Metal powder atomization preparation, modification, and reuse for additive manufacturing: A review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Additive manufacturing (AM) processes are pivotal in various manufacturing industries due to their efficiency and ability to produce parts with complex structures and shapes. Metal powders, essential as feedstock for AM, especially in direct energy deposition (DED) and powder bed fusion (PBF) processes, have garnered significant attention from academia and industry. However, a comprehensive review focusing on the entire lifecycle of powders for AM is currently lacking. This review provides an exhaustive overview of powders used in AM, covering powder preparation methods, modification, and reuse. We critically discuss and compare various powder preparation techniques and review their properties, characterization methods, and impacts on AM processes. Here, we also summarize powder modification methods and improvements in powder properties and AM-produced parts. Finally, we address the reuse of powders in AM fabrication, including strategies, effects, and assessments of reusability post-manufacturing, which are crucial for reducing AM-associated costs. This work offers a state-of-the-art perspective in preparation, modification, and reuse of metal powders in AM.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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