A nanoscale high reference material is a physical reference material with a specific value, mainly used for the transfer and calibration of relevant nanometric instruments. this paper develops a probe scanning atomic force microscopes (AFM) system for step height topography characterization. Firstly, the step standard template is proposed, and the computation time is reduced by iterative approach. Second, the principle of AFM and the roughness measurement method are investigated. Finally, the same step height is compared and measured using AFM. The results show that the maximum standard deviation of the AFM is around 0.015.
In this paper, a submicron linewidth measurement method based on computer microscopic imaging technology to improve the measuring precision is proposed. Firstly, the microscopic image of the standard line pair is taken at the magnification M, and the pixel representing distance (PRD) of the microscopic image is calibrated. Secondly, the noise of the image is eliminated by the median filtering technology, and then the minimum ambiguity criterion of direction information measurement is used to quickly identify the edge boundary points of linewidth. Then, the edge points of the linewidth are fitted and filled to form a regular geometry shape, which can be accurately located by using the cascaded Hough transform algorithm. Finally, in order to verify the validity of the method, several representative linewidths are selected on the standard sample plate to repeat the measurement nine times, the experimental results show that for line width greater than 2 μ m, the error of measuring linewidth with the method studied in this paper is less than 0.1 μ m. Therefore, this method reveals the possibility of high-precision measurement of linewidth through microscopic images, and makes it be a much better option to be employed for further micro-nano structures analysis applications.
In order to obtain high precision optical constants at in the ellipsometry measurement process, an optimization algorithm for solving the complex refractive index of nano films at visible wavelength is proposed. To improve the convergence rate and the ability to escape from local optimum of original algorithm, an Improved Particle Swarm Optimization (IPSO) has been proposed to deal with and analyze the ellipsometry parameters, this method combines the evolutionary algebraic attenuation factor with the adaptive genetic algorithm. The algorithm is used to calculate the film parameters of silicon dioxide nano film thickness standard template with standard value of 100.4±0.3 nm in this paper. The results show that the relative error of the calculation results of the optical constants refractive index error is less than 0.1 at visible wavelength. At the same time, it is verified by experiments that the IPSO algorithm model can effectively optimize the number of iterations and has the advantages of fast convergence speed and high measurement efficiency.
In order to obtain accurate nano-film characteristic parameters in the ellipsometry measurement process, an optimization algorithm for solving the thickness and complex refractive index of nano films by spectroscopic ellipsometry is proposed. An improved adaptive genetic algorithm (IAGA) has been proposed to process nano-film data, this method combines the evolutionary algebraic attenuation factor with the adaptive genetic algorithm. It can solve the problem that the genetic algorithm is premature and easy to fall into the local optimization. The algorithm is used to calculate the film parameters of silicon dioxide nano film thickness standard template with standard value of 49.7±0.4 nm in this paper. The results show that the relative error of the calculation results of the film thickness is less than 3%, and the error of refractive index is less than 0.1. At the same time, it is verified by experiments that the IAGA algorithm model can effectively optimize the number of iterations, and has the advantages of fast convergence speed and high measurement efficiency.
A method for solving bimetallic film coefficients using surface plasmon resonance (SPR) phase difference experimental data with fixed wavelength and multiple incident angles is presented to simplify and quickly solve the thickness and optical constants of metal films in this paper. The purpose is to extract unknown parameters from the phase difference between P- and S- polarizations of the reflected light occurred at the metal/dielectric interface. The results of bimetallic layer film’s thickness and optical constants obtained by our method are in better agreement with that of spectroscopic ellipsometer (SE) measurement method. Therefore, the approach reveals the possibility of retrieving the thickness and optical constants from the measurement results of the phase difference for multilayers, and makes it be a much better option to be employed for further film’s parameter analysis applications
In order to explore the key factors of the SPR effect, such as sensitive material, thickness of sensitive metal film, incident angle and wavelength, especially the affection of the incident light wavelength on the modulated reflectivity, calculations and analyses are carried out in this paper. Simulation results show that Ag has the lowest reflectivity when the incident light with shorter wavelength in visible wave band, Au has the lowest reflectivity with red light, and Cu has the best effect from 600 nm to infrared band. The ranges of thickness measurement for thin films can be obtained when the light source wavelength and incidence angle are fixed with the adopted metal sensitive material. Moreover, there is a special range of incidence angle that can put up a significant SPR effect phenomenon when there are definite metal films and wavelength of incident light.
A guided-wave surface plasmon resonance based sensor using graphene layer for detect the biomolecules has been analyzed. The use of waveguide layer between the gold film and graphene significantly improves the penetration depth and increases the sensitivity, then graphene layer is used to enhance the adsorption of the biomolecules. The thickness and materials of waveguide layer along with the number of graphene layer have been optimized to achieve the best performance of the sensor in terms of sensitivity. The highest sensitivity with 228.8°/RIU is obtained for visible wavelength with optimized thickness of gold and waveguide layer as 45nm and 10nm respectively while the materials of waveguide layer is chosen as zinc oxide and the optimum number of graphene layers is 2.We believe that this sensor could find potential applications in biological detection.
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