Demands, potentials and economic aspects of thermal spraying with aqueous solutions: Presentation held at Thermal Spray of Suspensions & Solutions Symposium (TS4), Montreal, 2./3.12.2015
Bibliographic record
Abstract
In this contribution, the main aspects of thermal spraying with suspensions, which have to be considered in order to produce suspension sprayed coatings in an economical way, are presented. The economic efficiency of the process depends on the availability of suitable additional system components (suspension feeder, injectors), on the development and handling of stable suspensions, as well as on the high process stability for acceptance at industrial scale. Special focus is made on thedevelopment and processability of water-based suspensions of ceramic oxides. The use of water as a liquid media for preparing suspensions is often critically discussed due to the necessity of a higher heat input during spraying compared toalcoholic suspensions. In fact, the safe and environmental friendly manufacturing as well as lower production and transport costs clearly speak for the industrial use of aqueous suspensions. Recent devel-opments have demonstrated successful production and processing of highly concentrated aqueous suspensions (of 50 wt. % or more). The economic aspects in terms of deposition efficiencies and feed rates in relation to the solids content of aqueous suspensions of different ceramic oxides are discussed. In the case of alumina S-HVOF coatings feed rates between 15 to 35 g/min and deposition efficiencies up to 65–70% could be reached with aqueous suspensions. The coating hardness (850 HV0.3) did not change with increase of the suspension concentration from 35 to 50 wt. %. For high melting temperature S-HVOF coatings like chromia, yttria, or yttria-stabilized zirconia the deposition efficiencies (15–30%) and coating thicknesses deposited per pass (2–5 μm/pass) were lower than in the case of alumina. Cr2O3 S-HVOF coatings with microhardness values in the range 1150–1450 HV0.3, which were higher than those of the conventional APS coatings, were produced with different aqueous Cr2O3 suspensions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.097 | 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".