Comparison of the Properties of Additively Manufactured 316L Stainless Steel for Orthopedic Applications: 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
Owing to the low cost, ease of fabricability, good mechanical properties, corrosion resistance and biocompatibility of the 316L stainless steel (SS), this material is considered a suitable choice for orthopedic applications. Based on its properties and large utilization in orthopedics, this review focuses on the importance of additively manufactured (AM) 316L stainless steel. Owing to the large flexibility of the additive manufacturing process, the microstructure of the 316L SS can be easily tuned to modify the mechanical, corrosion and biological properties. To elucidate the benefits of additively manufactured 316L stainless steel, the properties of the selective laser melted (SLM) 316L stainless steel and wrought 316L stainless steel are compared. Particularly, the unique features of the SLM 316L stainless steel have been discussed in detail. The existing challenges associated with the additive manufacturing processes and implications of their widespread application are also highlighted. A brief overview of the biological properties and reactions sequence of the host immune system, i.e. tissue response, the activation of acute and chronic inflammatory processes and immunological reactions, is also provided to understand the reasons for implant failure or rejection by the body.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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