PFI:AIR-TT: Prototype Development of Recipe Optimization for Deposition and Etching (RODEo)

PFI:AIR-TT：沉积和蚀刻配方优化的原型开发 (RODEo)

• 批准号: 1701121
• 负责人: Roger Bonnecaze
• 金额: $ 19.97万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-15 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1701121&HistoricalAwards=false
• 关键词: PFI; AIR; TT; Prototype; Development

This PFI:AIR Technology Translation project focuses on translating a research code for plasma etch and process optimization into a user-friendly industrially validated software tool. This will reduce the costs of recipe development by over 65% and shorten time to market for the products of semiconductor tool and chip makers. A single semiconductor chip requires over 50 etching steps. Each of these etch steps is a unique chemical process that requires specifications of an exact process condition or recipe (e.g., pressure, temperature, chemical ingredients and amounts, and time in the etch or deposition tool). The underlying patent-pending methodology and software implementation for this project, Recipe Optimization for Deposition and Etching (RODEo), uses kinetic process models and statistical analysis to reduce the time and cost of process development by a factor of three as compared with current industrial standards. Greater than $1.2B is spent on etch and deposition process development per year. This cost is projected to grow as new technologies and smaller features require new materials and greater numbers of etch and deposition steps. By reducing the number of experiments necessary to create a recipe by a factor of three, RODEo can reduce this by $800M. Development of plasma-based semiconductor processes is extremely costly and time consuming, severely slowing technology growth and constraining semiconductor equipment and chip sales. This project addresses this technology gap as it translates the RODEo methodology from research discovery toward commercial application. RODEo uses Bayesian statistics to uniquely combine the physics-based models and experiments and the expert or so-called tribal knowledge of etch engineers to accelerate the process of recipe development. Elements to be created for commercial translation of the research code include: 1) 3D profile simulator to couple with the existing plasma model; 2) Database of etch chemistry models and kinetic parameters for ease of use; 3) Optimized code for increased computational speed; 4) User interface; and 5) Industry demo of RODEo recipe development for sidewall control for etch of a high aspect ratio trench, against methods used by one of our industrial partners. In addition, personnel involved in this project, including undergraduate, graduate and post-doctoral students, will receive experiences in technology translation through interactions and user feedback from our partners and future customers, which include Lam Research, Intel, and Tokyo Electron.This project is jointly funded by the Division of Industrial Innovation and Partnerships and the Division of Engineering Education and Centers; reflecting the alignment of this project with the respective goals of the two divisions and their programs.

这个PFI：AIR技术翻译项目的重点是将等离子体蚀刻和工艺优化的研究代码翻译成用户友好的工业验证软件工具。这将使配方开发成本降低65%以上，并缩短半导体工具和芯片制造商产品的上市时间。 单个半导体芯片需要50多个蚀刻步骤。这些蚀刻步骤中的每一个都是独特的化学工艺，其需要精确工艺条件或配方的规范（例如，压力、温度、化学成分和量、以及蚀刻或沉积工具中的时间）。 正在申请专利的基本方法和该项目的软件实现，沉积和蚀刻配方优化（牛仔竞技表演），使用动力学过程模型和统计分析，以减少工艺开发的时间和成本的三分之一，与目前的工业标准相比。 每年用于蚀刻和沉积工艺开发的费用超过12亿美元。随着新技术和更小的特征需要新材料以及更多的蚀刻和沉积步骤，该成本预计将增长。通过将创建配方所需的实验数量减少三倍，牛仔竞技表演可以减少8亿美元。 基于等离子体的半导体工艺的开发极其昂贵和耗时，严重减缓了技术增长并限制了半导体设备和芯片的销售。该项目解决了这一技术差距，因为它将牛仔竞技表演方法从研究发现转化为商业应用。 牛仔竞技表演使用贝叶斯统计学，将基于物理的模型和实验与蚀刻工程师的专家或所谓的部落知识独特地联合收割机结合起来，以加速配方开发过程。 为研究代码的商业翻译而创建的元素包括：1）与现有等离子体模型耦合的3D轮廓模拟器; 2）易于使用的蚀刻化学模型和动力学参数的数据库; 3）用于提高计算速度的优化代码; 4）用户界面;和5）牛仔竞技表演高纵横比沟槽蚀刻侧壁控制配方开发的工业演示，与我们的一个工业合作伙伴使用的方法进行对比。 此外，参与该项目的人员，包括本科生、研究生和博士后学生，将通过我们的合作伙伴和未来客户（包括Lam Research、英特尔和东京电子）的互动和用户反馈，获得技术翻译方面的经验。该项目由工业创新与合作部门和工程教育与中心部门共同资助;反映了该项目与两个司各自的目标及其方案的一致性。

项目成果

A cellular automata simulation of atomic layer etching

原子层蚀刻的元胞自动机模拟

• DOI: 10.1117/12.2297435
• 发表时间: 2018
• 期刊: Advanced Etch Technology for Nanopatterning VII
• 作者: Bonnecaze, Roger T.;Chopra, Meghali J.;Strotmann, Jan
• 通讯作者: Strotmann, Jan

A model-based, Bayesian approach to the CF4/Ar etch of SiO2

基于模型的贝叶斯方法对 SiO2 进行 CF4/Ar 蚀刻

• DOI: 10.1117/12.2297482
• 发表时间: 2018
• 期刊: Design-Process-Technology Co-optimization for Manufacturability XII
• 作者: Chopra, Meghali J.;Zhu, Xilan;Zhang, Zizhuo Z.;Helpert, Sofia;Verma, Rahul;Bonnecaze, Roger
• 通讯作者: Bonnecaze, Roger

Minimum reaction network necessary to describe Ar/CF4 plasma etch

• DOI: 10.1117/12.2297502
• 发表时间: 2018-03
• 作者: Sofia Helpert;Meghali Chopra;R. Bonnecaze