Author Archives: Sandra Liu

Transistor-Level Performance Evaluation Based on Wafer-Level Process Modeling

By: Michael Hargrove, SP&I Engineer

Three years ago, I wrote a blog entitled “Linking Virtual Wafer Fabrication Modeling with Device-level TCAD Simulation” in which I described the seamless connection between the SEMulator3D® virtual wafer fabrication software platform and external 3rd party TCAD software. I’m now happy to report that device-level I-V performance analysis is now a built-in module within the SEMulator3D software platform.  Users are no longer required to export a mesh and import it into a TCAD platform, when performing transistor I-V simulation.  Now, once the 3D device structure is built in SEMulator3D, transistor I-V simulation can be performed directly within SEMulator3D without need for 3rd party solvers.  Contacts and bias can be applied using the SEMulator3D device design, and I-V transistor characteristics can be determined for specific steps in the process flow.  You can perform direct transistor-level performance evaluation inside the SEMulator3D software platform, without needing to export or import meshes. read more…

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Advanced 3D Design Technology Co-Optimization for Manufacturability

By: Yu De Chen, Jacky Huang, Dalong Zhao, Jiangjiang (Jimmy) Gu, Joseph Ervin

Yield and cost have always been critical factors for both manufacturers and designers of semiconductor products. It is a continuous challenge to meet targets of both yield and cost, due to new device structures and the increasing complexity of process innovations introduced to achieve improved product performance at each technology node. Design for manufacturability (DFM) and design technology co-optimization (DTCO) are widely used to ensure successful delivery of both new processes and products in semiconductor manufacturing. In this paper, we develop a new 3D DTCO model which combines 3D structure optimization and electrical analysis. We discuss how this 3D DTCO model can be used to improve product yield and accelerate product delivery timelines in semiconductor manufacturing. read more…

The Challenge of Modeling the Interaction between MEMS Inertial Sensors and their Packaging

By: Arnaud Parent

Simulation of Thermal Effects on MEMS Performances

MEMS inertial sensors, such as Accelerometers and Gyroscopes, have been commercially successful in the consumer marketplace, where reduced size and cost are more important than accuracy. These sensors are classified as commercial grade products, even though they are typically used in consumer applications. Today, MEMS inertial sensors are knocking on the door of tactical grade applications, where the requirements for accuracy are much more demanding. MEMS products may one day enter the navigation grade application space, where accuracy demands are even more stringent. To meet the enhanced accuracy and performance requirements of tactical and navigation grade inertial sensors, MEMS designers must not only consider the transducer itself but the interaction of the product with its surrounding environment (starting with the packaging). At Coventor, we have a new simulation platform that can be used to create a compact model of MEMS transducers along with their packaging, providing a method to efficiently study the overall behavior of MEMS inertial sensors. read more…

Improving Patterning Yield at the 5 nm Semiconductor Node

By:  Benjamin Vincent, Ph.D., Staff Engineer, Semiconductor Process & Integration

Engineering decisions are always data-driven.  As scientists, we only believe in facts and not in intuition or feelings.

At the manufacturing stage, the semiconductor industry is eager to provide data and facts to engineers based upon metrics such as the quantity of wafers produced per hour and sites/devices tested on each of those wafers. The massive quantity of data generated in semiconductor manufacturing can provide facts that engineers can use to make immediate and accurate decisions, such as how they might correct any excursion or yield drift. Data exists, so life is (kind of…) easy! read more…

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FD-SOI Adoption Expands

By Ed Sperling

Fully depleted silicon-on-insulator (FD-SOI) is gaining ground across a number of new markets, ranging from IoT to automotive to machine learning, and diverging sharply from its original position as a less costly alternative to finFET-based designs.

For years, FD-SOI has been viewed as an either/or solution targeted at the same markets as bulk CMOS.

read the full article here.


By Mike Pinelis

In August of 2017, Lam Research completed the acquisition of Coventor, a MEMS modeling and simulation software company, for a total purchase consideration of $137.6 million. When asked about how Coventor fits into Lam’s portfolio, the company’s Executive VP and CFO Douglas Bettinger said that, potentially, there are benefits and synergies with Coventor’s software capability to model and simulate the actual output of Lam’s equipment. We recently spoke with Stephen Breit, Coventor’s Sr. Director of MEMS, and discussed the trends that he is seeing in the MEMS marketplace. Since Coventor works with many MEMS companies, we also asked Stephen about the notable startups and technologies.

read the full article here.

Unlikely Pairings – Recent Atypical Mergers

By Bryon Moyer

Companies come; companies go. I don’t focus a lot on who buys whom – there are plenty of folks breathlessly watching that stuff, so I mostly leave the drama to them. After all, it’s an age of consolidation and accumulation of immense corporate power. So your typical low- to mid-level merger may not be particularly noteworthy.

But lately, there have been a couple of mergers/acquisitions that have had some unusual features to them. Add to that the fact that they’re companies we’ve looked at before, and it seems worth spending some time on them.

read the full article here.

Delivering the Next 5 Years of Semiconductor Technology

New, advanced semiconductor processing and architectural technologies take years to perfect and put into production. In the meantime, semiconductor customers continue to demand faster, smaller and higher functioning devices. Semiconductor manufacturers need to decide whether (and when) to jump to the next generation of devices and production technologies, weighing the risk and benefit of bringing the next processing and architecture technologies to market. read more…