In Situ Characterization of Lifetime and Morphology in Operating Bulk Heterojunction Organic Photovoltaic Devices by Impedance Spectroscopy
Time‐dependent charge transport in operating poly(3‐hexylthiophene):[6,6]‐phenyl‐C61‐butyric acid methyl ester (P3HT:PCBM) bulk heterojunction organic photovoltaic (OPV) devices has been characterized with impedance spectroscopy. Devices with varied composition and morphology were measured over a ra...
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Veröffentlicht in: | Advanced Energy Materials 2012-01, Vol.2 (1), p.120-128 |
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Sprache: | eng |
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Zusammenfassung: | Time‐dependent charge transport in operating poly(3‐hexylthiophene):[6,6]‐phenyl‐C61‐butyric acid methyl ester (P3HT:PCBM) bulk heterojunction organic photovoltaic (OPV) devices has been characterized with impedance spectroscopy. Devices with varied composition and morphology were measured over a range of illumination intensities ranging from dark conditions to 1 sun and applied bias voltages ranging from 0.0 V to 0.75 V. Using an equivalent circuit model, materials properties such as dielectric constant and conductivity were determined and found to be in agreement with values measured by other methods. Average carrier lifetimes were also extracted from the model and found to correlate with measured power conversion efficiencies. At the short circuit condition and ∼1 sun illumination, the average electron lifetime was found to vary from 7.8 to 22 μs for devices with power conversion efficiencies ranging from 2.0 to 2.5%. These results suggest that impedance spectroscopy is an effective tool for predicting how processing parameters can impact device performance in organic bulk heterojunction photovoltaic devices.
P3HT:PCBM bulk heterojunction organic photovoltaic devices with varied composition and morphology are characterized with impedance spectroscopy over a range of illumination intensities and applied bias voltages. Materials properties and average carrier lifetimes are extracted from an equivalent circuit model, and the results suggest that the approach is an effective tool for predicting how processing parameters can impact device performance. |
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ISSN: | 1614-6832 1614-6840 |
DOI: | 10.1002/aenm.201100357 |