The Chemical Vapour Deposition of Tantalum - in long narrow channels
Bibliographic record
Abstract
Tantalum’s resistance to corrosion in hot acidic environments and its superior metallic properties have made it a prime solution as a construction material or protective coating to equipment intended for use in such harsh chemical and physical conditions. The high price of tantalum metal limits its use as a construction material for process equipment, with the cheaper alternative being the construction of equipment from steel and then protecting it with a thin but efficacious layer of tantalum. Chemical Vapour Deposition (CVD) is chosen as the most effective process to apply thin corrosion protective layers of tantalum because of the process’ ability to coat complex geometries and its relative ease to control. This work focuses on studying the CVD of tantalum in long narrow channels with the view that the knowledge gained during the project can be used to optimise the commercial coating process that Tantaline A/S and Alfa Laval (Sweden) use to manufacture tantalum coated plate heat exchangers. Experiments are done by coating the inner side of long, thin stainless steel tubes in the temperature range of 700 – 950 °C and pressure range of 25 – 990 mbar while using different reactant concentrations in order to document the effects of these properties on the tantalum deposition rates. A kinetic model is developed upon the foundation of a Computational Fluid Dynamics (CFD) and Thermal model in order to broaden the understanding of the process and to identify the key control parameters. The developed model fits well at temperatures below 900 °C and the entire pressure range, but fails above 900 °C due to a change in reaction mechanism. Furthermore, Scanning Electron Microscope (SEM) imaging is used to show that the morphology of the deposited tantalum has a large dependence on temperature and that there is a major change in morphology between 850 – 900 °C. The effects of system pressure and precursor partial pressure are also studied, and were found to have relevance to the tantalum distribution along the substrates but little effect on the structural morphology of the deposited layer. In the implemented mechanism of reaction, TaCl3 is found to have a lot of relevance such that it is the main precursor to the surface reaction and that the overall deposition rates follow its abundance. An experiment with a real plate heat exchanger is also done and the corresponding model implemented with satisfactory results.
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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 | 0.000 | 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 teacher head, 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".