Recent Progress Toward Electrocatalytic Conversion of Nitrobenzene
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite that extensive efforts have been dedicated to the search for advanced catalysts to boost the electrocatalytic nitrobenzene reduction reaction (eNBRR), its progress is severely hampered by the limited understanding of the relationship between catalyst structure and its catalytic performance. Herein, this review aims to bridge such a gap by first analyzing the eNBRR pathway to present the main influential factors, such as electrolyte feature, applied potential, and catalyst structure. Then, the recent advancements in catalyst design for eNBRR are comprehensively summarized, particularly about the impacts of chemical composition, morphology, and crystal facets on regulating the local microenvironment, electron and mass transport for boosting catalytic performance. Finally, the future research of eNBRR is also proposed from the perspectives of performance enhancement, expansion of product scope, in-depth understanding of the reaction mechanism, and acceleration of the industrialization process through the integration of upstream and downstream technologies.
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.
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) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it