227-0622-00L  Thermal Modeling: From Semiconductor to Medical Devices and Personalized Therapy Planning

SemesterSpring Semester 2021
LecturersE. Neufeld, M. Luisier
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
227-0622-00 VThermal Modeling: From Semiconductor to Medical Devices and Personalized Therapy Planning2 hrs
Wed09:15-11:00ETZ J 91 »
E. Neufeld, M. Luisier
227-0622-00 UThermal Modeling: From Semiconductor to Medical Devices and Personalized Therapy Planning1 hrs
Wed11:15-12:00ETZ J 91 »
E. Neufeld, M. Luisier

Catalogue data

AbstractThe course introduces computational techniques to model electromagnetic heating across many orders of magnitudes, from the atomic to the macroscopic scale. Both desired and undesired thermal effects will be covered, e.g. thermal cancer therapies based on tissue heating or Joule heating in semiconductor devices. A wide range of simulation approaches and numerical methods will be introduced.
ObjectiveDuring this course the students will:

- learn the physics governing and computational models describing electromagnetic-induced heating;

- get familiar with computational simulation techniques across a wide range of spatial scales, incl. methods to simulate in vivo heating, considering thermoregulation and perfusion, or quantum mechanical approaches considering heat at the level of atomic vibrations;

- implement and apply simulation techniques within a state-of-the-art open-source simulation platform for computational life sciences, as well as a framework for computer-aided design of semiconductor devices;

- learn about remaining challenges in this field
ContentThe following topics will be discussed during the semester:

- Introduction about electromagnetic heating (from its historical perspective to its application in biology);

- Microscopic/Macroscopic thermal transport (governing equations, numerical methods, examples);

- Numerical algorithms and their implementation in python and/or C++, parallelisation approaches, and high performance computing solutions;

- Practical examples: thermal therapy planning with Sim4Life and technology computer aided design with OMEN;

- Model verification and validation.
Lecture notesLecture slides are distributed every week and can be found at
Link
Prerequisites / NoticeThe course requires an open attitude towards interdisciplinarity, basic python scripting and C++ coding skills, undergraduate entry-level familiarity with electric & magnetic fields/forces, differential equations, calculus, and basic knowledge of biology and quantum mechanics.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersE. Neufeld, M. Luisier
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationoral 30 minutes
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

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Only public learning materials are listed.

Groups

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Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Biomedical Engineering MasterRecommended Elective CoursesWInformation
Electrical Engineering and Information Technology MasterRecommended SubjectsWInformation
Electrical Engineering and Information Technology MasterSpecialization CoursesWInformation
Micro- and Nanosystems MasterElective Core CoursesWInformation
Computational Science and Engineering MasterElectromagneticsWInformation