Effect of single-electron interface trapping in decanano MOSFETs: A 3D atomistic simulation study
Abstract We study the effect of trapping/detrapping of a single-electron in interface states in the channel of n-type MOSFETs with decanano dimensions using 3D atomistic simulation techniques. In order to highlight the basic dependencies, the simulations are carried out initially assuming continuous doping charge, and discrete localized charge only for the trapped electron. The dependence of the random telegraph signal (RTS) amplitudes on the device dimensions and on the position of the trapped charge in the channel are studied in detail. Later, in full-scale, atomistic simulations assuming discrete charge for both randomly placed dopants and the trapped electron, we highlight the importance of current percolation and of traps with strategic position where the trapped electron blocks a dominant current path.
Automated understanding of spatio-temporal usage patterns of real-world applications are significant in urban planning. With the capability of smartphones collecting various information using inbuilt sensors, the smart city data is enriched with multiple contexts. Whilst tensor factorization has been successfully used to capture latent factors (patterns) exhibited by the real-world datasets, the multifaceted nature of smart city data needs an improved modeling to utilize multiple contexts in sparse condition. Thus, in our ongoing research, we aim to model this data with a novel Context-Aware Nonnegative Coupled Sparse Matrix Tensor (CAN-CSMT) framework which imposes sparsity constraint to learn the true factors in sparse data. We also aim to develop a fast and efficient factorization algorithm to deal with the scalability problem persistent in the state-of-the-art factorization algorithms.