Gold Nanocrystals and Conjugated Polymer-Wrapped Single-Walled Carbon Nanotube Composites for Catalyzing CO<sub>2</sub> Electroreduction
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Metal nanocrystals (NCs) have been synthesized and used as highly efficient electrocatalysts for the electrocatalytic CO 2 reduction reaction (eCO 2 RR) in recent years. Electrocatalysts with various metal sizes and morphologies have achieved remarkable improvement in the CO 2 reduction. However, the syntheses are typically energy-demanding and the catalysts exhibit low mass activity. Ultrasmall metal NCs synthesized by a one-step process at room temperature and an ambient environment stand out because of cost-effectiveness in materials and energy. Here, we report a facile synthesis to produce 1 nm gold nanocrystals in ambient conditions, which was realized by an in situ reduction of AuCl 3 on a semiconducting single-walled carbon nanotube (sc-SWCNT) surface. In addition, the bipyridine (BPy) units in tube-wrapped polymers function as chelating sites for anchoring Au 3+ and AuNCs. The ultrasmall size of AuNCs was achieved by fast AuCl 3 diffusion and the anchoring function of BPy units. A slow diffusion or absence of BPy units resulted in AuNCs in larger sizes. The NC density was controlled by AuCl 3 feed amounts by varying the Au-to-BPy molar ratios. Density functional theory was applied to simulate the Au-BPy coordination. The fabricated nanocomposites exhibited a high Faradaic CO selectivity up to 86% at 25 mA/cm 2 and a high mass activity up to 5.61 A/mg (Au) at 100 mA/cm 2, which is the highest value reported so far in AuNC electrocatalysts for CO 2 reduction.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".