2D Multivariate‐Metal‐Organic Frameworks (2D‐M<sup>2</sup>OF) for High Yield Ammonia Synthesis from Nitrate
Bibliographic record
Abstract
Abstract Ammonia synthesis from nitrate offers a promising approach for both nitrate removal and nitrogen recycling. In this study, a series of 2D multivariate‐metal‐organic frameworks (M2OFs) is synthesized, incorporating transition metals such as Co, Ni, Mn, and Ag to enhance these processes. These M2OFs exhibit remarkable ammonia production performance, with the highest performance achieved using the quaternary structure exceeding a current density of 1 A cm−2 at −0.8 V vs RHE, with an ammonia Faradic efficiency (F.E.) of ≈90%, and a yield rate of 68 mg h−1cm−2. Our findings reveal that the synergy among different metal centers in M2OFs provides a new efficient reaction pathway for nitrate reduction via surface hydrogen co‐adsorption, a mechanism not attainable with single‐metal MOFs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".