This grant provides funding for the investigation of reliability in nanoelectronics. Nanoelectronics is a driving force for strong economic growth in the United States. Reliability is recognized as one of the most critical factors in determining the success of nano fabrication and manufacturing. This collaborative project will be led by a nano device engineer and a reliability specialist. The objective of this interdisciplinary research is to investigate effective and practical nonparametric Bayesian methods to assess the reliability of nanoelectronic products during the early design and development stages. Specially, the proposed research tasks consist of two closely-related components: (i) an analytical study to develop practical nonparametric Bayesian methods for estimating important reliability measures of nanoelectronic devices, and (ii) an experimental study to validate the models by fabricating and characterizing newly developed nonvolatile memories based on nanocrystals embedded high-k thin films.
Upon the successful completion of this project, new methods and tools that are critical to design and manufacture reliable nanoelectronic products will be developed. This will be the first systematic study in modeling and predicting reliability of nano products based on experimental data and nonparametric Bayesian methods which offer great flexibility and capability to address challenges in real products influencing yield and cost. The result will enable manufacturers to assess reliability of new nano products and involved costs in the early design and development stages, which would expedite products to the market. Furthermore, the new nonvolatile memory devices have practical applications in future generation integrated circuits (ICs) and data storage. This multidisciplinary research project will provides students with both theoretical and experimental education in reliability, semiconductor devices, thin film materials, and high-tech fabrication processes.
