Smaller Geometries, Bigger Demands: The Role Of OCD In GAA Logic And Vertical Gate DRAM Process Control


AI workloads are pushing the boundaries of compute, memory, and interconnect architectures, and to meet these goals, manufacturers are rapidly accelerating advanced logic and DRAM development. Chief among these innovations: gate-all-around (GAA) logic transistor and vertical gate (VG) DRAM, two device architectures that promise higher performance, improved power efficiency, and greater scalabil... » read more

Pressure Builds On Failure Analysis Labs


Failure analysis labs are becoming more fab-like, offering higher accuracy in locating failures and accelerating time-to-market of new devices. These labs historically have been used for deconstructing devices that failed during field use, known as return material authorizations (RMAs), but their role is expanding. They now are becoming instrumental in achieving first silicon and ramping yie... » read more

Full Wafer OCD Metrology


Authored by: Daniel Doutt*a, Ping-ju Chena, Bhargava Ravooria, Tuyen K. Trana, Eitan Rothsteinb, Nir Kampelb, Lilach Tamamb, Effi Aboodyb, Avron Gerb, Harindra Vedalac ABSTRACT Optical Critical Dimension (OCD) spectroscopy is a reliable, non-destructive, and high-throughput measurement technique for metrology and process control that is widely used in semiconductor fabrication facilities (f... » read more

Metrology Options Increase As Device Needs Shift


Semiconductor fabs are taking an ‘all hands on deck’ approach to solving tough metrology and yield management challenges, combining tools, processes, and other technologies as the chip industry transitions to nanosheet transistors on the front end and heterogenous integration on the back end. Optical and e-beam tools are being extended, while X-ray inspection is being added on a case-by-... » read more

Using BDA To to Predict SAQP Pitch Walk


A new technical paper titled "Bayesian dropout approximation in deep learning neural networks: analysis of self-aligned quadruple patterning" was published by researchers at IBM TJ Watson Research Center and Rensselaer Polytechnic Institute. Find the technical paper here. Published November 2022.  Open Access. Scott D. Halle, Derren N. Dunn, Allen H. Gabor, Max O. Bloomfield, and Mark Sh... » read more

Methods To Overcome Limited Labeled Data Sets In Machine Learning-Based Optical Critical Dimension Metrology


With the aggressive scaling of semiconductor devices, the increasing complexity of device structure coupled with tighter metrology error budget has driven up Optical Critical Dimension (OCD) time to solution to a critical point. Machine Learning (ML), thanks to its extremely fast turnaround, has been successfully applied in OCD metrology as an alternative solution to the conventional physical... » read more

Nanosheet FETs Drive Changes In Metrology And Inspection


In the Moore’s Law world, it has become a truism that smaller nodes lead to larger problems. As fabs turn to nanosheet transistors, it is becoming increasingly challenging to detect line-edge roughness and other defects due to the depths and opacities of these and other multi-layered structures. As a result, metrology is taking even more of a hybrid approach, with some well-known tools moving... » read more

The Human Hand: Curating Good Data And Creating An Effective Deep-Learning R2R Strategy For High-Volume Manufacturing


Currently, the semiconductor manufacturing industry uses artificial intelligence and machine learning to take data and autonomously learn from that data. With the additional data, AI and ML can be used to quickly discover patterns and determine correlations in various applications, most notably those applications involving metrology and inspection, whether in the front-end of the manufacturing ... » read more

Speeding Up The R&D Metrology Process


Several chipmakers are making some major changes in the characterization/metrology lab, adding more fab-like processes in this group to help speed up chip development times. The characterization/metrology lab, which is generally under the radar, is a group that works with the R&D organization and the fab. The characterization lab is involved in the early analytical work for next-generati... » read more

What’s Next With AI In Fabs?


Semiconductor Engineering sat down to discuss the issues and challenges with machine learning in semiconductor manufacturing with Kurt Ronse, director of the advanced lithography program at Imec; Yudong Hao, senior director of marketing at Onto Innovation; Romain Roux, data scientist at Mycronic; and Aki Fujimura, chief executive of D2S. What follows are excerpts of that conversation. Part one ... » read more

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