Additive manufacturing of AISI 304L stainless steel: A review of processing parameters and mechanical performance
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) has become a favorable method for producing 304L stainless steel (SS) for various industrial applications, which is owing to its favorable characteristics including corrosion resistance, mechanical performance, and design flexibility. This review paper presents a comprehensive overview of the processing factors along with the mechanical performance of AM-fabricated 304L SS (AM304LSS). Firstly a discussion is provided for the fundamental principles of AM techniques that are common for processing SS304L. This includes selective laser melting (SLM), laser beam powder bed fusion (LB-PBF), direct metal laser sintering (DMLS), directed energy deposition (DED), wire-and-arc additive manufacturing (WAAM). Subsequently, the impact of key processing factors i.e. laser power, and powder characteristics on the microstructure and mechanical properties of AM304LSS is presented. In addition, this article examines recent progress in process optimization strategies and post-processing techniques for improving and enhancing the mechanical properties and surface finish of AM 304L stainless steel components. Finally, significant insights are provided for researchers, engineers, and practitioners involved in the advancement and application of AM304LSS components.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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