标题: 内部参数扰动在金属闸高介电鳍式场效应电晶体特性影响之3D元件模拟研究
A Unified 3D Device Simulation of Intrinsic Parameter Fluctuation on High-k/Metal Gate Bulk FinFET Device
作者: 苏信文
李义明
Li, Yiming
电机工程学系
关键字: 鳍式场效应电晶体;内部参数扰动;3D Device Simulation;High-k/Metal Gate Bulk FinFET Device;Intrinsic Parameter Fluctuation
公开日期: 2012
摘要: 近年来,根据国际半导体技术蓝图(ITRS romap),电晶体尺寸不断的微缩,已经来到次奈米级世代,各种制程步骤皆更加的繁杂,每个步骤背后需要仰赖更多技术的克服,因此若想要电晶体得以维持摩尔定律(Moore’s Law)继续微缩,除了传统制程技术上的突破创新,电晶体结构上的创新,是次奈米级甚至奈米级电晶体势必要有的革新,而在这些千奇百怪、天马行空的几何新结构中,又以鳍式场效应电晶体(FinFET)最符合公司成本上的需求并且有效提升电晶体电特性不只一个世代。另外使得摩尔定律能够延续的一项非常重要技术金属闸极与高介电系数闸极绝缘材料,它已经是奈米级电晶体元件开发不可或缺的技术,然而,伴随着这些结构的创新技术的改良,是否衍生出新的扰动来源,而传统的扰动来源于新结构中是否得以压抑等,都是学术界、工业界非常关切的议题。本论文提出有效的模拟方法,探讨制程变异,以及随机参数的扰动于鳍式场效应电晶体的影响,相较于传统电晶体将获得多少改进,并且探讨将种种扰动来源同时考虑后对于电晶体的影响。
本研究应用蒙地卡罗方法三维度电晶体元件模拟方式进行实验,在制程变异扰动元件的部分,由于鳍式场效应电晶体为通道三维度之场效应电晶体,将分别
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探讨通道长、宽、高,各分量上的变异对于电晶体造成的影响,发现各分量之变异度与电晶体之临界电压有着不同程度上的关系,分析后发现各变异量与临界电压几乎呈现不同斜率的线性比例,而最后探讨各分量同时考虑于一电晶体,更有效模拟实际制程情况,提供学术界、工业界,对于奈米级电晶体在制程变异上所造成的扰动有所依据,并且藉由各分量影响临界电压的趋势,给予制程技术上压抑扰动的一些想法。
而在随机参数的部分,本研究探讨了三种扰动来源分别为随机缺陷、随机掺杂、随机功函数变异。于随机掺杂的部分,依照高斯分布产生三维度掺杂分布于通道内,并对于每个不同掺杂的元件进行分析;而随机缺陷的部分则是依照类似的模拟方法,随机产生二维缺陷分给每一个元件,藉此分析缺陷在通道及高介电系数闸极绝缘材料的介面所引起的现象,而对于两种随机扰动,本研究皆完整的分析随机的数量以及位置对于临界电压,饱和与截止电流,最大电导,电晶体输出电阻,汲极导致能障下降等特性扰动。随机功函数变异的部分,于模拟部分采用局部功函数变异的方法有别于传统平均功函数的作法,更能有效模拟实际制程,探讨金属晶格大小,位置、数量造成上述的直流特性扰动,并且探讨如何于结构上改进压抑扰动。最后同时考虑随机缺陷、随机掺杂、随机功函数变异于电晶体上的影响,并比较鳍式场效应电晶体与传统电晶体,各种特性扰动将获得多少压抑,于何种几何比例的结构下可以得到最佳效益的电晶体。
总之,本论文分析了包含闸极长度、宽度、高度缺陷的制程变异,以及随机参数中的随机缺陷、随机掺杂、随机功函数,完整分析造成电晶体变异的主要扰动源,并进一步探讨各扰动源于同一电晶体时的情况,比较传统电晶体与鳍式场效应电晶体的压抑效果;此论文结果对于下一世代电晶体特性分析极有助益。
For these years, according to ITRS roadmap, the size of device keeps scaling. It comes to nanodevice’s generation, each step of process technology has became more complicated, and they based on more breakthrough of technology. If we want to keep scaling based on Moore’s Law technology, In addition to the breakthroughs and innovations for traditional process technology, the innovation of transistor structure for sub-nano-or even nanoscale transistors is the key-point. In those strange, or abstract geometric new structure, the FinFET transistor outstandingly conform the demands of costs for company, and it effectively improve the characteristics of transistors to next generation even batter. To keep the Moore’s Law be continued, there is a very important technology; high-□ metal gate technology. And, it has become indispensable technology for the development of nanoscale transistors. No matter the part of academia or industry, we all wonder to know whether the traditional fluctuated source is suppressed by new device structure, and whether there are new fluctuated source accompanied with the innovation of new structure. This paper presents an effective simulation method to investigate the impact of process variation, and random parameter effect for FinFET structure, we would investigate the extent of improvement compared to traditional planar transistor, and we also research that put all the different fluctuated source into one transistor, then investigate the reference between all different fluctuated sources.
In this study, we do the experiment of device simulation with Monte Carlo method for three-dimensional transistor, for the part of device process variation, and due to the FinFET structure is three-dimensional transistor, we would investigate the influences of transistor from the channel length, width and high variation. We found there are different degree of relationships between each component of variability and threshold voltage. After the analysis, the result shows that there are different slopes of the linear proportion between each variation and threshold voltage. Finally, we discuss each component was considered in one transistor, we can simulate more closely to the situation of real process by this way. This study provides the academia and industry a basis that process variation induced fluctuation for nanoscale transistor, and we investigate the trends from the variations induced fluctuation of transistor characteristic, by the trends we provide some idea for suppressing technology.
For the part of random parameter, we discuss three fluctuated sources: random interface traps, random dopants and random workfunction variation. In the part of random dopants, we generate three-dimensional dopants in the channel based on Gaussian distribution, and analyze each device for different distribution of dopants; in the paet of random interface traps, we applied similar simulation method, we randomly generate two-dimensional traps divided into each device, to analyze the phenomenon of traps between channel and insulator of high-k material. And, both these two fluctuated source, we completely examined the effects RDs and Its number and position on device characteristic fluctuations including threshold voltage, on-/off-state current, maximum transconductance, output resistance of transistor, drain induced barrier lowering, gate capacitance. For the part of random workfunction fluctuation, we applied localized workfunction simulation method which is different from the traditional average workfunction simulation method, it could effectively simulate the situation of actual process. We investigate the metal lattice size, location, quantity, resulting in DC characteristics fluctuation, and explore ways to improve structure for suppressing fluctuation. Finally, we simultaneously consider the effects of RDs, Its and WKs, and we compare the characteristic between the planar transistor and FinFET structure, we examined each suppression of fluctuated sources, and try to know most effective transistor is composed in which geometric proportions.
In summary, this paper analyzes the process variation including gate length, width, and height defects; we also examine the random effects including RDs, Its and WKs. We completely analyze all chiefly fluctuated sources inducing transistor variability, and to further explore the situation when each fluctuation considered in one transistor, to compare the suppression between traditional planar transistor and FinFET structure transistor. We believe the results of this study are useful for the characteristic analysis of next generation transistor.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT079923510
http://hdl.handle.net/11536/49775
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