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A Model of Silicon Nanocrystal Nucleation and Growth on SiO_2 by CVD

机译:CVD硅纳米晶核核切割和SiO_2的生长模型

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Silicon nanocrystals can be used in non-volatile memory devices to reduce susceptibility to charge loss via tunnel oxide defects, allowing scaling to smaller sizes than possible with conventional Flash memory technology. In order to optimize device performance, it is desirable to maximize the nanocrystal density and surface coverage, while maintaining sufficient inter-crystallite separation to limit electron tunneling between adjacent crystallites. Ideally, crystallite densities in excess of 10~(12) cm~(-2) with relatively narrow particle size distributions must be obtained, posing a significant challenge for process development and control. In order to facilitate development of such a process, a rate-expression-based model has been developed for the nucleation and growth of silicon nanocrystals on SiO_2 in a CVD process. The model addresses the phenomena of nucleation, growth, and coalescence and includes the effects of exclusion zones surrounding the growing nuclei. The model uses a phenomenological expression to describe the nucleation rate and assumes that following nucleation, crystallite growth is dominated by gas-phase deposition processes, analogous to CVD of polycrystalline silicon. The model-predicted time-evolutions of crystallite densities and crystallite size distributions are consistent with experimental distributions as measured by Scanning Electron Microscopy (SEM). By coupling the model to a reactor-scale model of polysilicon CVD, it is possible to predict variations in the crystallite size distributions at various locations across a wafer as a function of reactor settings (temperature, pressure, flow rates, etc...). This in turn can be used for process control and optimization in order to ensure uniform deposition of nanocrystals in a large-scale manufacturing environment.
机译:硅纳米晶体可用于非易失性存储器件,以通过隧道氧化物缺陷减少对电荷损耗的敏感性,允许通过传统的闪存技术缩放到较小的尺寸。为了优化装置性能,希望最大化纳米晶体密度和表面覆盖,同时保持足够的微晶间分离以限制相邻的微晶之间的电子隧道。理想情况下,必须获得超过10〜(12)厘米〜(-2)的微晶密度,必须获得相对窄的粒度分布,对过程开发和控制构成重大挑战。为了促进这种方法的发展,已经开发了一种基于速率表达的模型,用于CVD工艺中SiO_2上的硅纳米晶体的成核和生长。该模型解决了成核,生长和聚结的现象,包括围绕生长核的排除区的影响。该模型使用现象学表达来描述成核速率并假设在成核后,微晶生长以气相沉积方法为主,类似于多晶硅的CVD。微晶密度和微晶尺寸分布的模型预测的时间促进与通过扫描电子显微镜(SEM)测量的实验分布一致。通过将模型耦合到多晶硅CVD的反应堆级模型,可以在晶片上预测晶片上的各个位置的晶体尺寸分布的变化,作为反应器设置的函数(温度,压力,流速等......) 。这又可以用于过程控制和优化,以确保在大规模的制造环境中均匀地沉积纳米晶体。

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