Thermally Treated Carbon Nanoparticles for Boosting Industrial CO <sub>2</sub> Reduction to Formate on a SnO <sub>2</sub> Electrocatalyst
Bibliographic record
Abstract
Carbon black (CB) has been well-documented as an effective catalyst support for enhancing the performance and cost-effectiveness of catalysts in various electrochemical reactions. However, studies of these materials as catalyst supports for the CO 2 reduction reaction are still limited. Therefore, in this study, we developed a simple approach involving the modification of supporting carbon black nanoparticles (∼29 nm) to improve the activity and stability of the SnO 2 catalyst under industrially relevant conditions. Carbon black, as the supporting material, underwent calcination at moderate temperatures (350–550 °C) in the atmosphere, and the effects of the thermal treatment on the catalytic performance of the commercial SnO 2 catalyst were examined. Electrochemical measurements revealed that SnO 2 supported on CB thermally treated at 450 °C (SnO 2 /CB-450) exhibited superior activity and stability at industrially relevant current densities compared with other samples. While the SnO 2 -only and nontreated CB-supported samples showed rapid performance decay, the SnO 2 /CB-450 electrode maintained a Faradaic efficiency above 80% after 4 h and above 70% after 12 h of electrolysis in 2 M KOH at 200 mA cm –2 . The impacts of the thermally treated CB on the electrocatalytic performance of SnO 2 were assessed using various morphological and structural analyses, revealing a thermal treatment-induced surface modification of the CB nanomaterial support that effectively enhanced electrical conductivity and promoted the interaction and charge transfer between the catalyst and support, thereby improving overall catalyst performance and stability. Despite improvements, stability remains challenging, and the chemical and morphological changes of the electrode during the reaction were investigated over time to better understand the issue. This work introduces a straightforward and scalable strategy to enhance the activity and stability of the SnO 2 catalyst by modifying the carbon black nanomaterial support, offering a practical and scalable implication for the electrochemical CO 2 reduction reaction at high current densities.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".