Elucidation of the Roles of Ionic Liquid in CO2 Electrochemical Reduction to Value-Added Chemicals and Fuels
Bibliographic record
Abstract
The electrochemical reduction of carbon dioxide (CO2ER) is amongst one the most promising technologies to reduce greenhouse gas emissions since carbon dioxide (CO2) can be converted to value-added products. Moreover, the possibility of using a renewable source of energy makes this process environmentally compelling. CO2ER in ionic liquids (ILs) has recently attracted attention due to its unique properties in reducing overpotential and raising faradaic efficiency. The current literature on CO2ER mainly reports on the effect of structures, physical and chemical interactions, acidity, and the electrode–electrolyte interface region on the reaction mechanism. However, in this work, new insights are presented for the CO2ER reaction mechanism that are based on the molecular interactions of the ILs and their physicochemical properties. This new insight will open possibilities for the utilization of new types of ionic liquids. Additionally, the roles of anions, cations, and the electrodes in the CO2ER reactions are also reviewed.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".