Comparison of surface micro‐roughness and adaptation of titanium and cobalt chrome implant abutment fabricated by selective laser melting and conventional techniques
Bibliographic record
Abstract
PURPOSE: The objective of this study was to assess the surface micro-roughness and abutment adaptation of selective laser melting (SLM) implant abutments in comparison to cast and machined implant abutments. METHODS: Forty abutment specimens were divided equally into four groups according to the fabrication technique as follows (n = 10), Machined Ti alloy abutments (Control), Cast CoCr abutments, SLM-CoCr abutments, and SLM-Ti alloy abutments. Forty internal connection implants (Ø 4.0 ×10 mm, Superline™, Dentium Co., Seoul, Korea) were mounted in clear acrylic resin. Fabricated abutments were assessed for surface micro-roughness using a 3D optical noncontact surface microscope. Vertical and horizontal adaptation of the abutment with implant interface was assessed by using Bruker micro-CT. Data was assessed using analysis of variance and Tukey post hoc comparison tests for all the variables except vertical misfit was assessed using Kruskal-Wallis test. Pearson correlation was used to assess dependence between independent variable (surface roughness) and dependent variables (Horizontal misfit and vertical misfit). RESULTS: SLM-Ti abutments showed significantly rougher surface (p < 0.05) among the study groups. While SLM-CoCr abutments were smoother than Cast abutments with mean Ra of 1.30 ± 0.11 and 1.58 ± 0.17 μm, respectively (p < 0.05). For abutment adaptation, SLM-Ti abutments showed the highest horizontal misfit among the groups (p < 0.05). While, SLM-CoCr abutments (29.24 ± 11.11 μm) showed comparable (p > 0.05) horizontal misfit results with Cast (26.08 ± 3.93 μm) and machined (26.45 ± 7.33 μm) abutments. Comparable (p > 0.05) vertical misfit values between Cast CoCr (487.01 ± 40.34 μm), SLM-CoCr (358.38 ± 114.93 μm) and SLM-Ti (299.85 ± 172.88 μm) abutments were observed. A positive correlation was found between the surface roughness of the mating surfaces and abutment adaptation. CONCLUSION: SLM CoCr abutments exhibited low roughness and comparable abutment adaptation (vertically and horizontally) than cast (control) abutments. Therefore, SLM CoCr abutments should be clinically investigated as potential implant abutments for clinical use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 source (direct Gemma or distilled Codex), 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".