Lithium Vacancy‐Tuned [CuO<sub>4</sub>] Sites for Selective CO<sub>2</sub> Electroreduction to C<sub>2+</sub> Products
Bibliographic record
Abstract
Abstract Electrochemical CO 2 reduction to valuable multi‐carbon (C 2+ ) products is attractive but with poor selectivity and activity due to the low‐efficient CC coupling. Herein, a lithium vacancy‐tuned Li 2 CuO 2 with square‐planar [CuO 4 ] layers is developed via an electrochemical delithiation strategy. Density functional theory calculations reveal that the lithium vacancies (V Li ) lead to a shorter distance between adjacent [CuO 4 ] layers and reduce the coordination number of Li + around each Cu, featuring with a lower energy barrier for COCO coupling than pristine Li 2 CuO 2 without V Li . With the V Li percentage of ≈1.6%, the Li 2− x CuO 2 catalyst exhibits a high Faradaic efficiency of 90.6 ± 7.6% for C 2+ at −0.85 V versus reversible hydrogen electrode without iR correction, and an outstanding partial current density of −706 ± 32 mA cm −2 . This work suggests an attractive approach to create controllable alkali metal vacancy‐tuned Cu catalytic sites toward C 2+ products in electrochemical 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".