DOI > 10.5291/ILL-DATA.9-11-2090

Please note

The full details of this dataset is not yet available to the public as it still under its embargo period. As such there are only a few details publically exposed. To find out more about how the ILL governs the release of data, please go here. Thank you for your understanding.

Title

Hysteresis in polymer/small-molecule mixtures for OPV applications

Abstract

Organic photovoltaics (OPVs) are candidates for the large-scale capture of solar radiation, due to the potential to process these materials in large areas at low cost. However, considerable challenges exist in terms of lifetime and robustness of performance. This proposal forms part of a wider effort in which our motivation is to complement device optimisation strategies with in-depth studies of model systems, aimed at increasing the fundamental understanding of the materials science within polymer nanocomposite thin-films. This proposal builds on the understanding that we have recently developed by systematically studying equilibrated polymer/small-molecule bilayer systems, using in-situ thermal annealing/neutron reflectometry. Equilibration occurs on annealing at sufficiently high temperature. However, in a number of cases we have observed examples of `non-equilibrium mixingż during isothermal annealing at lower temperatures; here extensive mass transfer occurs, but the system does not achieve thermodynamic equilibrium. The current proposal seeks to systematically investigate this behaviour, which is of key importance for working OPVs.

Experimental Report

Download Data

The data is currently only available to download if you are a member of the proposal team.

Download Data

Data Citation

The recommended format for citing this dataset in a research publication is in the following format:

HIGGINS Anthony M.; CABRAL Joao T.; GUTFREUND Philipp; Andrew J. Parnell and SAERBECK Thomas. (2023). Hysteresis in polymer/small-molecule mixtures for OPV applications. Institut Laue-Langevin (ILL) doi:10.5291/ILL-DATA.9-11-2090

Cited by

This data has not been cited by any articles.

Metadata

Experiment Parameters

This data is not yet public

Sample Parameters

This data is not yet public