Thermo-mechanical improvement of Inconel 718 using ex situ boron nitride-reinforced composites processed by laser powder bed fusion
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Bibliographic record
Abstract
Abstract Hexagonal boron nitride-reinforced Inconel 718 (h-BN/IN718) composites were fabricated using a laser powder bed fusion (LPBF) technique to treat a nanosheet-micropowder precursor mixture prepared in a mechanical blending process. Tailoring the BN in IN718 enhanced the thermal resistance of the composites, thereby dampening the sharpness of the melting temperature peak at 1364 °C. This is because the presence of the BN reinforcement, which has a low coefficient of thermal expansion (CTE), resulted in a heat-blocking effect within the matrix. Following this lead, we found that the BN (2.29 g/cm 3 ) was uniformly distributed and strongly embedded in the IN718 (8.12 g/cm 3 ), with the lowest alloy density value (7.03 g/cm 3 ) being obtained after the addition of 12 vol% BN. Consequently, its specific hardness and compressive strength rose to 41.7 Hv 0.5 · cm 3 /g and 92.4 MPa · cm 3 /g, respectively, compared to the unreinforced IN718 alloy with 38.7 Hv 0.5 · cm 3 /g and 89.4 MPa · cm 3 /g, respectively. Most importantly, we discovered that the wear resistance of the composite improved compared to the unreinforced IN718, indicated by a decrease in the coefficient of friction (COF) from 0.43 to 0.31 at 2400 s. This is because the BN has an exfoliated surface and intrinsically high sliding and lubricating characteristics.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 it