The paper presents computer simulation results of heavy charged particles radiation effect on elements of electrostatic microelectromechanical systems. Modeling methods of heavy charged particles impact on MEMS elements were envisaged. The radiation sensitivity of different types of fractal electrostatic MEMS were evaluated. Methods of reduction of radiation impact on electrostatic MEMS based on fractal theory were discussed. Conclusions about fractal electrostatic MEMS features were outlined.
In the paper, an application of cognitive nanoinformatics to advance modeling and simulation of nanoelectronics devices is discussed. The multi-scale approach to information management for nanoelectronics devices modeling and simulation has been proposed. We illustrate our approach for two case study nanoelectronics devices.
In the paper silicon on insulator layout decomposition algorithms for the double patterning lithography on high performance computing platforms are discussed. Our approach is based on the use of a contradiction graph and a modified concurrent breadth-first search algorithm. We evaluate our technique on 45 nm Nangate Open Cell Library including non-Manhattan geometry. Experimental results show that our soft computing algorithms decompose layout successfully and a minimal distance between polygons in layout is increased.
An increasing complexity of mixed analog-digital signal circuits requires optimization at higher hierarchical level.
However, evolutionary optimization of mixed analog-digital signal circuits at the system level results in huge
computational costs. A key to manage these computational complexities of evolutionary circuit design is an application
of flexible fitness functions evaluation schedules. In this paper we compare the static, dynamic, and co-evolution fitness
function evaluation schedules for multi-objective optimization of mixed analog-digital signal circuits at the system level
on the base of the univariate marginal distribution algorithm. Experiments for our symmetry recognition circuit
benchmark chosen indicate that the dynamic fitness function schedule is a good compromise between computational
costs and optimization efficiency.