Sensor-Integrated Control for Rapid Thermal Chemical Vapor Deposition (RTCVD)

;​R o o t E n t y F W g C o m p o b j b W o r d d o c u m e n t O b j e c t P O O l 3 g的3 g-。/ 0 1 2 3 4 5 6 7 F Microsoft Word 6.0 Document MSWordDoc。6;​该合同是马里兰大学与位于罗利的北卡罗来纳州立大学的分包合同。这项工作的总体目标是展示一种传感器集成控制从硅烷中快速热化学气相沉积（RTCVD）多晶硅（poly Si）的方法，重点是控制沉积厚度和晶圆均匀性。该项目利用了实时传感器的先进技术，包括温度热法、温度均匀性热成像、厚度测量和过程环境监测的采样质谱法。通过高保真的热和流体流动模拟构建的降阶过程模型，以及基于物理的动态设备、过程和传感器模拟，是控制模型的基础。由此产生的控制沉积厚度和晶圆均匀性的运行-运行控制方法正在开发和实验验证，实时控制方法正在探索中。这些运行到运行的控制方法将扩展到实时控制。一种支持基本监督控制组件的架构正在进行演示，该架构使用基于物理的动态模拟来确定特定设备故障模式的传感器特征，并使用先进的算法作为干扰工具，用于检测传感器信号相关性和识别指示的设备/过程故障。马里兰大学的研究人员致力于模拟和控制，而北卡罗莱纳州立大学的研究人员则致力于传感器和多晶硅的快速热化学气相沉积。控制系统概念的实验验证将在北卡罗莱纳州立大学的集束工具沉积装置中进行。*** 0 0 Oh +' 0 $ H l D H, \\CLM15\SMURPHY$\WWUSER\TEMPLATE\NORMAL。如果你是我的朋友，我就会去找你，我就会去找你。9527576 sheronda murphy sherondaMicrosoft Word 6.0 2.0；e = e d d l l l l l l l 1 % d T G 9 l l lKrishnaprasad：该合同是马里兰大学与位于罗利的北卡罗来纳州立大学的分包合同。这项工作的总体目标是展示一种传感器集成控制从硅烷中快速热化学气相沉积（RTCVD）多晶硅（poly Si）的方法，重点是控制沉积厚度和晶圆均匀性。该项目利用了实时传感器的先进技术，包括温度热法、温度均匀性热成像、厚度测量和过程环境监测的采样质谱法。通过高保真的热和流体流动模拟构建的降阶过程模型，以及基于物理的动态设备、过程和传感器模拟，是控制模型的基础。由此产生的控制沉积厚度和晶圆均匀性的运行-运行控制方法正在开发和实验验证，实时控制方法正在探索中。这些运行到运行的控制方法

; R o o t E n t r y F W g C o m p O b j b W o r d D o c u m e n t O b j e c t P o o l 3 g 3 g - . / 0 1 2 3 4 5 6 7 F Microsoft Word 6.0 Document MSWordDoc Word.Document.6 ; 9527576 Krishnaprasad This award is the University of Maryland with a sub-contract to North Carolina State University at Raleigh. The overall goal of this effort is to demonstrate a methodology for sensor-integrated control of rapid thermal chemical vapor deposition (RTCVD) of polycrystalline silicon (poly Si) from silane with focus on controlling deposition thickness and across-wafer uniformity. The project exploits advances in real-time sensors, including pyrometry for temperature, thermal imaging for temperature uniformity, and sampling mass spectrometry for thickness metrology and process ambient monitoring. Reduced-order process models constructed from high fidelity heat and fluid flow simulations, together with physically-based dynamic equipment, process, and sensor simulations, are the basis for control models. Resulting run-to-run control methodologies for controlling deposition thickness and across-wafer uniformity are being developed and validated experimentally, and real-time control approaches are being explored. These run-to-run control approaches will be extendible to real-time c ontrol. An architecture to support a basic supervisory control component is being demonstrated, using physically-based dynamic simulation to determine sensor signatures of specific equipment failure modes, together with advanced algorithms as interference tools for detecting sensor signal correlations and identifying indicated equipment/process malfunction. The investigators at the University of Maryland provide the effort on simulation and control, while the investigators at North Carolina State University provide the effort on sensors and on rapid thermal chemical vapor deposition of polycrystalline silicon. The experimental proof of concept of the control system will be performed in the cluster tool deposition apparatus at North Carolina State University. *** 0 0 Oh +' 0 $ H l D h , \\CLM15\SMURPHY$\WWUSER\TEMPLATE\NORMAL.DOT S u m m a r y I n f o r m a t i o n ( , 9527576 SHERONDA MURPHY SHERONDA MURPHY @ X g @ @ X g @ Microsoft Word 6.0 2 ; e = e d d l l l l l l l 1 % D T G 9 l l l l l l l l l s 9527576 Krishnaprasad This award is the University of Maryland with a sub-contract to North Carolina State University at Raleigh. The overall goal of this effort is to demonstrate a methodology for sensor-integrated control of rapid thermal chemical vapor deposition (RTCVD) of polycrystalline silicon (poly Si) from silane with focus on controlling deposition thickness and across-wafer uniformity. The project exploits advances in real-time sensors, including pyrometry for temperature, thermal imaging for temperature uniformity, and sampling mass spectrometry for thickness metrology and process ambient monitoring. Reduced-order process models constructed from high fidelity heat and fluid flow simulations, together with physically-based dynamic equipment, process, and sensor simulations, are the basis for control models. Resulting run-to-run control methodologies for controlling deposition thickness and across-wafer uniformity are being developed and validated experimentally, and real-time control approaches are being explored. These run-to-run control approaches wi