潔淨室低濃度污染物螯合冷凝捕集技術研究

Chelating & Chilling Impinger Method to Sample Low Concentration Contaminants for Cleanroom

郭啟文(Kuo Chi Wen)

指導教授 ： 張陸滿

國立臺灣大學/工學院/土木工程學研究所/博士(2017年)

https://doi.org/10.6342/NTU201701244

摘要

當半導體製程技術已經發展到奈米尺寸等級，現代科技廠房潔淨室所面臨的的挑戰之一，便是；即使潔淨室空氣經過水洗單元、超高效率濾網與化學濾網的重重洗滌過濾，仍無法完全去除低濃度的空氣污染物，而且以目前的衝擊瓶或被動沉積採樣技術而言，無法有效的採集捕捉低濃度的空氣污染物。
惟目前用來評估(evaluate)進口濃度變化下空氣污染物捕集效率的方法多為統計迴歸之經驗公式，這些經驗公式主要藉由大量的實測數據，來得到不同進口濃度狀態下，進出口濃度對數函數與破出時間( breakthrough time)的線性關係，或是由統計迴歸方法直接描述去除效率與進口濃度的函數關係。然而這些經驗公式推導的方法，並無法解釋為何空氣污染物濃度降低時會引致去除效率大幅折減的現象，非真正具備預測(predict)去除效率的能力。
本論文基於Fick第二定律以動態擴散原理推導出一數值理論模型，用以描述低濃度污染物的特徵行為，同時做為預測(predict)污染物捕集效率的基礎。本研究之動態擴散模型係利用有限元素方法拆解空氣洗滌過濾的連續過程，再就去除效率進行積分計算，即可由一已知之進出口濃度對(pair)，來推算任一進口濃度條件下，該系統污染物之去除效率。故藉由本理論模型的演算推導，在質傳模數不變的條件下，本研究發現：傳統空氣污染物洗滌方法，於結構上存在著捕集效率的極限問題，即便延長洗滌時間或增加洗滌路徑的長度，皆無法有效提升低濃度污染物的去除效率。
基於本研究的結論：若能突破氣液膜面擴散質傳的瓶頸，即可提高污染物的捕集效率。為此本研究亦發展一套「螯合冷凝捕集」方法，以改變空氣污染物的捕集途徑，藉由冷凝成核主動捕捉固態微粒來取代傳統氣液相間的被動擴散質傳，以驗證本研究的論點。舉12吋晶圓傳輸盒(Front Opening Unified Pod)內部的酸性氣態污染物採樣為例，本研究所提供之螯合冷凝捕集方法可測得的總酸濃度為目前商用離子電泳質譜儀(Ion-Mobility Spectrometry, Adixen APA 302)所測得濃度的約20倍。
本論文旨在構建一空氣洗滌過濾現象的數學理論模型，並據此結論發展改變質傳途徑的螯合冷凝捕集方法，用以提升低濃度空氣污染物的捕集效率，大幅增進低濃度污染物監測的解析能力。

關鍵字

效率預測 ； 動態擴散 ； 螯合 ； 冷凝衝擊瓶 ； 低濃度污染物

並列摘要

When technology note has been scaled down to nanometer level, semiconductor industry is facing serious challenges to overcome the problems of low concentration contamination in cleanrooms. Even after heavily washing and filtrating, low concentration air borne molecular contaminations still cannot be effectively neither sampled nor removed. Previous studies have found that air washing facilities suffer from low removal efficiencies in situating low inlet concentrations. The present methods to evaluate the efficiency of sampling air borne contaminants in terms of inlet concentration are using statistical regressions. These regressions are resulted from empirical data. Herein, linear relationships between the logarithmic functions of the inlet concentrations and breakthrough times are found. In addition, the removal efficiency as a function of the inlet concentration is illustrated. These empirical regression formulas do not explain why the reduction of the inlet concentration leads to the removal efficiency degradation, nor provide prediction capacity.
Therefore, based on Fick's second law, a numerical model is deduced by dynamic diffusion method for explaining the characteristic behavior of low concentration contamination in this study. Meanwhile, it lays ground for predicting sampling efficiency. Moreover, finite element method is used to dismantle the continuous process of air washing and filtrating. Thus, the contaminant removal efficiency at different inlet concentration can be estimated from a known inlet/outlet concentration pair. In order to support the deduction of the theoretical model proposed this study, chelating and chilling impinger sampling methods are developed. Empirical results demonstrate that the total acid concentration measured by the chelating and chilling impinger method is about 20 times of the concentration measured by the ion mobility spectrometer method. With the deduced model for predicting air washing and filtration efficiency and the developed chelating and chilling impinger sampling method for sampling low concentration contaminants, they enhance the ability of contamination control and facilitate the cleanliness monitoring in cleanrooms.

並列關鍵字

Efficiency prediction ； Dynamic diffusion ； Chelating ； Chilling impinger ； Low concentration contaminants

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