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Quantifying charge carrier localization in chemically doped semiconducting polymers


Charge transport in semiconducting polymers ranges from localized (hopping-like) to delocalized (metal-like), yet no quantitative model exists to fully capture this transport spectrum and its dependency on charge carrier density. In this study, using an archetypal polymer–dopant system, we measure the temperature-dependent electrical conductivity, Seebeck coefficient and extent of oxidation. We then use these measurements to develop a semi-localized transport (SLoT) model, which captures both localized and delocalized transport contributions. By applying the SLoT model to published data, we demonstrate its broad utility. We are able to determine system-dependent parameters such as the maximum localization energy of the system, how this localization energy changes with doping, the amount of dopant required to achieve metal-like conductivity and the conductivity a system could have in the absence of localization effects. This proposed SLoT model improves our ability to predict and tailor electronic properties of doped semiconducting polymers.

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Fig. 1: Depiction of spatial localization in semiconducting polymers and the resulting thermoelectric properties.
Fig. 2: Doping P3HT with FeCl3 and the resulting thermoelectric and spectroscopic properties.
Fig. 3: Quantifying localization in P3HT–FeCl3.
Fig. 4: Comparing the Kang–Snyder model (black lines) and SLoT model (coloured lines) to experimental data from literature.

Data availability

Source data are provided with this paper. The collected datasets are included in this published article, and additional datasets that have been analysed are from cited literature. Furthermore, to assist in the dissemination of the SLoT model, we provide a supplemental Excel worksheet (Supplementary Data 1) with the P3HT–FeCl3 production data, an s = 1 lookup table and auto-fill equations and plots. Calculus and numerical methods are not required to implement equations (1)–(5) from the SLoT model with this Excel worksheet. In addition, for convenience, any additional datasets generated and analysed during the current study will also be made available from the corresponding authors upon reasonable request.


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S.A.G. appreciates the partial support from the Office of Naval Research (award no. N00014-19-1-2162), the Department of Education Graduate Assistance in Areas of National Need (GAANN) programme at the Georgia Institute of Technology (award no. P200A180075), the Link Energy Foundation, and the Science and Technology of Material Interfaces (STAMI) group at the Georgia Institute of Technology. J.M.R. is grateful for partial support from the Office of Naval Research (award no. N00014-19-1-2162) and the GAANN program at Georgia Institute of Technology (award no. P200A180075). S.A.G. thanks J. F. Ponder Jr for a critical review and feedback. A.A. appreciates the support from the National Science Foundation (NSF) Graduate Research Fellowship (grant no. DGE-1650044). J.P.W. acknowledges support from the NSF Graduate Research Fellowship (grant no. DGE-1650044). A.K.M. acknowledges funding support from the ITRI-Rosenfeld Fellowship from the Energy Technologies Area at Lawrence Berkeley National Laboratory. G.J.S. thanks the NSF Designing Materials to Revolutionize and Engineer our Future (DMREF) programme (award no. 1729487). S.K.Y. is grateful for partial support from support the Office of Naval Research (award no. N00014-19-1-2162). Part of this work (XPS analysis) was performed in part at the Georgia Tech Institute for Electronics and Nanotechnology, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the NSF (grant no. ECCS-1542174). Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

Author information




S.A.G. conceptualized and coordinated the project, led charge transport measurements and authorship, and together with R.H. developed the SLoT model. R.H. conducted numerical modelling, prepared figures and manuscript and provided advice. A.A. and J.M.R. performed charge transport measurements and assisted with manuscript preparation. J.P.W. performed XPS measurements and analysis and assisted with manuscript preparation. A.K.M. guided the early formulation of the SLoT model and reviewed the manuscript. M.D.L. provided guidance to S.A.G. and J.P.W. for the XPS analysis and to S.A.G. for thermal and carrier property relationships. G.J.S. provided insight and reviewed the model and manuscript. S.K.Y. initially motivated the investigation, provided overall guidance and advice to the project, commented on the SLoT model development and reviewed and edited the manuscript.

Corresponding authors

Correspondence to Riley Hanus or Shannon K. Yee.

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The authors declare no competing interests.

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Peer review information Nature Materials thanks Denis Andrienko and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Notes 1–5.

Supplementary Data 1

SLoT model lookup table, algebraic transport computations and compiled thermoelectric data.

Source data

Source Data Fig. 2

XPS spectral data for Fig. 2.

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Gregory, S.A., Hanus, R., Atassi, A. et al. Quantifying charge carrier localization in chemically doped semiconducting polymers. Nat. Mater. (2021).

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