Surface Roughness and Microhardness of Two Different Monolithic Materials after Chewing Simulation
Date
2018Author
Mahmoud, Wafaa Mahmoud Hamed
Hussein, Eman Mohamed Anwar "Supervisor"
Amin, Rania Adel "Supervisor"
Aboushahba, Mostafa ElSayed "Supervisor"
Metadata
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The purpose of this study was to evaluate weight loss, surface roughness and micro-hardness of two different monolithic materials (PICN and Lithium disilicate) after thermo-mechanical aging using chewing simulator. In this study, 6 blocks of each tested materials milled into cylinders using CAD/CAM system (CAM 5-S1 impression). Each cylinder were cut into discs (10mm X 2mm) using microtome. Samples were divided into two groups according to the material: ▪ Group (1) (n=14): Discs of PICN (polymer infiltrated ceramic network). ▪ Group (2) (n=14): Discs of Lithium disilicate Samples of each group were tested before chewing simulation for weight loss, surface roughness and micro-hardness. The samples were then inserted into the chewing simulator machine for wear test, each sample was opposed by a palatal cusp of upper first premolar. Samples were subjected to chewing simulation testing at a frequency of 60 cycle/min for (75,000 cycles) with a load of 5Kg (49 N) to test: 1- Weight loss: by measuring the difference in weight before and after chewing simulation by using an electrical balance. 2- Surface Roughness: by measuring the difference in sample surface roughness before and after chewing simulation by using 3D optical profilometry. 3- Micro-hardness: by measuring the difference in sample micro-hardness before and after chewing simulation by using Vickers hardness test. After chewing simulation; samples tested for weight loss, surface roughness and micro-hardness. From the results, it was found that: 1) PICN had higher mean weight loss than Lithium disilicate after chewing simulation. 2) PICN had higher mean surface roughness value than Lithium disilicate after chewing simulation. 3) Lithium disilicate had higher mean micro- hardness values than PICN after chewing simulation.