Enhancing Perovskite Electrocatalysis of Solid Oxide Cells Through Controlled Exsolution of Nanoparticles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perovskite oxides have received a great deal of attention as promising electrodes in both solid oxide fuel cells (SOFCs) and solid oxide electrolyzer cells (SOECs) because of their reasonable reactivity, impurity tolerance, and tunable properties. In particular, exploration is still required for improving perovskite electrodes, which normally suffer from slow kinetics in electrocatalysis. Experimental studies have led to the development of new classes of perovskites with advanced characteristics and electrode kinetics at technical levels. In parallel with those developments, achievements in theoretical and computational studies have led to substantial understanding, at the atomic level, of their physicochemical properties and electrocatalytic behaviors. Their chemical and structural flexibilities enable perovskites to accommodate most metallic elements without destroying their complex matrix structures, thereby delivering a pathway to engineer their catalytic properties. In this Minireview, recent advances in perovskite electrodes are introduced, and perovskites with exsolved nanoparticles are discussed as enhanced electrocatalytic materials.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it