Software to Enable Rapidly Optimized Integrated Circuit Fabrication
Computing & Wireless : Application Software
Available for licensing
- Roger Bonnecaze, Ph.D. , Chemical Engineering
- Meghali Chopra , NASCENT
Today, recipe development and optimization for micro and nanofabrication processes are typically based on time-consuming and expensive experimental trial and error. Some processes may take up to a year to be fully optimized. Shortening this development time offers a clear opportunity to save time and money. Importantly, for semiconductor tool manufacturers, a shorter time to development can mean millions in tool sales. Existing techniques to mitigate this high cost, such as Design of Experiment (DoE), often still require large numbers of experiments and neglect information that might be gained from an understanding of process physics.
Researchers at The University of Texas at Austin have developed a process that uses physics-based models and integrated Bayesian statistics to dramatically speed up and reduce the cost for the empirical optimization of micro- and nano-fabrication processes compared to classical DoE. This methodology employs an iterative feedback between a model constructed on a robust theoretical foundation and experiments to guide the user to choose the best experiments to most quickly identify the optimal process conditions. The method enables the knowledge and experience of the user to be incorporated quantitatively to further decrease the time to optimization. Preliminary results show that number of experiments can be reduces by a factor of two to three compared to DoE.
- Reduces time and cost associated with recipe development and optimization
- Optimizes processing conditions using limited prior data
- Applicable in general to micro- and nano-fabrication processes, including tool-to-tool variations
- Physics based models predict process outcomes
- Bayesian statistics to optimized experimental design framework
This invention is particularly valuable for highly nonlinear nanomanufacturing processes.
Semiconductor process equipment suppliers that provide equipment for etch, lithography, and deposition will benefit from using this technology.
Proof of concept
- 1 U.S. patent application filed