Issue Information: Plasma Process. Polym. 1/2024
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
Outside Front Cover: Plasma-activated CO 2 and CH 4 are expected to kinetically promote heterogeneous catalysis for effi cient gas valorization via mostly vibrational excitation.Highlighting the importance of plasma-surface interaction, comparatively analyzing which type of plasma and catalysts is the most promising, by which the superiority of fl uidized-bed dielectric barrier discharge reactor is confi rmed.The fl uidized bed with an enlarged catalyst surface and heat transfer augmentation enables better plasma-catalyst coupling and highly nonthermal properties.Fluidized-bed plasma catalysis reactor, powered by renewable energy, alternatively contributes to the electrifi cation of chemical processes and thus reduces the net CO 2 emission.For further details please visit the article by Xiaozhong Chen, Hyun-Ha Kim, and Tomohiro Nozaki (e2200207).Chemical conversion enhanced by cold plasma, that is, molecules that are excited or dissociated by energetic electrons, suff ers from the intrinsic problem that product molecules are also activated by the plasma, resulting in the backward reaction and/or consecutive reactions.Options to mitigate this problem are discussed, relying on removal of product molecules or protecting product molecules for the plasma.In the picture, this is presented by selectively putting NO molecules in the basket. Plasma-based conversions with in situ product removal
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.045 | 0.066 |
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