Thermal cycling on microstructure and mechanical properties of laser powder bed fusion manufactured IN738LC alloy
Bibliographic record
Abstract
Abstract This study investigated the impact of thermal cycling effects on the microstructure and mechanical properties of IN738LC alloy manufactured by laser powder bed fusion, considering different volumetric energy densities (VEDs) and interlayer times (ILTs) as part of the experimental parameters. The results show that low VED and long ILT samples displayed superior quality, with an average grain size of 10.97 μm and relatively low strain accumulation level. In contrast, samples with high VED and long ILT exhibit increased cracking and porosity, the average grain size is 14.63 μm and present higher strain accumulation degree. The nano‐primary MC phase within the alloy transformed into a spherical secondary MC phase inside the grain and a polygonal secondary MC phase on the grain boundary. In the low VED and long ILT, the mean equivalent diameter (MED) of MC carbide within the grain and on the grain boundary was 63 and 140 nm, respectively, the tensile strength was 1072 ± 21 MPa. By contrast, for the high VED and long ILT, the MED of MC carbide in the grain and on the grain boundary were 47 and 105 nm, respectively, and the tensile strength was 794 ± 31 MPa. The tensile strength of high VED and long ILT decreased by 26% compared with low VED and long ILT.
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".