Jacek Nazdrowicz

A study on microbolometer electro-thermal circuit modelling

Electro-thermal models are commonly used in simulations and designing MEMS devices, also in case of microbolometers. These models allow to estimate sensors performance before fabrication that consequently impacts on fabrication cost. Coupling of electric and thermal domains and building appropriate model for carrying out simulations are crucial to detect all phenomena having impact for Readout Integrated Circuit. This article brings closer to the subject matter of circuit modelling (willingly implemented in MATLAB/SIMULINK or PSPICE tools) and to its theoretical background.

FEM analysis of a 3D model of a capacitive surface-micromachined accelerometer

In this paper we present the analysis of a 3D model of a surface-micromachined accelerometer. It allows us to define basic mechanical parameters, which give us information about mechanical properties of the modelled sensor. The analysis has been performed in COMSOL Multiphysics software. We used the Finite Element Method (FEM) for the analysis of the 3D structure. We analysed the behaviour of our sensor for changing the acceleration up to 8g. We also checked the eigenfrequencies of the sensor in order to define its parameters.

Simulations and analysis of microgyroscope response in drive and sense directions

This paper presents developed mathematical model of MEMS gyroscope in Matlab/SIMULINK environment. This model was created with standard SIMULINK library, so it can be used commonly. It uses blocks which have been used for some years and they are compatible backwards with previous versions of SIMULINK. This model can be very useful for calculating MEMS gyroscope parameters especially geometrical ones because these have huge impact on device response and possibilities of application. In this paper output characteristics of MEMS gyroscope are presented in both orthogonal directions, this gives quick overview of behavior this kind of microgyroscope.

SIMULINK and COMSOL software application for MEMS accelerometer modeling and simulation

In the last few years MEMS accelerometers have achieved huge commercial success thanks to new cheap technologies of manufacturing, new materials and achievements of researches. Due to low weight and low energy consumption, microaccelerometers found wide application in many popular devices expanding their functionality. Commercial fabrication of MEMS and intensive developing require taking advantage of advanced mathematical and engineering tools for modelling and simulation. The objective of this research work is to present designing and simulation capabilities of MEMS devices with mathematical models and Finite Element Method. One of the most famous software to make such analysis is COMSOL Multiphysics. In this article MEMS accelerometer is presented with modeling and simulation processes. Results of simulations are supported with results obtained from Matlab/SIMULINK software and analyzed for displacement response for two of the most popular spring geometries — folded and straight.

Modelling Microbolometer using Matlab/SIMULINK package with thermal noise sources

Infrared radiation microdetectors become a concern for many scientists, because of their wide capability application in industry. Microbolometers are good example of resistive microdetectors belonging to large family of MEMS devices. Electro-thermal models are commonly used in simulations and designing MEMS devices, also in microbolometers modelling and analyzing of performance. It is crucial to build the most detailed model as possible with mutual electric and thermal domains influence for carrying out simulations and detect all phenomena. During modeling creation it is important to notice that Microbolometers detection capability is limited by fluctuation of various noise sources which have random nature. This article presents theoretical background of circuit modelling, with thermal noise sources taken into consideration.

A relational database environment for numerical simulation backend storage

Problem of effective data processing in scientific applications is well-known. There are two reasons of that: nonoptimal front-end application code and ineffective system of scientific data management at back-end. This article presents differences between flat file and relational database data storage. It also shows (based on Microsoft SQL Server database engine) benefits and methods of taking advantages of relational database. These include creation scientific workgroup environment for high availability, fault tolerance and optimal scientific data processing with build-in implemented structures and mechanisms. Such solution can be useful in numerical methods programs, also in Finite Element Methods.