雙極脈衝直流反應式濺鍍氮化鋁薄膜與光學發射光譜大數據分析輔助預測薄膜殘留應力最小化之研究;Minimizing film residual stress with in-situ OES big data using principle component analysis of deposited AlN films by pulsed DC reactive sputtering

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Title:	雙極脈衝直流反應式濺鍍氮化鋁薄膜與光學發射光譜大數據分析輔助預測薄膜殘留應力最小化之研究;Minimizing film residual stress with in-situ OES big data using principle component analysis of deposited AlN films by pulsed DC reactive sputtering
Authors:	盧德澐;Lu, Te-Yun
Contributors:	光機電工程研究所
Keywords:	殘留應力
Date:	2020-07-29
Issue Date:	2020-09-02 15:37:12 (UTC+8)
Publisher:	國立中央大學
Abstract:	本論文研究目的是氮化鋁（AlN）薄膜沉積在Si（100）上，並研究了隨沉積條件變化而產生的最小殘餘應力。鋁靶的脈衝直流反應濺射是在氮氣（N2）和氬氣（Ar）的氣體比例為N2：Ar的比例為15:15至60:15且功率為400W至1000W的條件下進行的。通過X光射線繞射分析（X-ray diffraction, XRD）、掃描電子顯微鏡（Scanning electron microscope, SEM）、表面輪廓儀(Alpha-Step)、傅立葉轉移紅外光譜（Fourier transform infrared spectroscopy, FTIR）光譜，並根據與薄膜微觀結構信息相關的光學發射光譜（Optical Emission Spectroscopy, OES）研究的大數據，沉積AlN薄膜的應力狀態會受到N2流量和功率的關鍵參數影響，這與主要的的自由基N2（315nm，336 nm），Al（394nm，396 nm）和Ar（750nm，811 nm）來構建分類器來預測殘餘應力。此外，殘餘應力（VRS）的建議值可以通過PC1-DEV（第一主分量方向上的標準偏差）方法來計算，以準確預測沉積AlN薄膜的應力狀態，區分為壓應力(tensile stress)或拉應力(compressive stress)，作為AlN薄膜沉積時，可以及時方式檢驗薄膜的品質。建立VRS(Value of Residual Stress)分類器來預測不同的應力狀態，即VRS平均值為0.12 / -0.21，再搭配上3σ限制來控制極限為0.03 / -0.09，可以用作拉伸/壓縮應力的即時監測工具，減少製程成本和時間，以提高機台使用效率。總而言之，通過大數據OES光譜的方法，再使用主成分分析（Principal Component Analysis, PCA）來減少維度，靠著通過製程電漿離子監測工具，來正確地預測殘餘應力。;In this study, aluminum nitride (AlN) thin films were deposited on Si(100) and investigated the minimization residual stress with varying deposition condition. Pulsed DC reactive sputtering of aluminum targets was carried out in gas ratio of nitrogen (N2) and argon (Ar) plasma with N2:Ar ratios from 15:15 to 60:15 and power 400W to 1000W. According to the large scale data of in-situ Optical emission spectroscopy (OES) study, the deposited films stress states can be highly affected by the critical processing parameters of N2 flow rate and power, which is consistent with radicals of interest N2 (315nm, 336 nm), Al (394nm, 396 nm) and Ar (750nm, 811 nm) such that a classifier can be built to predict residual stress. In addition, the proposed value of residual stress (VRS) can be calculated by PC1-DEV (the standard deviation in the first principal component direction) method for accurate prediction on the stress states of deposited films, i.e. compressive stress or tensile stress, which will provide valuable information of residual stress characterization as the in-situ monitoring tool for the AlN thin films deposition process. The VRS classifier was established to differentially predict stress state as mean VRS of 0.12/-0.21 and control limits of 0.03/-0.09, which can be used as the in-situ monitoring tool for tensile/compressive stress. In summary, it is suggested a methodology based on large data OES by which principal component analysis (PCA) to reduce dimension can be used to determine residual stress characterization from a simple measurement in-situ plasma monitoring tool.
Appears in Collections:	[Graduate Institute of opto-Mechatronics] Electronic Thesis & Dissertation

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