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使用统计机器学习优化 YTZP 喷砂工艺中的表面粗糙度、相转变和剪切结合强度。

Optimization of surface roughness, phase transformation and shear bond strength in sandblasting process of YTZP using statistical machine learning.

机构信息

Mechanical Engineering Programme Area, Faculty of Engineering, Universiti Teknologi Brunei, Gadong, BE1410, Brunei Darussalam; Wellness Research Thrust, Universiti Teknologi Brunei, Gadong, BE1410, Brunei Darussalam.

出版信息

J Mech Behav Biomed Mater. 2024 Feb;150:106245. doi: 10.1016/j.jmbbm.2023.106245. Epub 2023 Nov 17.

DOI:10.1016/j.jmbbm.2023.106245
PMID:37992583
Abstract

Sandblasting process is often applied to roughen the intaglio of yttria tetragonal zirconia polycrystals (YTZP) surfaces for easy and quality adhesion and micro-shear retention with dentine/resin cements. Sandblasting process parameters have shown to influence, at different scales, surface roughness, phase transformation and shear bond strength, all of which are referred, herein, as performance characteristics. This study aimed to find the parametric settings of sandblasting parameters that could simultaneously optimize these performance characteristics, hypothetically testing the probability. YTZP surfaces were sandblasted at different levels of incidence angle (IA), abrasive particle size (AP), pressure(P) and sandblasting time (ST) following the Taguchi method based on the two-level parametric process settings (L(2)). Surface morphologies, roughness (SR), monoclinic content (MC), and shear bond strength (SS) were characterized by the SEM, average surface roughness, XRD, and shear bond strength tests, respectively. Rough surfaces containing scratches, plastic deformation streaks, micro cracks and pitting were observed. According to the Taguchi method, the same optimum sandblasting parametric setting maximized SR and MC but failed to maximize SS. Subsequently, the principal component analysis embedded in statistical machine learning was applied to find the optimum sandblasting parametric setting that maximized all the performance characteristics. The optimum sandblasting setting of IA = 45°, AP = 110 μm, ST = 20 s and P = 400 kPa predicted the maximum values of SR = 0.773 μm, MC = 36% and SS = 16.6 MPa. Analysis of variance confirmed AP and P as the most influencing parameters affecting all performance characteristics. Finally, these results provide a systematic and comprehensive route for optimizing sandblasting roughening of YTZP surfaces which can be adopted in adhesive dental and orthodontic industry.

摘要

喷砂工艺常用于粗糙化四方氧化锆多晶钇(YTZP)的凹版,以实现与牙本质/树脂水门汀的轻松、高质量的粘附和微剪切保持。喷砂工艺参数已被证明在不同尺度上影响表面粗糙度、相变和剪切结合强度,所有这些都被称为性能特征。本研究旨在寻找喷砂参数的参数设置,以同时优化这些性能特征,假设检验概率。根据田口方法,在两级参数过程设置(L(2))的基础上,YTZP 表面以不同的入射角(IA)、磨料粒度(AP)、压力(P)和喷砂时间(ST)水平进行喷砂。通过 SEM、平均表面粗糙度、XRD 和剪切结合强度试验分别对表面形貌、粗糙度(SR)、单斜含量(MC)和剪切结合强度(SS)进行了表征。观察到含有划痕、塑性变形条纹、微裂纹和麻点的粗糙表面。根据田口方法,相同的最佳喷砂参数设置最大程度地提高了 SR 和 MC,但未能最大程度地提高 SS。随后,应用嵌入统计机器学习的主成分分析来寻找最大化所有性能特征的最佳喷砂参数设置。IA = 45°、AP = 110 μm、ST = 20 s 和 P = 400 kPa 的最佳喷砂设置预测了 SR = 0.773 μm、MC = 36%和 SS = 16.6 MPa 的最大值。方差分析证实 AP 和 P 是影响所有性能特征的最具影响力的参数。最后,这些结果为优化 YTZP 表面的喷砂粗化提供了一种系统而全面的方法,可以在粘接牙科和正畸行业中采用。

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