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Research On Non-Resonant Tapping Mode Atomic Force Microscope System

Posted on:2021-02-02Degree:MasterType:Thesis
Country:ChinaCandidate:F H KongFull Text:PDF
GTID:2370330614961195Subject:Detection Technology and Automation
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With the rapid development of nanotechnology,atomic force microscopes(AFM)have been widely used in scientific researches in various fields.Compared with the traditional contact mode and tapping mode AFM,the non-resonant mode AFM can achieve better control accuracy of the interaction force control.Besides,various mechanical properties of the samples can be obtained while obtaining the surface morphology of the samples,so it is widely used in the field of nano-science.In this paper,a set of self-made non-resonant tapping mode AFM system was built by using a combination of background subtraction and synchronization algorithm,which can realize the morphology imaging of the tested sample while characterizing its various mechanical properties.And the minimum controllable force accuracy of the system was optimized so that the minimum controllable force was less than 50 p N.The main research contents are as follows:(1)The working principle of the non-resonant tapping mode AFM system was studied.First of all,the mechanical model of the interaction force between the probe and the sample was theoretically studied for this system,the detection method of the cantilever micro deflection was analyzed,and the non-resonance achieved by the background subtraction algorithm and synchronization algorithm used in this paper was analyzed.The imaging principle of tapping mode AFM was discussed in detail,and the extraction method of its mechanical properties was studied.(2)In order to improve the response speed and accessibility of the system,the optimal control strategy of the system was studied.By using the relay feedback test method and the beetle swarm optimization algorithm,the optimal control parameters of the system were obtained,which improves the system response speed and effectively solves the problem that parameters need to be repeatedly adjusted during the use of the system.Based on the Matlab/Simulink environment,a simulation model of the non-resonant tapping mode AFM system was built.The Ziegler-Nichols tuning parameter method and the beetle swarm optimization algorithm were used to obtain the PI control parameters of the system.The simulation results shows that by using the BSO tuning method,the response of the system is faster and error is narrower.(3)A non-resonant tap mode AFM system was built on the basis of theoretical and simulation researches.The geometric optical path of the system,the structure of the scanning head,and the hardware structure of the system were studied and designed,including the Z-direction stage,cantilever beam,sample scanning mechanism,controller,and host computer.The photoelectric detection circuit of the system was designed and researched.Through the theoretical analysis of the bandwidth and noise of the detection circuit,the op amp chip was selected.The noise simulation model of the detection circuit was built to analyze the noise and measure the actual noise.The system data processing unit was designed to ensure that the processing speed meets the system requirements.(4)The system was tested through a large number of experiments,and the experimental process and steps were discussed in detail.Mainly including: acquiring and analyzing the force curve of the sample to obtain its minimum controllable force;imaging the topography of the standard silicon grid to ensure the effectiveness and accuracy of the system under the condition of ensuring imaging resolution Verification;AFM,which is a more commonly used commercial tapping mode,and this system were used to scan a composite sample composed of two different materials,low-density polyethylene and polystyrene.Through the analysis of the experimental results,it is verified that the non-resonant tapping mode AFM system constructed in this paper can not only achieve high-resolution multi-information acquisition functionality.
Keywords/Search Tags:AFM, non-resonant tapping, beetle swarm optimization algorithm, Nano-characterization, background subtraction algorithm
PDF Full Text Request
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