Electrocatalytic applications of organic semiconductors
Bibliographic record
Abstract
With the announcement of Nobel Prize in chemistry in 2000, organic semiconductors and conjugated structures have been used for various applications like organic solar cells (OSCs), organic light emitting diodes (OLEDs), organic field effect transistors (OFETs).Due to the common belief in their instability in solutions (both in organic and in aqueous) exploration of their activity as catalytic materials remains mainly unexplored.This study aims to explore catalytic properties of organic semiconductors with a heterogeneous approach.As a first step a wellknown organic semiconductor, polythiophene is used as backbone for the immobilization of metal complexes which are capable of reducing CO 2 to further products.This combined with photoactive property of polythiophene enabled the photoelectrocatalytic reduction of carbon dioxide.Apart from fixing the catalyst on the electrode via polymerization, anchoring of the catalyst CuTPP-COOH for driving the photoelectrochemical reduction of O 2 to H 2 O 2 was also carried out.CuTPP-COOH supported on TiO 2 NTs showed good stability over time and more importantly reduced dissolved oxygen to hydrogen peroxide in neutral pH with a rate of 13.4 g H 2 O 2 / g CuTPP-COOH / h.This value is comparable to the well-known literature examples of ZnO and g-C 3 N 4 .In another approach H-bonded semiconductors, namely Quinacridone, Indigo and naphthalene diimide, were utilized as efficient carbon dioxide (CO 2 ) capturing agents in organic solvents as well as in aqueous media.These compounds showed uptake capacities of 4.6 mmol.g -1 and 2.3 mmol.g -1 which are comparable to state-of-the-art amine based capturing agents (uptake capacity of 8 mmol.g -1 ).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".