Synthesis, characterization, and evaluation of high selectivity mixed molybdenum and vanadium oxide catalysts for oxidative dehydrogenation of propane
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
Abstract Molybdenum and vanadium oxide catalysts with varied compositions (Mo/V = 1/1, 7/3, 8/2, and 9/1) were prepared using a modified citrate‐nitrate auto‐combustion method for the oxidative dehydrogenation of propane to propylene. These catalysts were characterized by BET‐technique, TPR, XRD, SEM, Raman, and UV spectroscopy. The effects of washing and supercritical CO 2 drying on catalysts during the preparation steps were investigated. Results show an interaction between the molybdenum and vanadium metal ions in all of these catalysts due to the presence of a peak at 785 cm −1 from the Raman study, which was assigned to a polymolybdovanadate species V‐O‐Mo vibration. This interaction could be efficient for alkane activation reaction. The catalysts were evaluated in a fixed bed micro‐reactor at temperatures in the range of 350–600 °C and at atmospheric pressure. The activity of the catalyst increased by increasing the molybdenum content. All of the catalysts in this study showed 100 % selectivity for propylene in the temperature range of 350–450 °C; however, the propylene selectivity was found to decrease with an increase in the temperature. The highest yield of 4.8 % with 100 % propylene selectivity was obtained for a catalyst with Mo/V ratio of 9:1 at 500 °C.
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) | 0.000 | 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 it