Mechanical and tribological properties of (AlCoCrNiSi)100−xNx thin films
Bibliographic record
Abstract
High entropy thin films of (AlCoCrNiSi)100−xNx were deposited on silicon wafers using a pulsed DC magnetron sputtering technique, with nitrogen gas flow ratios (RN) of 0, 0.33, and 0.50. The structure and properties of these films were analyzed for elemental composition, surface and cross-sectional morphologies, microstructure, roughness, and mechanical properties. The coatings were primarily composed of an amorphous structure with a minor presence of a BCC structure and exhibited periodic variations in chemical composition from the substrate to the free surface. An increase in RN enhances crystallinity of the materials. Nanoindentation results showed that the films deposited at RN = 0.50 displayed the highest hardness (10.7 ± 0.5 GPa) and reduced modulus (176 ± 5 GPa), which were the highest among the films. Microtribology testing was conducted using a 20 μm radius spherical diamond tip under ambient air and normal loads ranging from 0.5 to 9 mN. Worn surfaces were characterized using atomic force microscopy. The coefficient of friction was evaluated to investigate the elastic and plastic behaviors of films using Schiffmann’s model. The coating without nitrogen displayed a predominant plastic behavior during the initial cycles, while the coating deposited at RN = 0.33 demonstrated a more elastic behavior, particularly at lower loads.
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".