模拟单片有源像素传感器:使用通用掺杂曲线的技术独立方法

Håkan WennlöfDeutsches Elektronen-Synchrotron DESY, Dominik DannheimCERN, Manuel Del Rio VieraDeutsches Elektronen-Synchrotron DESYUniversity of Bonn, Katharina DortCERNUniversity of Giessen, Doris EcksteinDeutsches Elektronen-Synchrotron DESY, Finn FeindtDeutsches Elektronen-Synchrotron DESY, Ingrid-Maria GregorDeutsches Elektronen-Synchrotron DESY, Lennart HuthDeutsches Elektronen-Synchrotron DESY, Stephan LachnitDeutsches Elektronen-Synchrotron DESYUniversity of Hamburg, Larissa MendesDeutsches Elektronen-Synchrotron DESYUniversity of Bonn, Daniil RastorguevDeutsches Elektronen-Synchrotron DESYUniversity of Wuppertal, Sara Ruiz DazaDeutsches Elektronen-Synchrotron DESYUniversity of Bonn, Paul SchützeDeutsches Elektronen-Synchrotron DESY, Adriana SimancasDeutsches Elektronen-Synchrotron DESYUniversity of Bonn, Walter SnoeysCERN, Simon SpannagelDeutsches Elektronen-Synchrotron DESY, Marcel StanitzkiDeutsches Elektronen-Synchrotron DESY, Alessandra TomalUniversity of Campinas, Anastasiia VelykaDeutsches Elektronen-Synchrotron DESY, Gianpiero VignolaDeutsches Elektronen-Synchrotron DESYUniversity of Bonn
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引用次数: 0

摘要

要优化具有复杂非均匀电场的 CMOS 传感器的敏感区,就必须进行精确模拟,而这可以通过静电场模拟和蒙特卡洛方法的结合来实现。本文以具有小收集电极和高电阻率外延层的 CMOS 像素传感器为例,介绍了此类模拟的指导原则。本文介绍了完整的模拟工作流程,以及可能存在的误区和如何避免这些误区。对于商用 CMOS 工艺来说,详细的掺杂情况是保密的,但本文介绍的方法提供了一种优化工具,它具有足够的准确性,可以在不了解专有信息的情况下研究不同传感器设计的传感器行为和权衡。工作流程从 TCAD 中的详细电场有限元法模拟开始,使用通用掺杂曲线。示例显示了模拟传感器不同参数变化的影响,以及加权场和瞬态脉冲模拟的创建。TCAD 模拟产生的场可导入 Allpix Squared MonteCarlo 模拟框架,该框架可进行高统计模拟,包括粒子相互作用的基本物理过程的随机波动建模。本文介绍了蒙特卡罗模拟设置示例,并描述了模拟链的不同部分。介绍了小型集电极 CMOS 传感器的仿真研究,并展示了测试光束望远镜配置中单传感器和多传感器的示例结果。所示研究通常是在测试光束活动中的传感器原型上进行的,并与测试光束数据进行了比较,结果显示最大偏差为 4%,证明该方法可以生成真实的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulating Monolithic Active Pixel Sensors: A Technology-Independent Approach Using Generic Doping Profiles
The optimisation of the sensitive region of CMOS sensors with complex non-uniform electric fields requires precise simulations, and this can be achieved by a combination of electrostatic field simulations and Monte Carlo methods. This paper presents the guiding principles of such simulations, using a CMOS pixel sensor with a small collection electrode and a high-resistivity epitaxial layer as an example. The full simulation workflow is described, along with possible pitfalls and how to avoid them. For commercial CMOS processes, detailed doping profiles are confidential, but the presented method provides an optimisation tool that is sufficiently accurate to investigate sensor behaviour and trade-offs of different sensor designs without knowledge of proprietary information. The workflow starts with detailed electric field finite element method simulations in TCAD, using generic doping profiles. Examples of the effect of varying different parameters of the simulated sensor are shown, as well as the creation of weighting fields, and transient pulse simulations. The fields resulting from TCAD simulations can be imported into the Allpix Squared Monte Carlo simulation framework, which enables high-statistics simulations, including modelling of stochastic fluctuations from the underlying physics processes of particle interaction. Example Monte Carlo simulation setups are presented and the different parts of a simulation chain are described. Simulation studies from small collection electrode CMOS sensors are presented, and example results are shown for both single sensors and multiple sensors in a test beam telescope configuration. The studies shown are those typically performed on sensor prototypes in test beam campaigns, and a comparison is made to test beam data, showing a maximum deviation of 4% and demonstrating that the approach is viable for generating realistic results.
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