可控统计参数粗糙表面的粘附特性研究

发布时间：2018-05-15 22:28

  本文选题：粗糙表面 + 聚焦离子束加工　； 参考：《中国科学技术大学》2015年硕士论文

【摘要】：粘附现象的研究在微／纳机电系统、扫描探针显微镜、纳米操纵等领域有着极其重要的影响。对粘附力进行准确预测和有效的控制,以实现减小不利的粘附和有效地利用好的粘附,是微纳米工程技术的大问题。 实际表面并不是理想光滑的,其表面微／纳米结构与表面粘附特性密切相关。为了定量地分析结构参数和表面粘附特性的相互依赖关系,需要首先获得具有指定统计粗糙度参数的三维粗糙表面。 本文围绕具有可控统计参数的粗糙表面的粘附特性研究,进行了具有可控统计参数的粗糙表面的设计、加工与复制,及其表面粘附特性的表征和分析,主要进行了以下几个方面的研究工作： 1、具有可控统计参数的粗糙表面的模拟。实际的工程表面尤其是珩磨表面,具有较大的自相关长度。为了提高对具有大自相关长度的表面的设计效率和精度,在非线性共轭梯度法中引入了遗传算法。将傅里叶变换法和共轭梯度法进行对比,结果显示傅里叶变换方法可以准确模拟小自相关长度的表面,而对于相关长度较大的表面共轭梯度法模拟效果更好。结合遗传算法后计算效率明显提高。 2、具有可控统计参数的粗糙表面的加工。利用聚焦离子束在硅基底上加工了一系列具有不同高度分布和自相关长度的三维粗糙表面。主要针对加工模板的灰度等级进行了优化设计,灰度级的选择对加工质量有重要影响,随着模板灰度级增大表面更加平滑,根据64级灰度图加工的表面更满足加工精度的要求。然后,用原子力显微镜测试所加工样品的表面形貌,并对测试图与设计图做定量对比和分析。结果表明,样品加工精度较高,大部分表面参数相对误差控制在10%以内,并定性分析了造成误差的可能原因。聚焦离子束直接在硅基底上精确加工,有利于后续粗糙表面结构的转印及批量复制的探索。 用快速转印方法将这些结构复制到聚二甲基硅氧烷薄膜,并且应用参数评价和频谱分析等对模板和复制结构之间的原子力显微镜测量结果进行评价比较。复制表面和模板的典型参数能很好的吻合,比如均方根粗糙度误差范围在-6.4%到1.7%。由频谱分析可知复制样品和模板在低频段更加吻合。可控表面统计参数的粗糙表面加工及复制可为后续进行粗糙结构相关的表面功能特性实验和定量分析研究提供支持。 3、三维粗糙表面粘附特性的测量。在对原子力显微镜探针刚度标定的基础上,对加工和复制的具有可控参数的三维粗糙表面粘附特性进行测试,分别选用胶体球探针和普通探针两种方式。为探索粗糙表面粘附特性与表面复杂三维形貌特征之间的关系,及更好的预测表面粘附力提供了实验基础。并对三维粗糙表面与二氧化硅胶体球探针弹塑性接触做了初步有限元分析,为研究表面粘附特性与接触面积、结构参数之间的关系提供了参考。
[Abstract]:The study of adhesion plays an important role in the fields of micro / nano electromechanical systems, scanning probe microscopy and nano manipulation. Accurate prediction and effective control of adhesion force in order to reduce unfavorable adhesion and make good use of adhesion is a big problem in micro and nano engineering technology. The actual surface is not ideal smooth, and its surface microstructures / nanostructures are closely related to the surface adhesion properties. In order to quantitatively analyze the interdependence between structural parameters and surface adhesion properties, it is necessary to obtain a three-dimensional rough surface with specified statistical roughness parameters. In this paper, the adhesion characteristics of rough surfaces with controllable statistical parameters are studied, and the design, processing and replication of rough surfaces with controllable statistical parameters, as well as the characterization and analysis of surface adhesion properties are carried out. The main research work is as follows: 1. Simulation of rough surfaces with controllable statistical parameters. The actual engineering surface, especially the honing surface, has a large autocorrelation length. In order to improve the design efficiency and accuracy of surfaces with large autocorrelation length, genetic algorithm is introduced into the nonlinear conjugate gradient method. The comparison between the Fourier transform method and the conjugate gradient method shows that the Fourier transform method can accurately simulate the surface with small autocorrelation length, and the simulation effect is better for the surface conjugate gradient method with larger correlation length. The computational efficiency of genetic algorithm is improved obviously. 2. Machining rough surfaces with controllable statistical parameters. A series of three dimensional rough surfaces with different height distribution and autocorrelation length were fabricated on silicon substrate by focusing ion beam. The optimization design of the grayscale grade of the machining template is mainly carried out. The selection of the gray level has an important effect on the machining quality. With the increase of the gray level of the template, the surface is smoother, and the surface machined according to the gray-scale image of the 64-level can meet the requirement of machining precision. Then, the surface morphology of the processed samples was measured by atomic force microscope, and the quantitative comparison and analysis between the test and design drawings were made. The results show that the sample processing accuracy is high, the relative error of most surface parameters is controlled within 10%, and the possible causes of the errors are analyzed qualitatively. The accurate processing of focused ion beam directly on silicon substrate is beneficial to the further exploration of transfer printing and batch reproduction of rough surface structure. These structures were copied into polydimethylsiloxane films by rapid transfer printing, and the AFM results between templates and replicating structures were evaluated and compared by means of parameter evaluation and spectrum analysis. The typical parameters of the replicating surface and the template are in good agreement, for example, the RMS roughness error range from -6.4% to 1.7%. Spectrum analysis shows that the duplicated sample and template are more consistent in low frequency range. Rough surface processing and reproduction of controlled surface statistical parameters can provide support for surface functional properties experiments and quantitative analysis of rough structures. 3. Measurement of the adhesion properties of three-dimensional rough surfaces. Based on the calibration of the atomic force microscope (AFM) probe stiffness, the adhesion characteristics of the 3D rough surface with controllable parameters were tested. The colloidal ball probe and the common probe were used respectively. It provides an experimental basis for exploring the relationship between the adhesion characteristics of rough surfaces and the complex 3D surface morphology, and for better prediction of surface adhesion. The elastoplastic contact between 3D rough surface and silica colloidal ball probe is analyzed by finite element method, which provides a reference for studying the relationship between surface adhesion characteristics, contact area and structural parameters.
【学位授予单位】：中国科学技术大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TB306

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