Silvaco Announces Expected Addition to Three US Russell Indexes
September 16, 2024
这位作者还没有写个人简历。
我们为 Gigi Boss 对 401 篇日志做的贡献感到骄傲。
September 16, 2024
2024年9月26日
在本次研讨会上,我们将为您介绍仿真软件Victory Atomistic,它以量子力学理论为基础,为专业TCAD环境中的二维晶体管原型开发提供了有力的支持。
2024年8月29日
在本次网络研讨会上,我们将为您介绍美光科技如何利用Silvaco的FTCOTM(Fab Technology Co-Optimization)平台来优化半导体工艺,以开发和制造先进的存储器。
August 7, 2024
2024年7月25日
FTCO基于实际生产工艺中的物理和化学机制,利用人工智能(AI)和机器学习(ML)生成精确的TCAD数字模型(数字孪生)。对于这种数字孪生模型,可以采用DoE方法进行测试和分析,而无需真实流片,从而大大节省了制造相关的时间和费用。
June 20, 2024
June 12, 2024
It is often the case that a design of experiments (DOE) is required to optimize the performance of a particular device. Sometimes this simply means tweaking the implant dose for threshold voltage or other minor adjustments, but in other cases it can mean tweaking such things as high energy deep well implants.
Recently a new diffusion model was introduced to Victory Process: the CMOS model. This model aims at taking on the challenges brought by the specificities of CMOS device processing such as steep temperature ramps, short annealings or shallow implantations.
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