Enhanced CO selectivity for reverse water‐gas shift reaction using Ti<sub>4</sub>O<sub>7</sub>‐doped SrCe<sub>0.9</sub>Y<sub>0.1</sub>O<sub>3‐δ</sub> hollow fibre membrane reactor
Bibliographic record
Abstract
Abstract Reverse water‐gas shift reaction (RWGS) is important in the CO2 utilization cycle to convert carbon dioxide (CO2) and hydrogen (H2) to carbon monoxide (CO). In this work, the RWGS performance is evaluated by utilizing Ti4O7‐doped SrCe0.9Y0.1O3‐δ (SCY‐b) hollow fibre membrane reactor where H2 permeates through the SCY‐b proton conducting membrane and reacts with CO2 feed gas. Upon increasing the temperature from 750 to 950 °C, the CO yield increased from a negligible value to 14.82 %, when the sweep gas flow rate was 50 mL min−1 H2‐He (50:50 vol. ratio) and the feed gas flow rate was 100 mL min−1 CO2‐N2 (5:95 vol. ratio). The CO yield increase with the temperature increase reflects the enhanced H2 permeation flux through the SCY‐b membrane at higher temperatures. Higher CO2 concentration in the feed gas led to lower CO yield due to the higher amount of remaining CO2 in the outlet stream. The deposition of porous SCY or SCY‐b surface layer onto the hollow fibre outer circumference surface also increased H2 flux through the fibre relative to the non‐deposited one. Thermogravimetric and CO2‐temperature programmed desorption results further reveal that SCY‐b adsorbed CO2 at temperature above 500 °C due to the reaction between CO2 and SCY‐b material. Despite the formation of SrCO3 during RWGS, the SCY‐b hollow fibre membrane reactor still displayed a stable CO yield of around 14 % throughout the 6‐day continuous membrane reactor test.
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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) | 0.000 | 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) | 0.000 | 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 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".