Manipulating the Optically Active Defect–Defect Interaction of Colloidal Quantum Dots for Carbon Dioxide Photoreduction
Bibliographic record
Abstract
Defect engineering in colloidal quantum dots (QDs), a typical photocatalytic material, is promising to tailor optoelectronic properties and achieve solar-to-fuel energy conversion. However, understanding the effect of defect–defect interactions on both charge carrier and catalytic dynamics is still challenging. Here, we report a class of defect-engineered copper-deficient Zn-doped CuInS 2 (ZCIS) QDs that synergistically utilize copper vacancy and Cu 2+ defect states to realize CO 2 photoreduction. Steady and transient optical characterizations reveal that the density of copper vacancy can manipulate the distribution of optically active Cu + and Cu 2+ defect states (appearing as Cu In ″ and Cu Cu • species, respectively), wherein the Cu + defect states suppress interband absorption and sharpen the Shockley–Read–Hall recombination, while Cu 2+ defect states enable the prolonged exciton lifetime of QDs. In situ infrared spectroscopic investigation and theoretical density functional calculation demonstrate the photoactive Cu 2+ defect states nearby the copper vacancy in ZCIS QDs can effectively activate CO 2 to the COOH* intermediates, leading to a remarkable photocatalytic CO production rate up to 532.3 μmol g –1 h –1 (turnover number ∼1963) after 120 h illumination.
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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 | 0.001 | 0.001 |
| 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 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".