Influence of Excess Conjugated Wrapping Polymer in Semiconducting Single-Walled Carbon Nanotube Dispersions
Bibliographic record
Abstract
Single-walled carbon nanotubes (SWNTs) are promising nanomaterials for incorporation into organic electronic devices (OEDs), with the potential to fabricate flexible devices while exploiting inexpensive solution-processing techniques. As-synthesized SWNTs are insoluble and comprised of a mixture of metallic and semiconducting SWNTs (sc-SWNTs), necessitating dispersal and purification before integration into OEDs. Refinement of conjugated polymer extraction techniques has allowed for the isolation of sc-SWNTs from metallic in a reproducible and scalable manner. The availability of highly-pure sc-SWNT materials has facilitated the production of thin-film transistors (TFTs) with very high charge carrier mobilities, outperforming organic small molecule and polymer semiconductors. However, the realization of commercial OED applications of polymer-sorted sc-SWNTs have not yet been achieved, partially due to the prohibitive time and materials costs associated with purifying sc-SWNTs. Current protocols for dispersing sc-SWNTs with conjugated polymers involve three broad steps: (1) dispersion of bulk SWNT material, (2) removal of non-dispersed carbonaceous materials, and (3) removal of excess polymer through filtration or centrifugation. The final step of removal of excess polymer is time-consuming and wasteful, but viewed as necessary for preparing high-performing TFTs, as the conjugated polymer has much lower performance compared to SWNTs. In this study we performed the first systematic investigation of the effect of excess polymer on SWNT TFT performance. Three SWNT concentrations were investigated, with varying ratios of excess polymer added to each. TFT device performance was monitored using several metrics, including: mobility, threshold voltage, on/off ratios and hysteresis. Characterization of large numbers of replicate TFT devices determined that below a threshold amount of excess polymer the presence of excess polymer did not have a negative impact on device performance. Detailed analysis of the sc-SWNT films through Raman spectroscopy and atomic force microscopy (AFM) confirmed that a simple rinsing step was sufficient to remove all the unbound conjugated polymer from the substrate surface without affecting the sc-SWNT network. The volume of solvent required for the rinsing step was substantially lower than that required for filtration or centrifugation steps. Furthermore, at higher SWNT concentrations the excess polymer prevented nanotube bundling, resulting in moderate improvements in both mobility and on/off ratios. Our results were reproducible for two different conjugated polymer sc-SWNT systems, demonstrating the versatility of this procedure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".