding of the processes involved is limited. Hence, predicting the optimized processing conditions and the corresponding device performance remains a challenge. We present an experimental and modeling study on blends of a small band gap diketopyrrolopyrrole-quinquethiophene alternating copolymer (PDPP5T) and [6,6]-phenyl-C71-butyric acid methyl ester ([70]PCBM) cast from chloroform solution. The model uses the homogeneous Flory-Huggins free energy of the multicomponent blend and accounts for interfacial interactions between (locally) separated phases, based on physical properties of the polymer, fullerene, and solvent. We show that the spinodal liquid-liquid demixing that occurs during drying is responsible for the observed morphologies. The model predicts an increasing feature size and decreasing fullerene concentration in the polymer matrix with increasing drying time in accordance with experimental observations and device performance. The results represent a first step toward a predictive model for morphology formation.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/ja405493j

Cites

50 of 50 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 316

Metadata

Authors
Kouijzer, S., Michels, J. J., van den Berg, M., Gevaerts, V. S., Turbiez, M., Wienk, M. M., & Janssen, R. A. J.
Venue
Journal of the American Chemical Society
Published
2013-08-01
Volume
135
Issue
32
Pages
12057-12067
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2148721114
Cited by
316
References
50
FWCI
13.58
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.