Making Random Variation Less Random


The economics for random variation are changing, particularly at advanced nodes and in complex packaging schemes. Random variation always will exist in semiconductor manufacturing processes, but much of what is called random has a traceable root cause. The reason it is classified as random is that it is expensive to track down all of the various quirks in a complex manufacturing process or i... » read more

Controlling Variability Using Semiconductor Process Window Optimization


To ensure success in semiconductor technology development, process engineers must set the allowed ranges for wafer process parameters. Variability must be controlled, so that final fabricated devices meet required specifications. These specifications include critical dimensions, electrical performance requirements, and other device characteristics. Pre-production or ramp-up production Si wa... » read more

Advanced Process Control


David Fried, vice president of computational products at Lam Research, looks at shrinking tolerances at advanced processes, how that affects variation in semiconductor manufacturing, and what can be done to achieve the benefits of scaling without moving to new transistor architectures. » read more

Challenges In Making And Testing STT-MRAM


Several chipmakers are ramping up a next-generation memory type called STT-MRAM, but there are still an assortment of manufacturing and test challenges for current and future devices. STT-MRAM, or spin-transfer torque MRAM, is attractive and gaining steam because it combines the attributes of several conventional memory types in a single device. In the works for years, STT-MRAM features the ... » read more

The Precision Knob


Precision used to be a goal, but increasingly it is being used as a tool. This is true for processing and algorithms, where less precision can greatly improve both performance and battery life. And it is true in manufacturing, where more precision can help minimize the growing impact of variation. Moreover, being able to dial precision up or down can help engineers see the impact on a system... » read more

Low Power Meets Variability At 7/5nm


Power-related issues are beginning to clash with process variation at 7/5nm, making timing closure more difficult and resulting in re-spins caused by unexpected errors and poor functional yield. Variability is becoming particularly troublesome at advanced nodes, and there are multiple causes of that variability. One of the key ones is the manufacturing process, which can be affected by every... » read more

Power Budgets At 3nm And Beyond


There is high confidence that digital logic will continue to shrink at least to 3nm, and possibly down to 1.5nm. Each of those will require significant changes in how design teams approach power. This is somewhat evolutionary for most chipmakers. Five years ago there were fewer than a handful of power experts in most large organizations. Today, everyone deals with power in one way or another... » read more

New Design Approaches At 7/5nm


The race to build chips with a multitude of different processing elements and memories is making it more difficult to design, verify and test these devices, particularly when AI and leading-edge manufacturing processes are involved. There are two fundamental problems. First, there are much tighter tolerances for all of the components in those designs due to proximity effects. Second, as a re... » read more

The Good And Bad Of 2D Materials


Despite years of warnings about reaching the limits of silicon, particularly at leading-edge process nodes where electron mobility is limited, there still is no obvious replacement. Silicon’s decades-long dominance of the integrated circuit industry is only partly due to the material’s electronic properties. Germanium, gallium arsenide, and many other semiconductors offer superior mobili... » read more

Using Sensor Data To Improve Yield And Uptime


Semiconductor equipment vendors are starting to add more sensors into their tools in an effort to improve fab uptime and wafer yield, and to reduce cost of ownership and chip failures. Massive amounts of data gleaned from those tools is expected to provide far more detail than in the past about multiple types and sources of variation, including when and where that variation occurred and how,... » read more

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