Nanostructured Ni(Zn)–Al2O3 cermet particle synthesis in high-energy mechanical alloying method (CG-3:IL07)
Bibliographic record
Abstract
Ceramic-metallics (cermets) have emerged as an important class of composite material combining favorable properties of their constitutive phases. In this work, nanostructured cermet Ni(Zn)–Al 2 O 3 composition was synthesized using the high-energy mechanical alloying (HE-MA) method to be deployed as a cold spray deposition powder feedstock . Pre-milled Ni(Zn) alloy particles were mechanically mixed followed by milling in a SPEX™ 8000 M High Energy Ball Mill at a fixed 1050 rpm. The material design-of-experiment (DoE) involved two design compositions (30 wt% and 50 wt% α-alumina) with two substitutional alloy compositions, Ni(5 wt%Zn) and Ni(10 wt%Zn), along with milling time as a process variable. Microstructural characterization confirmed the embedment of nanoscale Al 2 O 3 grain in micron-scale Ni(Zn) alloy particles. Additionally, EBSD analysis of Ni(Zn) alloy particles revealed that Ni(5 wt%Zn) experienced more uniform plastic deformation , work hardening and subsequent fracturing when compared to Ni(10 wt% Zn) alloy particles. The particle size measurement was carried out by laser diffraction showed that the cermet particles milled for 4 h had the desired size range for the objective of cold spraying. Also, the embedment of alumina into the Ni(Zn) alloy matrix and thereby, homogenization of cermet particles enhanced with the increase in milling time.
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 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 | 0.001 |
| 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".