Additive manufacturing of refractory high-entropy alloys: A critical review of fundamentals and advances
Bibliographic record
Abstract
Refractory high entropy alloys (RHEAs) hold immense potential as superior alternatives to existing superalloys in the nuclear, energy, and aerospace industries. However, the fabrication of refractory alloys and RHEA parts has long been hindered by challenges associated with brittleness and a high oxidation rate. Fortunately, additive manufacturing (AM) presents a transformative opportunity for these materials. In contrast to conventional methods, AM offers the advantage of fabricating intricate and near-net-shape parts without restrictions caused by high melting points and severe high-temperature oxidation of refractories. Consequently, numerous studies have explored the feasibility of printing RHEAs for various applications, with the majority demonstrating improved mechanical properties and the ability to engineer microstructures and compositions. Nevertheless, challenges exist in the AM of these alloys, including the formation of microcracks, pores and elemental loss, impeding the realization of their full potential. This paper aims to delve into the fundamentals of RHEAs, encompassing the preparation of RHEA powders, the printability of these alloys and a critical assessment of their properties. To overcome the RHEA printing issues, this paper reviews the integration of thermodynamic modeling, phase diagram calculations, and numerical modeling, followed by an evaluation of the potential applications of RHEAs based on their properties and costs.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 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".