Surface Basicity Controlled Degradation and Recoverability of Proton Conducting Perovskites, BaZr<sub>0.8</sub>Ce<sub>0.1</sub>Y<sub>0.1</sub>O<sub>3−δ</sub> and Ba<sub>0.5</sub>Sr<sub>0.5</sub>Ce<sub>0.6</sub>Zr<sub>0.2</sub>Gd<sub>0.1</sub>Y<sub>0.1</sub>O<sub>3−δ</sub>, in the Presence of CO<sub>2</sub>
Bibliographic record
Abstract
A fundamental understanding of carbonation kinetics is essential for the development of durable proton conducting electrolysis cells that can electrochemically convert CO 2 into fuels. The degradation behavior of two representative proton conducting perovskite materials, BaZr 0.8 Ce 0.1 Y 0.1 O 3−δ (BZCY811) with low cerium content and strontium-containing Ba 0.5 Sr 0.5 Ce 0.6 Zr 0.2 Gd 0.1 Y 0.1 O 3−δ (BSCZGY6211), was studied and analyzed using different solid–gas reaction models. These perovskite compositions are promising candidates for various electrochemical applications where a combination of high conductivity and high stability is required such as for direct CO 2 conversion to fuels (or syngas). The kinetic stability of these two compositions under CO 2 (and CO) was evaluated using X-ray diffraction, X-ray photoelectron spectroscopy, micro-Raman spectroscopy, CO 2 temperature-programmed desorption, and N 2 physisorption. Kinetic analysis of the isothermal solid–gas reaction indicated that BZCY811 powders were partially carbonated according to a first-order nucleation/nuclei growth mechanism, in which oxygen vacancies act as active nucleation sites. The degradation was not complete as a protective external carbonate layer was formed, which maintained the internal crystalline structure of BZCY811. In contrast, BSCZGY6211 was kinetically stable in the presence of CO 2 with no signs of degradation at high pressures (2.0 MPa). The higher kinetic stability of the latter composition is rationalized in terms of its higher surface acidity.
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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 | 0.025 | 0.013 |
| Meta-epidemiology (narrow) | 0.012 | 0.012 |
| Meta-epidemiology (broad) | 0.016 | 0.007 |
| Bibliometrics | 0.003 | 0.012 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.004 | 0.011 |
| Open science | 0.012 | 0.007 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".