Steps Toward Automated Deprocessing of Integrated Circuits
Steps Toward Automated Deprocessing of Integrated Circuits
复制标题
集成电路自动解处理的步骤
DOI：
10.31399/asm.cp.istfa2017p0285
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
E. Principe
中科院分区：
文献类型：
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作者：
E. Principe
IC的去处理历史上采用各种机械和化学工艺工具与一种或多种成像模态组合来重建IC架构。在这项工作中，我们探讨了一个可扩展的编程工作流程，可以利用不断发展的技术在2D/3D成像，分布式仪器控制，图像处理，以及自动化机械/化学去处理技术的发展。初步研究涉及65 nm节点3.0 cm 2 Opteron IC处理器芯片的自动背面机械超薄，结合自动蒙太奇SEM成像和基于实验室的X射线断层扫描和微量分析。使用气体辅助等离子体FIB脱层对大至800 μ m × 800 μ m的区域进行了脱处理。将封装器件中的硅衬底在IC器件的1-2um内超薄化显著减少了去处理所需的时间量。与手工技术相比，计算机辅助背面超薄方法不仅提高了成功率，还允许首先通过高分辨率SEM对具有最小特征尺寸的致密下层进行成像，同时样品层最均匀。背面去处理具有额外的优点，即可以访问器件，同时保持其“活跃”以进行原位电气测试。正在进行的工作涉及通过桥接FIB-SEM仪器控制和近实时数据分析来增强具有“智能自动化”的去处理工作流程，以建立计算引导的显微镜套件。如本文所述，FIB-SEM平台与图像处理和微量分析平台之间的通用Python脚本API架构允许快速开发具有数据处理集成和反馈的定制编程仪器控制。目前的研究使用智能卡作为原型来开发自动化的工作流程。智能卡代表了一个很好的架构来讨论和开发这些方法，因为它们的面积比1cm 2的处理器小16倍，并且通常包含很少的层。然而，这些小形状因子嵌入式集成电路已迅速成为现代社会的广泛元素，并且它们的安全架构代表了一个重要问题。我们证明了第一次;断层重建的基础上自动背面超薄耦合到自动气体辅助等离子体FIB脱层。
Deprocessing of ICs historically employs a variety of mechanical and chemical process tools in combination with one or more imaging modalities to reconstruct the IC architecture. In this work, we explore the development of an extensible programmatic workflow which can take advantage of evolving technologies in 2D/3D imaging, distributed instrument control, image processing, as well as automated mechanical/chemical deprocessing technology. Initial studies involve automated backside mechanical ultra-thinning of 65nm node 3.0 cm2 Opteron IC processor chips in combination with automated montage SEM imaging and lab-based x-ray tomography and microanalysis. Areas as large as 800umX800um were deprocessed using gas-assisted plasma FIB delayering. Ultrathinning the silicon substrate in the packaged device within 1-2um of the IC device significantly reduces the amount of time required for deprocessing. The computer aided backside ultrathinning approach not only improves the success rate, as compared to manual techniques, it also allows the dense lower layers with smallest feature size to be imaged via high resolution SEM first, while the sample layers are the most uniform. Backside deprocessing has the additional advantage that it can be possible to access the device while keeping it “alive” for in-situ electrical testing. Ongoing work involves enhancing the deprocessing workflow with “intelligent automation” by bridging FIB-SEM instrument control and near real-time data analysis to establish a computationally guided microscopy suite. As described in the text, a common python scripting API architecture between the FIB-SEM platform and the image processing and microanalysis platforms permit rapid development of customized programmatic instrument control with data process integration and feedback. Current studies use smartcards as an archetype to develop automated workflows. Smartcards represent a good architecture to discuss and develop these methods because they are as much as sixteen times smaller area than a 1cm2 processor and typically containing far few layers. Yet these small form factor embedded integrated circuits have rapidly become a widespread element of modern society and their security architecture represents an important problem. We demonstrate for the first time; tomographic reconstruction based upon automated back-side ultra-thinning coupled to automated gas-assisted plasma FIB delayering.