發(fā)布時(shí)間：2018-08-10 19:46

【摘要】：隨著GLSI的高度集成化和立體化,互連線的特征尺寸越來(lái)越小,對(duì)平坦化的要求越來(lái)越高,在多層銅布線的化學(xué)機(jī)械拋光(Chemical Mechanical Polishing,CMP)過程中,拋光液和拋光工藝是影響拋光后晶圓的表面質(zhì)量和平坦化性能的兩個(gè)關(guān)鍵因素。拋光液中各成分含量的比例不同,工藝不同,均會(huì)導(dǎo)致不同的拋光速率和平坦化效果。因此如何獲得拋光液中各成分含量的比例和拋光工藝與拋光速率和平坦化效果之間的映射關(guān)系,并根據(jù)該映射關(guān)系得到滿足工業(yè)要求的拋光液各組成成分的最佳配比和工藝條件,是目前研究的一個(gè)前沿課題。針對(duì)該問題,本課題采用我校微電子所自主研發(fā)的以FA/O型螯合劑為主要成分的多層銅布線堿性拋光液,通過計(jì)算機(jī)智能優(yōu)化技術(shù)來(lái)分析優(yōu)化該拋光液中各成分含量的比例和拋光工藝,從而提高拋光速率和平坦化性能。首先,作為一個(gè)跨學(xué)科的研究課題,在研究了以化學(xué)作用為主的CMP堿性技術(shù)的反應(yīng)機(jī)理的基礎(chǔ)上,通過對(duì)計(jì)算機(jī)智能優(yōu)化技術(shù)中的誤差反向傳播(Back Propagation,BP)神經(jīng)網(wǎng)絡(luò)和人工蜂群(Artificial Bee Colony,ABC)算法的深入學(xué)習(xí)和研究,將BP神經(jīng)網(wǎng)絡(luò)和ABC算法兩者相結(jié)合,針對(duì)現(xiàn)有建模方法BP-ABC算法預(yù)測(cè)能力不佳的問題,提出了改進(jìn)后的建模方法:Back Propagation Niche Crowding Artificial Bee Colony算法,簡(jiǎn)稱BP-NCABC算法。通過仿真實(shí)驗(yàn)證明BP-NCABC算法在建模能力和泛化能力方面均優(yōu)于BP-ABC算法。其次,利用BP-NCABC算法對(duì)CMP實(shí)驗(yàn)數(shù)據(jù)進(jìn)行仿真實(shí)驗(yàn),建立拋光液各成分與拋光速率之間的關(guān)系模型,實(shí)現(xiàn)了對(duì)拋光速率的預(yù)測(cè)。同時(shí)利用該方法,針對(duì)300mm銅光片的實(shí)驗(yàn)數(shù)據(jù)建立了拋光液各成分和拋光工藝與拋光速率和片內(nèi)非均勻性(With-In-Wafer-Non-Uniformity,WIWNU)之間的關(guān)系模型,實(shí)現(xiàn)了對(duì)拋光速率和WIWNU的同時(shí)預(yù)測(cè),大大提高了在CMP工藝和材料的優(yōu)化過程中的效率。最后,利用統(tǒng)計(jì)學(xué)中的敏感性分析方法對(duì)以上兩個(gè)模型進(jìn)行敏感性分析,使拋光工藝和拋光液各組成成分及其交互作用對(duì)拋光速率的影響程度和對(duì)WIWNU的影響程度得到了量化。根據(jù)量化分析結(jié)果,結(jié)合實(shí)際實(shí)驗(yàn)驗(yàn)證發(fā)現(xiàn):在工藝條件為:壓力1.2psi,流量300ml/min,拋光機(jī)轉(zhuǎn)速為87rpm/min,拋光液各組成成分的配比為:磨料濃度為7vol.%,氧化劑濃度為0.5 vol.%,FA/O型螯合劑濃度為2.5 vol.%,活性劑濃度為3vol.%時(shí),拋光速率為907.39nm/min,WIWNU為2.92%,圖形片上拋光前后臺(tái)階高低差消除了大約3100?,拋光后表面狀態(tài)良好,粗糙度為0.386nm,缺陷明顯減少,實(shí)現(xiàn)了低壓下的良好的平坦化性能,滿足了工業(yè)發(fā)展對(duì)CMP技術(shù)的低壓低磨料的要求。
[Abstract]:With the highly integrated and three-dimensional GLSI, the characteristic size of the interconnect becomes smaller and smaller, and the requirement of planarization is higher and higher. In the (Chemical Mechanical polishing process of multilayer copper wiring, Polishing fluid and polishing process are two key factors that affect the surface quality and flatness of polished wafer. Different proportion of each component in polishing liquid and different technology will result in different polishing rate and flattening effect. Therefore, how to obtain the mapping relationship between the content of each component in the polishing liquid and the polishing process, the polishing rate and the flattening effect, According to the mapping relation, the optimum proportion and process conditions of the components of polishing liquid which meet the industrial requirements are obtained, which is a forward research topic at present. In order to solve this problem, we use the FA/O type chelating agent as the main component of the multilayer copper wiring alkaline polishing liquid, which is developed by our institute of microelectronics. In order to improve the polishing rate and flatting performance, the proportion of each component in the polishing solution and the polishing process are analyzed and optimized by computer intelligent optimization technology. First of all, as an interdisciplinary research topic, the reaction mechanism of CMP alkalinity technology with chemical action is studied. Through the in-depth study and research on the Back propagation BP neural network and the artificial bee colony (Artificial Bee algorithm in the computer intelligent optimization technology, the BP neural network and the ABC algorithm are combined. In order to solve the problem of poor prediction ability of existing modeling methods, BP-ABC algorithm, an improved modeling method called BP-NCABC algorithm, is proposed in this paper. Simulation results show that BP-NCABC algorithm is superior to BP-ABC algorithm in modeling ability and generalization ability. Secondly, the BP-NCABC algorithm is used to simulate the CMP experiment data, and the relationship model between the polishing liquid components and the polishing rate is established, which realizes the prediction of the polishing rate. At the same time, based on the experimental data of 300mm copper wafer, the relationship model between polishing liquid composition and polishing process, polishing rate and in-chip non-uniformity (WIWNU) is established, and the simultaneous prediction of polishing rate and WIWNU is realized. The efficiency of CMP process and material optimization is greatly improved. Finally, the sensitivity analysis of the above two models is carried out by using the sensitivity analysis method in statistics, which quantifies the influence of polishing process and polishing liquid components and their interaction on polishing rate and WIWNU. According to the results of quantitative analysis, The experimental results show that when the process conditions are as follows: pressure 1.2psi, flow rate 300ml / min, polishing machine rotating speed 87rpm / min, the composition ratio of polishing liquid is: abrasive concentration is 7vol.slug, oxidant concentration is 0.5 vol.r / FAO type chelator concentration is 2.5 vol.and active agent concentration is 3vol.percent, The polishing rate is 907.39 nm / min WIWNU is 2.92, the difference between the steps before and after polishing on the graphics chip is eliminated, the surface condition is good, the roughness is 0.386 nm, the defect is reduced obviously, and the flatting performance is realized at low pressure. Meet the industrial development of CMP technology low-pressure abrasive requirements.
【學(xué)位授予單位】：河北工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TN305.2

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