Selective laser melting of hybrid ex-situ/in-situ reinforced titanium matrix composites: Laser/powder interaction, reinforcement formation mechanism, and non-equilibrium microstructural evolutions
Bibliographic record
Abstract
Hybrid ex-situ/in-situ reinforced titanium matrix composites (TMCs) were fabricated by selective laser melting (SLM). The optimized pre-processed 5 wt% B 4 C/Ti-6Al-4V composite powder feedstock and the un-reinforced Ti-6Al-4V powder were consolidated using energy densities in the range of 50–75 J/mm 3 . Despite the full melting of the powder particles in the monolithic Ti-6Al-4V system, complete melting of the host Ti-6Al-4V constituent in the composite case took place by energy densities exceeding 62.5 J/mm 3 . Presence of the guest B 4 C particles surrounding the un-melted/partially melted host particles gave evidence of the non-efficient guest-to-host heat transfer. In-situ formation of (TiB + TiC) reinforcements was discussed based on a mechanism proposing dissolution rather than melting of the guest particles. The degree of dissolution was a significant function of the energy density and the guest particle size. Microstructural evolutions during SLM of 5 wt% B 4 C/Ti64 composite were studied, and the non-equilibrium solidification sequence was suggested based on the microstructural observations and the equilibrium solidification path. High cooling rates during SLM inhibited some of the liquid and solid-state transformations in the TMCs. This was confirmed by microstructural observations of the arc-melted parts fabricated by the same composite feedstock. The SLM processed TMCs showed 30–80% enhancement in microhardness compared to the unreinforced Ti64.
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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".