Electrochemical Transformation of 2,5-Diphenyltellurophene
Bibliographic record
Abstract
Tellurphene-containing materials are attracting great attention in a wide range of chemistry field. Due to the metalloid nature of tellurium, tellurophene shows unique reactivity. Previous report revealed that the 2,5-diphenyltellurophene (PT) reacted with halogen sources to give its dihalogen adducts PT-X2 (Seferos et al., Dalton Trans. 2015, 44, 2092.) (Figure, upper). In this reaction, the oxidation state of tellurium-center changed from Te(II) to Te(IV), in other word, tellurium transformed into the hypervalent state. Interestingly, dehalogenation also occurred by the irradiation of the lights to give an original Te(II)-centered tellurophene. In this study, we have investigated the electrochemical transformation of PT (Figure, lower). The spectroelectrochemistry measurements have successfully revealed that the oxidation of PT in the presence of halides (F-, Cl-, Br-) gave the corresponding hypervalent tellurium compound, PT-X2 . In addition, the electrochemical reduction of PT-X2 resulted in the recovery of PT. In the course of Te(II)/Te(IV) redox cycle, there were no trace of side reaction, evidenced by the existence of isobestic points in absorption spectra. The bulk electrolysis of PT was also succeeded to give PT-X2 in sufficient yield. Figure 1
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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) | 0.001 | 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".