Incorporation of Nitrogen and Nano-diamonds into Diamond-Like Carbon Coatings on Ti-6Al-4V for Enhancement of Wear and Corrosion Resistance
Bibliographic record
Abstract
Titanium and its alloys are widely used for industrial applications. However, extended use of titanium in some applications has been severely limited due to its poor surface properties. Diamond-like carbon (DLC), which is a special group of amorphous carbon materials, can be highly beneficial in this regard. In the past decades, nitrogen incorporation into DLC has gained significant attention due to enhanced quality in terms of stress reduction, electrochemical and mechanical properties. However, so far the reports on the chemical structure of nitrogen-doped DLC have not been conclusive as nitrogen tends to form different bonding configuration with carbon depending on deposition methods. In the present thesis, a low energy End-Hall ion beam source (E-H source) was used to deposit nitrogen-incorporated DLC thin films on Ti-6Al-4V sheets. The adhesion, mechanical and electrochemical properties of DLC and nitrogen- incorporated DLC (N-DLC) were investigated. In order to improve interfacial adhesion, Ti-6Al-4V sheets were first treated in a microwave plasma enhanced chemical vapour deposition (MPCVD) reactor to grow nanodiamond particles on their surface. DLC and N-DLC coatings were then deposited on them by ion beam deposition. Silicon wafers were also used as the substrate for reference. Raman spectroscopy, X-ray absorption spectroscopy (XAS), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and optical profilometry were used to characterize the chemical and morphological structure of the coatings. Nanoindentation and Rockwell C testing were used for measuring the mechanical and adhesion properties, respectively. DLC showed a hardness value of 11 GPa, whereas N-DLC showed slightly lower hardness because of the increased graphitic bonding, demonstrated by Raman and XPS results. The optical profilometer measurements shows a decrease in surface roughness with nitrogen doping while Rockwell C testing shows that the nanodiamond particles grown on titanium alloy surface greatly enhance the adhesion of DLC and a small amount of nitrogen doping further improves the adhesion. N-DLC coated samples showed reduced coefficient of friction (COF) when measured against UMPHE balls. The COF showed monotonic decrease with increase in nitrogen concentration. Significant reduction in the wear rates were observed for N-DLC against SS 440C steel balls. The samples with N/C ratio of 0.27 show the lowest wear rate. The corrosion resistance was evaluated by Tafel polarization and Electrochemical Impedance Spectroscopy. N-DLC with pre-deposited nanodiamonds on titanium substrate alloys showed significant improvement in corrosion resistance compared to bare titanium alloy substrate in 0.89% NaCl solution.
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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".