BTU auf einen Blick
Fakultät 1
Fachgebiet Mikro- und Nanosysteme Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk
Physics
ModulContentScope    Responsible
12-7-61
  • Introduction to error analysis/error calculation
  • Basic principles of mechanics: Forces, conservation of energy and momentum, dynamics of masses and bodies
  • Fundamentals of thermodynamics, kinetic theory of heat
  • Vibrations and waves
  • Electrostatics and magnetostatics in a vacuum and in matter
  • Electromagnetic waves in matter
  • Structure and properties of solids
2 SWS V,
2 SWS S,
1 SWS P		Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk
Micro Systems
ModulContentScope    Responsible
13-0-19
  • Introduction to silicon technology:
    materials, film deposition and structuring, surface- and volume-micromechanics, overview of equipment technology.
  • Physical principles of efficiency:
    basic physical principles of efficiency of simple sensors and actors (e.g. electrostatic, piezoelectric and magnetic effects).
  • Proposal of complex sensors and actors:
    overview of systematics and methodology, simple simulation examples for the calculation of dynamic properties of MEMS sensors.
  • Function and properties of complex sensors and actors:
    e.g. light modulators, acceleration sensors, gyroscope, scanner mirror.
2 SWS L,
1 SWS E,		Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk
Advanced Micro Systems, Focus on Microsensors
ModulContentScope    Responsible
13-7-52
  • Differentiation of sensors, transducers, actuators
  • Classification of sensors according to operating principles and intended use
  • Characteristics of sensors such as linearity, hysteresis, resolution
  • Analogue and digital sensors From elementary sensors to signal processing
  • Design, mode of operation and properties of selected capacitive, optical, chemical, acoustic and ultrasonic sensors
  • Application areas of sensors
  • Signal conditioning
  • Current research activities in microsensor technology
  • Principles and examples of microactuators and microtransducers
2 SWS L,
1 SWS S,		Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk
Data Exploration and System Management Using Artificial Intelligence / Machine Learning
ModulContentScope  Responsible
13-0-19The subject of the module are the classes of real-world problems that can be solved by data exploration using AI/ML methods. This includes, for example, anomaly/outlier detection, data decomposition and feature selection, data fusion, prediction, decision support. A mapping between problems and available AI/ML methods will be presented.
The project consists in solving a self-defined problem using a selected AI/ML technique and computer simulations. The software procedure together with a project report will be created by student		2 SWS L,
1 SWS P		Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk

Durchführung:
Dr. hab. Ireneusz Jablonski
Experimental Techniques in Physics Supported with Artificial Intelligence / Machine Learning
ModulContentScope  Responsible
13-9-08The subject of the module is the fundamentals of experiment design, including the theoretical and practical aspects of experiment planning and execution. This includes, for example, the role of observation and measurement in cognition process, data collection and processing with the use of statistical and AI/ML methods, data and system modeling, computer simulation, and planning of experiment.
The laboratory will use computer simulation to solve selected problems of experimentation, e.g. forward and inverse modeling, signal reconstruction, model identification, experiment planning. Statistical and AI/ML techniques will be used in exemplary tasks. The form of the class includes the realization of tasks under supervision and solving self-defined problems.		2 SWS L,
2 SWS P,		Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk

Durchführung:
Dr. hab. Ireneusz Jablonski
Particle-based microfluidics