Dopant-Modulated Conjugated Polymer Enrichment of Semiconducting SWCNTs
Bibliographic record
Abstract
Conjugated polymer extraction (CPE) is a low-cost, scalable process that can enrich single-walled carbon nanotube (SWCNT) materials in organic media. For other separation methods in aqueous phases, redox chemistry and/or pH control dramatically affect the sorting process of the SWCNTs. We have previously determined that the CPE process can be fine-tuned by adjusting the pH on the tube surface. Here, we systematically studied the effect of redox chemistry on the CPE process by adding organic p-/n-dopants. At a very strong p-/n-doping level, static repulsions dominated the interactions between the tubes and the CPE lost selectivity. When the doping level changed from a medium p-doping to a neutral state, the yield of CPE increased and the selectivity was compromised. We also observed chiral selectivity when a weak p-dopant was used. A photoluminescence excitation mapping under different titration conditions provided more insight into the doping level of the tubes relative to their diameters, chiralities, and redox potentials. We proposed a mechanism for the CPE process. The semiconducting and metallic tubes are separated because of their different solubilities, which are determined by the bundling energy between the tubes and are related to their doping level in polymer solutions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".