Fundamental Study of Particle Formation, Transport, Deposition and Filtration for Semiconductor Applications

Abstract

Nowadays, the major semiconductor manufacturing companies try to fabricate smaller nodes (up to ~2 nm) by using the current start-of-the-art EUV lithography system. As a result, the particle size of interest becomes smaller. Preventing and controlling particle contaminations is essential in the semiconductor manufacturing process to increase semiconductor yield. Examples of these unwanted nanoparticles in the semiconductor industry are airborne molecular contamination (AMC), haze, and deposited nanoparticles. For these reasons, to control and reduce nanoparticle contamination in the semiconductor manufacturing process, particle formation, transport, deposition, and filtration studies should be simultaneously investigated. The objectives of this study were to 1) demonstrate particle formation in a particle-free environment, 2) investigate particle deposition and transport characteristics in commercial gas pipelines, and 3) present a new analytical equation for calculating the pressure drop of nanofiber filter media. In Chapter 2, the detection method for methyl salicylate molecules which is one of the volatile organic samples by using soft X-ray and aerosol measurement techniques was described. The aromatic chemical compounds which have the benzene ring are well detected by the soft X-ray-assisted detection method which converts gas vapors to nanoparticles through the photochemical processes. This chapter reports the characteristics of the formation of the nanoparticles by describing the stage change during the soft X-ray reaction: particle-free mode; nucleation mode; transition mode; accumulation mode; and stable mode. The empirical calibration curves can predict ppbv-level methyl salicylate vapor concentrations by using particle number or volume concentration data obtained from the real-time aerosol detection instrument. In Chapter 3, nanoparticle transport through a sharp-bent tube, i.e., elbow connection, was systematically examined by using a particle size ranging from 3 to 50 nm. In the experiments, particle size and flow rate significantly affected the penetration efficiency. To be specific, the smaller particles which had higher diffusion coefficients were more likely deposited on the sharp-bent tube and the higher flow rate reduced the flow-directional nanoparticle residence time resulting in increased penetration efficiency. To explain the experimental penetration efficiency on the sharp-bent tube, characteristics of fluid flow on the sharp-bent tube were studied numerically. The flow field calculations showed that the recirculation pattern occurred at the corner of the sharp-bent tube, and the flow separation and reattachment were observed at the inner wall right after the bending point. Additionally, when compared to a higher Reynolds number, the intensity of the secondary flow was weaker at a lower Reynolds number as well as its center point was located farther from the tube wall. Therefore, the nanoparticle residence time on the sharp-bent tube became longer and a smaller number of particles penetrated the tube at a lower Reynolds number. Based on the experimental data, the penetration efficiency on the sharp-bent tube was predicted by the correlation fitting curve. The relative penetration efficiency on the sharp-bent tube was also obtained by comparing it to the penetration efficiency on the straight tube. The strong diffusion transport rate and weak advection transport rate induced more particle losses due to secondary flow after the bending point, resulting in decreased relative particle efficiency. The characteristics of fluid flow on a sharp-bent tube under various conditions were analyzed in Chapter 4. Numerical simulations for analyzing the particle deposition locations and patterns on a sharp-bent tube were conducted by using the modified single-particle tracking analysis based on aerosol mass flow rate. Through the numerical calculation, we showed that after the bending point in a sharp-bent tube, the faster axial velocity occurred near the outer wall, and the boundary layer at a high Reynolds number became thinner. Furthermore, the faster radial velocity near the tube wall was observed at less developed-flow regions at high Reynolds numbers owing to the stronger secondary flow. The nanoparticle deposition locations and patterns were systematically examined from various viewpoints including the cumulative number of deposited particles, local deposition enhancement factor, and particle deposition pattern according to azimuthal angles. We found that most of the nanoparticles were deposited on the outer wall right after the bending point owing to outward-sloping flow. Moreover, the difference in relative deposition efficiency along the azimuthal angles at each section in the sharp-bent tube was reduced as the Reynolds number increased. This is because the nanoparticles near the wall were well mixed due to the strong secondary flow at high Reynolds numbers. The objective of Chapter 5 is to investigate the penetration characteristics of sub-100 nm nanoparticles on a forked tube (tree-like branching tube) at Reynolds numbers from 370 to 2,000. The modified single-particle tracking analysis based on aerosol mass flow rate was employed for tracking individual particles. The particle deposition efficiency was compared with the experimental results to ensure the accuracy of the numerical analysis method. The flow and deposition characteristics of sub-100 nanoparticles were systematically analyzed by obtaining the contours of particle distribution, particle concentration, and particle ID on various cross-sections in a forked tube. Based on the results, we found non-uniform particle concentration, resulting in creating a particle-free zone after passing a bending point. In addition, we suggested the correlation equation for the deposition efficiency on a forked tube at various conditions, which can be simply presented by the Peclet number, and the equation covers the whole tested Reynolds number. Furthermore, the clear differences in deposition behaviors between the forked, straight, and single sharp-bent tubes were presented (dep,FT = 13.75Pe-0.3798). The usage of a correlation equation for a single-bent tube to determine the deposition efficiency in a forked tube (two consecutive elbow connections) overestimated the efficiency due to the non-uniformity of the particle distribution after the particle passes the first elbow. The model presented in this work can be expanded further for more complicated tubing systems and give insight into tracking particle contamination sources in various applications. Nanoparticle resuspension or removal efficiencies on forked tubes with various methods, e.g., pulsed air jet, ultrasonication, and acid dissolution, were evaluated in Chapter 6. We deposited particles on two different surfaces: 200 mm wafers and forked tubes. For depositing particles on 200 mm wafers, PSL particles were deposited by electrophoresis and direct deposition method. On forked tubes, fluorescent and silver nanoparticles were deposited by using the aerosol method, and pulsed air jet, and ultrasonication resuspension or removal efficiency for silver nanoparticles was evaluated. We confirmed that 50 nm silver nanoparticles were hardly resuspended by using the ultrasonication method, and particle removal efficiency is less than 10%. For validating particle deposition efficiency and low particle removal efficiency, we used ultrasonication and particle dissolution by acid extraction method. 40 nm silver nanoparticles were deposited by using the aerosol method. The particle removal efficiency of 40 nm silver nanoparticles is still less than 10%. Based on the series of experimental results for particle removal efficiency, we confirmed that the small size of silver nanoparticles is hardly resuspended through ultrasonication. In Chapter 7, a semi-empirical correlation curve for predicting nanofiber pressure drop was suggested. By applying the slip effect on the nanofiber surface, the airflows across the nanofiber filter media (0.005 ≤ α ≤ 0.100, and 30 ≤ df ≤ 300 nm) were simulated. We compared and discussed other theoretical models (Brown, 1993; Kuwabara, 1959) and empirical models (Bian et al., 2018; Davies, 1953) with current numerical results and the previous experimental results.