New breakdown data generation and analytics methodology to address BEOL and mol dielectric TDDB process development and technology qualification challenges
New breakdown data generation and analytics methodology to address BEOL and mol dielectric TDDB process development and technology qualification challenges
复制标题
新的击穿数据生成和分析方法可解决 BEOL 和摩尔电介质 TDDB 工艺开发和技术鉴定挑战
DOI：
--
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Choon
中科院分区：
文献类型：
--
作者：
Fen Chen;C. Graas;M. Shinosky;C. Griffin;R. Dufresne;R. Bolam;C. Christiansen;K. Zhao;S. Narasimha;C. Tian;Choon
MOL PC-CA隔离层和BEOL Low-k介电击穿数据通常与光刻、蚀刻、化学机械抛光、清洁和薄膜沉积等工艺步骤引起的多个变量有关。传统的强调每个芯片一个DUT或每个芯片多个DUT的方法，如果没有仔细的数据去卷积，就无法解决当前复杂的MOL PC-CA和BEOL Low-k介质击穿建模挑战。本文提出了一种新的大数据生成方法和一种分析程序方法，以合理地评估MOL和BEOL介质时变击穿数据。首次提出了一种新的诊断可靠性概念，用于全面的过程诊断和更准确的可靠性故障率确定。
Both MOL PC-CA spacer dielectric and BEOL low-k dielectric breakdown data are commonly convoluted with multiple variables induced by process steps such as lithography, etch, CMP, cleaning, and thin film deposition. The traditional method of stressing one DUT per die or multiple DUTs per die, without careful data deconvolution, is incapable of addressing current complex MOL PC-CA and BEOL low-k dielectric breakdown modeling challenges. In this paper, a new big data generation method plus an analytics procedure method is proposed to soundly evaluate both MOL and BEOL dielectric time-dependent-dielectric breakdown data. A new diagnostic reliability concept is for the first time proposed for comprehensive process diagnostics and more accurate reliability failure rate determination.