Advanced Electrochemical System for Energy Storage through CO<sub>2 </sub>conversion
Bibliographic record
Abstract
The extensive usage of fossil fuel as energy source has led to the increased atmospheric concentration of CO2, which is mainly responsible for the negatively intensified greenhouse effect upon our living habitat. Various pathways have been studied in order to alleviate the negative effects of CO2 emission; electrochemical reduction of CO2 is considered as one of the promising method to effectively reduce CO2 emission. The process involves the conversion of CO2 to useful chemicals and fuels using high temperature solid oxide electrolysis cells (SOECs), these devices can run in the opposite direction in solid oxide fuel cells but utilize similar concepts, and involve materials challenges and operating conditions to achieve ‘Power to Fuels’. It is well known that CO2 molecules are very stable so that high energy input is required for cathodic reaction to proceed. The cathodic reaction, therefore, plays a vital role in the overall cell performance and so far, extensive investigations have been conducted to develop the advanced cathode materials with high catalytic activity and stability. Among various types of catalysts for SOECs, perovskite-based materials have attracted world wide research efforts as the mixed ionic and electronic conductors through introducing proper doping elements into perovskite lattice during synthesis process. Nonetheless, the cathodic material thus developed still suffer from relatively lower catalytic activity compared to conventional nickel-based cermets. In this work, three strategies are adopted to improve their performance of CO2 electrochemical reduction. It has been demonstrated that the perovskites with exsolved nanoparticles anchored on the surface of matrix exhibit excellent catalytic activity in comparison with the conventional ones. As a facile in-situ process, exsolution can significantly increase the number of reaction sites by forming uniformly dispersed active nanoparticles and at the same time, can efficiently impede agglomeration of nanoparticles under high temperature. Therefore, the perovskite with exsolved nanoparticles is a promising cathode material that can enhance the overall performance of CO2 reduction in an electrochemical cell.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".