Evolution of Microstructure and Properties of Cold-Sprayed Copper Coatings: Influence of Feedstock Powder Characteristics, Process Parameters and Heat Treatment
Bibliographic record
Abstract
The Nuclear Waste Management Organization of Canada (NWMO) uses copper coatings to protect nuclear waste containers (used fuel containers - UFCs) from corrosion in deep geological repositories (DGRs). One fabrication method is cold spray, a solid-state powder consolidation technique that enables the deposition of high-strength, dense, thick coatings at high rates. However, as-sprayed (AS) coatings are often brittle, with mechanical properties strongly dependent on process parameters and feedstock powder characteristics, including the particle-to-critical velocity ratio (η) and surface oxide content. Their response to heat treatment is also influenced by their state in the AS condition.Particle size strongly affects the η ratio, as it is inversely proportional to both particle and critical velocity. This thesis investigates the effect of copper powder size distributions on the evolution of mechanical strength and ductility in fabricated coatings.First, coatings were fabricated by cold spraying copper powders with similar characteristics (morphology, oxygen content) but different size distributions (“fine” and “coarse”) at various particle velocity ranges. Increasing η improved interparticle bonding, enhancing the mechanical properties. However, coatings originating from the “fine” powder exhibited superior strength and ductility over “coarse” powder coatings, despite attaining similar η ratios. This was attributed to the presence of thick surface oxides on the “coarse” powder particles, which were entrapped at the particle-particle interfaces (PPIs) significantly limiting metallurgical bonding.Next, coatings with varying AS properties and/or feedstock powder particle size distributions were heat-treated in identical conditions. Interparticle bonding and properties improved overall due to sintering and interparticle oxide changes. However, coatings with initially superior AS properties did not always retain their advantage post-heat treatment, as the “as-sprayed” microstructure played a key role, with coarse particle size and thick interparticle oxides being found to be detrimental.The final chapter focuses on the technique used for the mechanical property evaluation, shear punch testing. As sprayed and heat-treated coatings, along with bulk copper specimens, were tested. Insights into effective ductility and fracture behavior of copper during testing are provided. Additionally, the expected mechanical property trends for differently processed bulk and coating copper samples are confirmed, demonstrating that heat-treated cold-sprayed copper can behave similarly to bulk copper during mechanical loading and fracture.These findings contribute to optimizing copper cold spray for critical applications depending on mechanical properties. Through the selection of appropriate process parameters, feedstock powders and heat treatment conditions, it is possible to manufacture coatings with good structural integrity and properties that meet the required standards
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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) | 0.001 | 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 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".