1997
DOI: 10.1016/s0167-9317(96)00052-4
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Statistical metrology for characterizing CMP processes

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Cited by 13 publications
(9 citation statements)
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“…[16][17][18] Despite recent advances in CMP, some manufacturing concerns associated with successful implementation of CMP remain to be overcome. [16][17][18][19][20][21][22][23] In theory, CMP can achieve global planarity, but the problem of within wafer nonuniformity (WIWNU) still remains as one of the major operation concerns. WI-WNU indicates the variation in the surface thickness across the wafer radial position, especially on the edge.…”
Section: Multizone Cmpmentioning
confidence: 99%
“…[16][17][18] Despite recent advances in CMP, some manufacturing concerns associated with successful implementation of CMP remain to be overcome. [16][17][18][19][20][21][22][23] In theory, CMP can achieve global planarity, but the problem of within wafer nonuniformity (WIWNU) still remains as one of the major operation concerns. WI-WNU indicates the variation in the surface thickness across the wafer radial position, especially on the edge.…”
Section: Multizone Cmpmentioning
confidence: 99%
“…CMP polishing process is required for planarization of wafer surface, as lack of planarity may lead to insufficient depth of focus [8]. The topography variation of wafer surface after CMP is closely related to the feature density distribution [9,10]. Given the feature density distribution, a 2-D low-pass filter model proposed by Ouma et al is widely used to estimate the post-CMP topography variation [11].…”
Section: Density Optimizationmentioning
confidence: 99%
“…Initial investigations of oxide thickness included development of a fingered electrical capacitive test structure, as illustrated in Fig. 4, from which the oxide thickness between two metal layers could be inferred using TCAD tools in conjunction with a large volume of electrical probe measurements (5)(6)(7)(8)11).…”
Section: A Test Structure Designmentioning
confidence: 99%
“…While we discussed the connection to circuit performance evaluation in this paper, we believe that statistical metrology methods are also extremely powerful in developing and optimizing advanced process technology (e.g. the development of optimal CMP processes (10,11,12,23,29) or pads that minimize pattern dependencies), as well as in equipment selection and evaluation, and in process control. For example, CMP models are enabling more time and resource efficient processes which minimize the production of waste by-products in CMP.…”
Section: Summary and Future Workmentioning
confidence: 99%