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Record W3025008929 · doi:10.1149/ma2020-018760mtgabs

Formation of Ion Pairs and Charge-Transfer Complexes in the p-Doping of Organic Semiconductors

2020· article· en· W3025008929 on OpenAlexaff
Hannes Hase, Jiang Tian Liu, Pat Forgione, Ingo Salzmann

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsDopantDopingMaterials scienceFourier transform infrared spectroscopyOrganic semiconductorAcceptorInfrared spectroscopyIonizationPolymerAnalytical Chemistry (journal)Chemical physicsIonChemistryOrganic chemistryOptoelectronicsOpticsPhysics

Abstract

fetched live from OpenAlex

The formation of ion pairs (IPA) through integer charge transfer and ground-state charge-transfer complexes (CPXs) with only fractional charge transfer are the two known mechanisms in the molecular doping of conjugated polymers and molecules, which form the material class of organic semiconductors (OSCs). As it entails no immediate ionization of the OSC, CPX formation is regarded as detrimental to the doping efficiency. For IPA formation to occur, a match between the electron affinity (EA) of the p-dopant and the ionization energy (IE) of the OSC is expected as crucial, while their pronounced frontier molecular orbital overlap should promote CPX formation instead [1]. To explore these complementary scenarios, we first studied the thermal de-doping of the prototypical conjugated polymer poly(3-hexylthiophene) (P3HT), p-doped with the common strong electron acceptor tetrafluoro-tetracyanoquinodimethane (F4TCNQ) [2]. We combined grazing incidence X-ray diffraction (GIXRD) with Fourier-transform infrared spectroscopy (FTIR) to determine the microstructure, and absorbance spectroscopy (UV/vis/NIR) to observe the spectral fingerprint of the two doping scenarios. We found two microstructural environments through their distinguished thermal stabilities, where, the dopants were observed (i) alternatingly stacked with the polymer backbone as well as (ii) dispersed in its sidechain region. From FTIR and UV/vis/NIR we deduce that all dopants are fully ionized, although packing between dopant and polymer backbone would be expected to favor CPX formation instead. Notably, while characteristic shifts of the mid-infrared cyano-stretch modes of TCNQ derivatives are known to well indicate the degree of charge transfer, we show here that they allow further to assess the dopant site in the polymer environment. We further investigated the influence of EA with respect to IE by contrasting F4TCNQ with its derivatives of lower degree of fluorination, which translates into reduced EA while leaving the spatial aspects of the dopant largely intact. We find that using F2TCNQ and FTCNQ still results in IPA formation in spite of EA < IE, which we understand through the lower degree of spatial, and therefore energetic order in OSCs as compared to inorganic semiconductors, which therefore possess no sharp band edges. Surprisingly, at high doping concentrations (additional) CPX formation occurred for all the differently strong dopants, which highlights the complexity of these systems going beyond the sole impact of the energetics of the individual constituents. Finally, we juxtaposed the known tendency of small molecular OSCs to form CPXs and that of polymer OSCs to form IPAs. To maximize the comparability with P3HT, alkylated oligothiophenes of different length were synthesized in-house (from 4 to 10 thiophene repeat units) and doped with F4TCNQ. For the longest oligomer, we were able to observe the switch from the CPX regime into that of IPA, i.e., we approach the doping behavior polymer limit. Knowing this threshold is valuable for applications in organic electronics where vacuum processible small molecular OSCs are preferred over polymeric OSCs, which are only processible via solution-based methods. [1] I. Salzmann, G. Heimel, M. Oehzelt, S. Winkler, N. Koch, Acc. Chem. Res. 2016, 49, 370. [2] H. Hase, K. O’Neill, J. Frisch, A. Opitz, N. Koch, I. Salzmann, The Journal of Physical Chemistry C 2018, 122, 25893.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.253
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
Has abstractyes

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