Thermochemical Analysis of Molybdenum Thin Films on Porous Alumina
Bibliographic record
Abstract
Molybdenum (Mo) thin films (thickness <100 nm) were physically deposited by e-beam evaporation on a porous alumina substrate and were analyzed for their stability and reactivity under various thermal and gas conditions. The Mo thin-film composites were stable below 300 °C but had no reactivity toward gases. Mo thin films showed nitrogen incorporation on the surface as well as in the subsurface at 450 °C, as confirmed by X-ray photoelectron spectroscopy. The reactivity toward nitrogen was diminished in the presence of CO 2, although no carbon species were detected either on the surface or in the subsurface. The Mo thin films have a very stable native oxide layer, which may further oxidize to higher oxidation states above 500 °C due to the reaction with the porous anodized alumina substrate. The oxidation of Mo thin films was accelerated in the presence of oxidizing gases. At 600 °C in N 2, the Mo thin film on anodized alumina was completely oxidized and may also have been volatilized. The results imply that choosing thermally stable and inactive porous supports and operating in nonoxidizing conditions below 500 °C will likely maintain the stability of the Mo composite. This study provides key information about the chemical and structural stability of a Mo thin film on a porous substrate for future membrane applications and offers further insights into the integrity of thin-film composites when exposed to harsh conditions.
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.
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) | 0.001 | 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".