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San Jose Convention Center
San Jose, California, United States
23 - 27 February 2020
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Add an application track to help get your presentation noticed

Add an application track

2020 application tracks
The application tracks highlights papers focused on specific topics. Authors selecting an application track get their presentation identified in the conference program and special care is taken to ensure presentations on the same topic do not overlap. This way, participants can easily locate and attend presentations in the their area of interest.

You can add an application track to your abstract submission to increase the visibility of your presentation in the program.

Abstracts due
21 August 2019

Author notification
21 October 2019

Manuscripts due
29 January 2020

How to indicate an application track

1. Select a conference online, click "Submit an Abstract", and follow the instructions.
2. Indicate the appropriate subject Machine Learning, Stochastics, or Overlay when prompted during the submission process.

Accepted presentations will be listed in both the submitted conference and the appropriate application track listing in the program, helping attendees find presentations related to this topic.

2020 Application tracks

Machine Learning

Machine Learning is permeating the scientific and industry sectors recently especially through the approach using artificial neural network. Machine Learning seems to provide significant speed improvement and yet comparable accuracy to traditional methods that rely on complicated algorithm and/or rigorous physical model development. At the end it might mitigate many of the bottlenecks in turnaround time in full chip application and opens up a lot of possibilities that shorten product development time.


Stochastic effects was not given much attention in the early development of EUV lithography but recently as the industry is moving EUV to volume manufacturing these stochastic effects becomes more critical in lithography yield. Stochastic defects are difficult to mitigate because of its probabilistic nature. They could manifest as LER, LWR, and in worst case a catastrophic defects. There are active effort to reduce stochastic effect in the research community including increasing EUV source power significantly, which means new light source might be needed, as well as innovation and breakthrough in photoresist material and processing.


As technology node advances feature sizes are scaling to provide density benefit. This drives a much higher requirement in overlay and the situation is getting worse by the use of multiple patterning. Just by having better overlay performance from a scanner is not sufficient. A holistic approach where the exposure tool, process architecture, device design, circuit design, overlay metrology and analytics and manufacturing process control are all required to minimize the overlay problem to improve circuit yield.

Explore where you research fits best so you can submit an abstract

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