An application of finite element method in material selection for dental implant crowns
-
Abdullah T. Şensoy
,
Murat Çolak
Abstract
Materials used for dental crowns show a wide range of variety, and a dentist’s choice can depend on several factors such as patient desires, esthetics, tooth factors, etc. One of the most important issues for implant surgery is the primary stability and it should be provided to minimize the risks of screw loosening, failed osseointegration, or nonunion. The current study aims to present the Finite Element Analysis (FEA)-based material selection strategy for a dental crown in terms of reducing the aforementioned risks of dental implants. A virtual surgery mandible model obtained using MIMICS software was transferred to the ANSYS and material candidates determined using CES software were compared using FEA. The results indicated that Zr02+Y2O3 (zirconia) has shown a 12.79% worse performance compared to Au83-88/Pt4-12/Pd4.5-6 alloy in terms of abutment loosening. On the other hand, zirconia is the most promising material for dental crowns in terms of the stability of the bone-implant complex. Therefore, it may show the best overall performance for clinical use. Moreover, as suggested in this study, a better outcome and more accurate predictions can be achieved using a patient-specific FEA approach for the material selection process.
Research funding: No funding was received for the present study.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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© 2021 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Research Articles
- Attention based convolutional network for automatic sleep stage classification
- Emotion recognition using time–frequency ridges of EEG signals based on multivariate synchrosqueezing transform
- A novel signal to image transformation and feature level fusion for multimodal emotion recognition
- PVC arrhythmia classification based on fractional order system modeling
- A clinical set-up for noninvasive blood pressure monitoring using two photoplethysmograms and based on convolutional neural networks
- Virtual simulation of otolith movement for the diagnosis and treatment of benign paroxysmal positional vertigo
- Development and control of a home-based training device for hand rehabilitation with a spring and cable driven mechanism
- An easy and low-cost biomagnetic methodology to study regional gastrointestinal transit in rats
- Detection of adverse events leading to inadvertent injury during laparoscopic cholecystectomy using convolutional neural networks
- Comparison of a standardized four-point bending test to an implant system test of an osteosynthetic system under static and dynamic load condition
- An application of finite element method in material selection for dental implant crowns
Articles in the same Issue
- Frontmatter
- Research Articles
- Attention based convolutional network for automatic sleep stage classification
- Emotion recognition using time–frequency ridges of EEG signals based on multivariate synchrosqueezing transform
- A novel signal to image transformation and feature level fusion for multimodal emotion recognition
- PVC arrhythmia classification based on fractional order system modeling
- A clinical set-up for noninvasive blood pressure monitoring using two photoplethysmograms and based on convolutional neural networks
- Virtual simulation of otolith movement for the diagnosis and treatment of benign paroxysmal positional vertigo
- Development and control of a home-based training device for hand rehabilitation with a spring and cable driven mechanism
- An easy and low-cost biomagnetic methodology to study regional gastrointestinal transit in rats
- Detection of adverse events leading to inadvertent injury during laparoscopic cholecystectomy using convolutional neural networks
- Comparison of a standardized four-point bending test to an implant system test of an osteosynthetic system under static and dynamic load condition
- An application of finite element method in material selection for dental implant crowns
