Bibliographic record
Abstract
Recently, additive manufacturing (AM) became a promising technology to manufacture complex structures with acceptable mechanical properties. The laser powder-bed fusion (L-PBF) process is one of the most common AM processes that has been used for producing a wide variety of metals and composites. Invar 36 is an austenite iron-nickel alloy that has a very low coefficient of thermal expansion; therefore, it is a good candidate for the L-PBF process. This chapter covers the state-of-the-art for producing Invar 36 using the L-PBF process. The chapter aims at describing research insights of using metal AM techniques in producing Invar 36 components. Like most of nickel-based alloys, Invar 36 is weldable but hard-to-machine. However, there are some challenges while processing these alloys by laser. This chapter also covers the challenges of using the L-PBF process for producing nickel-based alloys. In addition, it reports the L-PBF conditions that could be used to produce fully dense Invar 36 components with mechanical properties comparable to the wrought Invar 36.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".