Torsional and Bending Properties of V Taper 2H, ProTaper NEXT, NRT, and One Shape
Bibliographic record
Abstract
Nickel-titanium (NiTi) rotary files have enabled efficient root canal preparations that maintain the canal center with fewer aberrations compared to hand files. However, NiTi rotary files are susceptible to fracture, which can thereby compromise root canal treatment. Therefore, NiTi files have been developed to enhance fracture resistance by modifying design and thermal treatment. The objective of this study was to compare the torsional fatigue resistance and bending resistance of NiTi files manufactured from different alloys and treatments. ProTaper NEXT X2 (PTN; M-wire), V taper 2H (V2H; controlled memory wire), NRT (heat-treated), and One Shape (OS; conventional alloy) instruments of tip size #25 were compared. Torsional fatigue was evaluated by embedding the 3 mm tip of each instrument (N = 10/brand) in resin and the repetitive application of torsional stress (300 rpm, 1.0 N·cm) by an endodontic motor with autostop when the file fractured. The number of loading cycles to fracture was recorded and analyzed by Kruskal–Wallis and Mann–Whitney U tests with Bonferroni’s correction. Bending resistance of the instruments was tested using a cantilever bending test to the 3 mm point from the tip (N = 10/brand). The stress was measured when deflection of 3 mm was subjected and statistically analyzed with a one-way analysis of variance and Tukey’s honest significance difference test (α = 0.05). V2H withstood the highest number of load applications during torsional fatigue testing ( p<0.05 ), followed by NRT, PTN, and OS, where the differences between NRT and PTN ( p=0.035 ) and between PTN and OS ( p=0.143 ) were not statistically significant. V2H showed the lowest bending stiffness, followed by NRT, PTN, and OS ( p<0.001 ). Thermal treatment of NiTi wire resulted in improved mechanical properties, and controlled memory wire provided improved flexibility and torsional fatigue resistance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".