Utilizing computer simulations with physics-based models to develop and optimize semiconductor device technology.
Modern technology computer-aided design (TCAD) technologies have been around now for years. Yet, many semiconductor engineers still run experiments directly on wafers to examine chip fabrication processes and device operation.
While it can be challenging to become proficient in TCAD, conducting experiments on wafers isn’t exactly easy, nor is it quick or cost-effective to do. As with so many other aspects of chip design and verification, doesn’t it make sense to automate the process for better productivity and results?
TCAD tools represent a branch of EDA and utilize computer simulations with physics-based models to develop and optimize semiconductor device technology. As chipmakers move to smaller geometries, certain design considerations and materials that worked well at older process nodes may no longer be effective at the more advanced nodes.
Read on to learn why TCAD technologies should be an integral part of your electronic design automation (EDA) flow and get details on how industry/academia collaboration in this realm can support the workforce development that’s integral to moving the semiconductor industry forward.
TCAD tools offer a way to experiment and determine what works and what doesn’t work at different process nodes. The same explorations and optimizations can be done via experimentation with silicon wafers, but this is time-consuming, expensive, laborious and, often, less insightful.
Used most heavily at the R&D level and for pathfinding by foundries and chipmakers, TCAD tools have enabled Moore’s law for a long time. Early on, 2D device simulation tools were used for single transistor-level simulations of planar CMOS to determine how to overcome scaling challenges.
As transistor sizes have shrunk, the physics for continued Moore’s law scaling grew more complicated, leading to new transistor architectures such as finFETs and, eventually, interest in 3D stacking. TCAD tools are used to model these new designs and help determine how to optimize them for power, performance, and area (PPA), including in the face of process variability that can result in electrical noise. Its use also applies to other areas, including power electronics, RF, and CMOS image sensors.
TCAD tools can be grouped into three categories to model semiconductor manufacturing and device performance:
Optimizing performance to meet the demand of compute-intensive applications such as AI, cloud computing, and highly automated vehicles continues to be a challenge. While Moore’s law has long provided a pathway to design for optimal PPA, design technology co-optimization (DTCO) offers an avenue to assess PPA based on the chip’s process technology and design considerations. TCAD can enhance DTCO, a methodology that helps fabs reduce cost and time to market in advanced process development. During the pathfinding process, when engineers are evaluating architectures, materials, and different ways to integrate their devices, TCAD plays a role in the technology selection for DTCO. Traditionally, TCAD has examined individual transistors and circuit designs, employing SPICE models to analyze the behavior within circuits, while DTCO allows for evaluation of PPA at the standard-cell and even block level.
Many questions remain on how to integrate and further scale next-generation transistor architectures, which will go down to angstrom-level feature sizes. Not only does this make TCAD a continually important methodology, but it also requires a TCAD workforce with the expertise to utilize these tools and optimize future device designs and processing flows.
One of the key challenges and often a bottleneck to workforce development is acquiring manufacturing experience. However, TCAD creates an alternative approach where users and enthusiasts can gain meaningful insights into the manufacturing process by running simulations through a virtual fab. This is particularly appealing to institutions and startups that may have limited space and/or are tight on budget. Therefore, TCAD solutions can help reduce the need for students to access a semiconductor lab.
To address this, the Synopsys Academic & Research Alliances (SARA) program is working with leading universities to set up labs to provide students with hands-on training in process technologies, materials, and device architecture through software and course content. Recently, the Indian Institute of Technology (IIT) Bombay announced the Synopsys Semiconductor Lab for Virtual Fab Solutions, enabled with Synopsys TCAD solutions.
These types of collaborations exemplify how industry & academia collaboration can help support workforce development to advance the semiconductor industry. As various regions of the world invest in semiconductor design and manufacturing, having a workforce that’s ready to step in and fill the roles is crucial toward getting new fabs online quickly.
Looking ahead, we can expect TCAD to continue supporting DTCO as it evolves toward system technology co-optimization (STCO). Emerging from the shift toward multi-die systems, STCO is positioned to co-optimize the entire system, from technology to die to package, with guidance from tightly integrated multi-objective analyses. With the increasing prevalence of 3D heterogeneous integration, TCAD becomes an important player evaluating the impact of new materials, thermal properties, and stress.
In summary, the smart technology modeling available through today’s TCAD tools can lead to cost and time savings in pathfinding, development, and production ramping of semiconductor technologies. From atoms to circuits, these solutions are an important enabler of continued semiconductor innovation.
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