Search result: Catalogue data in Spring Semester 2020

Electrical Engineering and Information Technology Master Information
Master Studies (Programme Regulations 2018)
Electronics and Photonics
The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Electronics and Photonics", see https://www.ee.ethz.ch/studies/main-master/areas-of-specialisation.html.

The individual study plan is subject to the tutor's approval.
Core Courses
These core courses are particularly recommended for the field of "Electronics and Photonics".
You may choose core courses form other fields in agreement with your tutor.

A minimum of 24 credits must be obtained from core courses during the MSc EEIT.
Foundation Core Courses
NumberTitleTypeECTSHoursLecturers
227-0111-00LCommunication ElectronicsW6 credits2V + 2UQ. Huang
AbstractElectronics for communications systems, with emphasis on realization. Low noise amplifiers, modulators and demodulators, transmit amplifiers and oscillators are discussed in the context of wireless communications. Wireless receiver, transmitter and frequency synthesizer will be described. Importance of and trade offs among sensitivity, linearity and selectivity are discussed extensively.
Learning objectiveFoundation course for understanding modern electronic circuits for communication applications. We learn how theoretical communications principles are reduced to practice using transistors, switches, inductors, capacitors and resistors. The harsh environment such communication electronics will be exposed to and the resulting requirements on the sensitivity, linearity and selectivity help explain the design trade offs encountered in every circuit block found in a modern transceiver.
ContentAccounting for more than two trillion dollars per year, communications is one of the most important drivers for advanced economies of our time. Wired networks have been a key enabler to the internet age and the proliferation of search engines, social networks and electronic commerce, whereas wireless communications, cellular networks in particular, have liberated people and increased productivity in developed and developing nations alike. Integrated circuits that make such communications devices light weight and affordable have played a key role in the proliferation of communications.
This course introduces our students to the key components that realize the tangible products in electronic form. We begin with an introduction to wireless communications, and describe the harsh environment in which a transceiver has to work reliably. In this context we highlight the importance of sensitivity or low noise, linearity, selectivity, power consumption and cost, that are all vital to a competitive device in such applications.
We shall review bipolar and MOS devices from a designer's prospectives, before discussing basic amplifier structures - common emitter/source, common base/gate configurations, their noise performance and linearity, impedance matching, and many other things one needs to know about a low noise amplifier.
We will discuss modulation, and the mixer that enables its implementation. Noise and linearity form an inseparable part of the discussion of its design, but we also introduce the concept of quadrature demodulator, image rejection, and the effects of mismatch on performance.
When mixers are used as a modulator the signals they receive are usually large and the natural linearity of transistors becomes insufficient. The concept of feedback will be introduced and its function as an improver of linearity studied in detail.
Amplifiers in the transmit path are necessary to boost the power level before the signal leaves an integrated circuit to drive an even more powerful amplifier (PA) off chip. Linearized pre-amplifiers will be studied as part of the transmitter.
A crucial part of a mobile transceiver terminal is the generation of local oscillator signals at the desired frequencies that are required for modulation and demodulation. Oscillators will be studied, starting from stability criteria of an electronic system, then leading to criteria for controlled instability or oscillation. Oscillator design will be discussed in detail, including that of crystal controlled oscillators which provide accurate time base.
An introduction to phase-locked loops will be made, illustrating how it links a variable frequency oscillator to a very stable fixed frequency crystal oscillator, and how phase detector, charge pump and programmable dividers all serve to realize an agile frequency synthesizer that is very stable in each frequency synthesized.
Lecture notesScript is available online under https://iis-students.ee.ethz.ch/lectures/communication-electronics/
Prerequisites / NoticeThe course Analog Integrated Circuits is recommended as preparation for this course.
227-0147-00LVLSI II: Design of Very Large Scale Integration Circuits Information W6 credits5GF. K. Gürkaynak, L. Benini
AbstractThis second course in our VLSI series is concerned with how to turn digital circuit netlists into safe, testable and manufacturable mask layout, taking into account various parasitic effects. Low-power circuit design is another important topic. Economic aspects and management issues of VLSI projects round off the course.
Learning objectiveKnow how to design digital VLSI circuits that are safe, testable, durable, and make economic sense.
ContentThe second course begins with a thorough discussion of various technical aspects at the circuit and layout level before moving on to economic issues of VLSI. Topics include:
- The difficulties of finding fabrication defects in large VLSI chips.
- How to make integrated circuit testable (design for test).
- Synchronous clocking disciplines compared, clock skew, clock distribution, input/output timing.
- Synchronization and metastability.
- CMOS transistor-level circuits of gates, flip-flops and random access memories.
- Sinks of energy in CMOS circuits.
- Power estimation and low-power design.
- Current research in low-energy computing.
- Layout parasitics, interconnect delay, static timing analysis.
- Switching currents, ground bounce, IR-drop, power distribution.
- Floorplanning, chip assembly, packaging.
- Layout design at the mask level, physical design verification.
- Electromigration, electrostatic discharge, and latch-up.
- Models of industrial cooperation in microelectronics.
- The caveats of virtual components.
- The cost structures of ASIC development and manufacturing.
- Market requirements, decision criteria, and case studies.
- Yield models.
- Avenues to low-volume fabrication.
- Marketing considerations and case studies.
- Management of VLSI projects.

Exercises are concerned with back-end design (floorplanning, placement, routing, clock and power distribution, layout verification). Industrial CAD tools are being used.
Lecture notesH. Kaeslin: "Top-Down Digital VLSI Design, from Gate-Level Circuits to CMOS Fabrication", Lecture Notes Vol.2 , 2015.

All written documents in English.
LiteratureH. Kaeslin: "Top-Down Digital VLSI Design, from Architectures to Gate-Level Circuits and FPGAs", Elsevier, 2014, ISBN 9780128007303.
Prerequisites / NoticeHighlight:
Students are offered the opportunity to design a circuit of their own which then gets actually fabricated as a microchip! Students who elect to participate in this program register for a term project at the Integrated Systems Laboratory in parallel to attending the VLSI II course.

Prerequisites:
"VLSI I: from Architectures to Very Large Scale Integration Circuits and FPGAs" or equivalent knowledge.

Further details:
https://vlsi2.ethz.ch
227-0125-00LOptics and PhotonicsW6 credits2V + 2UJ. Leuthold
AbstractThis lecture covers both - the fundamentals of "Optics" such as e.g. "ray optics", "coherence", the "Planck law" or the "Einstein relations" but also the fundamentals of "Photonics" on the generation, processing, transmission and detection of photons.
Learning objectiveA sound base for work in the field of optics and photonics will be given.
ContentChapter 1: Ray Optics
Chapter 2: Electromagnetic Optics
Chapter 3: Polarization
Chapter 4: Coherence and Interference
Chapter 5: Fourier Optics and Diffraction
Chapter 6: Guided Wave Optics
Chapter 7: Optical Fibers
Chapter 8: The Laser
Lecture notesLecture notes will be handed out.
Prerequisites / NoticeFundamentals of Electromagnetic Fields (Maxwell Equations) & Bachelor Lectures on Physics.
Advanced Core Courses
NumberTitleTypeECTSHoursLecturers
227-0146-00LAnalog-to-Digital Converters Information
Does not take place this semester.
Course will be moved to the fall semester 2021.
W6 credits2V + 2U
AbstractThis course provides a thorough treatment of integrated data conversion systems from system level specifications and trade-offs, over architecture choice down to circuit implementation.
Learning objectiveData conversion systems are substantial sub-parts of many electronic systems, e.g. the audio conversion system of a home-cinema systems or the base-band front-end of a wireless modem. Data conversion systems usually determine the performance of the overall system in terms of dynamic range and linearity. The student will learn to understand the basic principles behind data conversion and be introduced to the different methods and circuit architectures to implement such a conversion. The conversion methods such as successive approximation or algorithmic conversion are explained with their principle of operation accompanied with the appropriate mathematical calculations, including the effects of non-idealties in some cases. After successful completion of the course the student should understand the concept of an ideal ADC, know all major converter architectures, their principle of operation and what governs their performance.
Content- Introduction: information representation and communication; abstraction, categorization and symbolic representation; basic conversion algorithms; data converter application; tradeoffs among key parameters; ADC taxonomy.
- Dual-slope & successive approximation register (SAR) converters: dual slope principle & converter; SAR ADC operating principle; SAR implementation with a capacitive array; range extension with segmented array.
- Algorithmic & pipelined A/D converters: algorithmic conversion principle; sample & hold stage; pipe-lined converter; multiplying DAC; flash sub-ADC and n-bit MDAC; redundancy for correction of non-idealties, error correction.
- Performance metrics and non-linearity: ideal ADC; offset, gain error, differential and integral non-linearities; capacitor mismatch; impact of capacitor mismatch on SAR ADC's performance.
- Flash, folding an interpolating analog-to-digital converters: flash ADC principle, thermometer to binary coding, sparkle correction; limitations of flash converters; the folding principle, residue extraction; folding amplifiers; cascaded folding; interpolation for folding converters; cascaded folding and interpolation.
- Noise in analog-to-digital converters: types of noise; noise calculation in electronic circuit, kT/C-noise, sampled noise; noise analysis in switched-capacitor circuits; aperture time uncertainty and sampling jitter.
- Delta-sigma A/D-converters: linearity and resolution; from delta-modulation to delta-sigma modulation; first-oder delta-sigma modulation, circuit level implementation; clock-jitter & SNR in delta-sigma modulators; second-order delta-sigma modulation, higher-order modulation, design procedure for a single-loop modulator.
- Digital-to-analog converters: introduction; current scaling D/A converter, current steering DAC, calibration for improved performance.
Lecture notesSlides are available online under https://iis-students.ee.ethz.ch/lectures/analog-to-digital-converters/
Literature- B. Razavi, Principles of Data Conversion System Design, IEEE Press, 1994
- M. Gustavsson et. al., CMOS Data Converters for Communications, Springer, 2010
- R.J. van de Plassche, CMOS Integrated Analog-to-Digital and Digital-to-Analog Converters, Springer, 2010
Prerequisites / NoticeIt is highly recommended to attend the course "Analog Integrated Circuits" of Prof. Huang as a preparation for this course.
227-0150-00LSystems-on-chip for Data Analytics and Machine Learning
Previously "Energy-Efficient Parallel Computing Systems for Data Analytics"
W6 credits4GL. Benini
AbstractSystems-on-chip architecture and related design issues with a focus on machine learning and data analytics applications. It will cover multi-cores, many-cores, vector engines, GP-GPUs, application-specific processors and heterogeneous compute accelerators. Special emphasis given to energy-efficiency issues and hardware-software techniques for power and energy minimization.
Learning objectiveGive in-depth understanding of the links and dependencies between architectures and their energy-efficient implementation and to get a comprehensive exposure to state-of-the-art systems-on-chip platforms for machine learning and data analytics. Practical experience will also be gained through practical exercises and mini-projects (hardware and software) assigned on specific topics.
ContentThe course will cover advanced system-on-chip architectures, with an in-depth view on design challenges related to advanced silicon technology and state-of-the-art system integration options (nanometer silicon technology, novel storage devices, three-dimensional integration, advanced system packaging). The emphasis will be on programmable parallel architectures with application focus on machine learning and data analytics. The main SoC architectural families will be covered: namely, multi and many- cores, GPUs, vector accelerators, application-specific processors, heterogeneous platforms. The course will cover the complex design choices required to achieve scalability and energy proportionality. The course will will also delve into system design, touching on hardware-software tradeoffs and full-system analysis and optimization taking into account non-functional constraints and quality metrics, such as power consumption, thermal dissipation, reliability and variability. The application focus will be on machine learning both in the cloud and at the edges (near-sensor analytics).
Lecture notesSlides will be provided to accompany lectures. Pointers to scientific literature will be given. Exercise scripts and tutorials will be provided.
LiteratureJohn L. Hennessy, David A. Patterson, Computer Architecture: A Quantitative Approach (The Morgan Kaufmann Series in Computer Architecture and Design) 6th Edition, 2017.
Prerequisites / NoticeKnowledge of digital design at the level of "Design of Digital Circuits SS12" is required.

Knowledge of basic VLSI design at the level of "VLSI I: Architectures of VLSI Circuits" is required
227-0159-00LSemiconductor Devices: Quantum Transport at the Nanoscale Information W6 credits2V + 2UM. Luisier, A. Emboras
AbstractThis class offers an introduction into quantum transport theory, a rigorous approach to electron transport at the nanoscale. It covers different topics such as bandstructure, Wave Function and Non-equilibrium Green's Function formalisms, and electron interactions with their environment. Matlab exercises accompany the lectures where students learn how to develop their own transport simulator.
Learning objectiveThe continuous scaling of electronic devices has given rise to structures whose dimensions do not exceed a few atomic layers. At this size, electrons do not behave as particle any more, but as propagating waves and the classical representation of electron transport as the sum of drift-diffusion processes fails. The purpose of this class is to explore and understand the displacement of electrons through nanoscale device structures based on state-of-the-art quantum transport methods and to get familiar with the underlying equations by developing his own nanoelectronic device simulator.
ContentThe following topics will be addressed:
- Introduction to quantum transport modeling
- Bandstructure representation and effective mass approximation
- Open vs closed boundary conditions to the Schrödinger equation
- Comparison of the Wave Function and Non-equilibrium Green's Function formalisms as solution to the Schrödinger equation
- Self-consistent Schödinger-Poisson simulations
- Quantum transport simulations of resonant tunneling diodes and quantum well nano-transistors
- Top-of-the-barrier simulation approach to nano-transistor
- Electron interactions with their environment (phonon, roughness, impurity,...)
- Multi-band transport models
Lecture notesLecture slides are distributed every week and can be found at
https://iis-students.ee.ethz.ch/lectures/quantum-transport-in-nanoscale-devices/
LiteratureRecommended textbook: "Electronic Transport in Mesoscopic Systems", Supriyo Datta, Cambridge Studies in Semiconductor Physics and Microelectronic Engineering, 1997
Prerequisites / NoticeBasic knowledge of semiconductor device physics and quantum mechanics
Specialization Courses
These specialization courses are particularly recommended for the area of "Electronics and Photonics", but you are free to choose courses from any other field in agreement with your tutor.

A minimum of 40 credits must be obtained from specialization courses during the Master's Programme.
NumberTitleTypeECTSHoursLecturers
227-0117-10LExperimental TechniquesW6 credits4GC. Franck, H.‑J. Weber
AbstractThis lecture is an introduction to experimental and measurement techniques. The course is designed with practical relevance in mind and comprises several laboratory modules where the students perform, evaluate and document experiments. The taught topics are of relevance for all electrical engineering disciplines, in this course they are taught with examples of high-voltage engineering.
Learning objectiveAt the end of this lecture, the students will be able to:
- perform basic practical laboratory experiments and record data, in particular with an oscilloscope.
- take a meaningful Lab Notebook, write a clear measurement evaluation protocol, and can estimate the accuracy and precision of the evaluated data.
- can explain the main reasons for electromagnetic interference and propose measures to avoid or reduce these interferences.
- Explain and use different methods to generate and measure high voltages and calculate basic relevant relations.
Content- Messtechnik, Messunsicherheit, Messprotokolle
- Erzeugung und Messung hoher Spannungen
- Elektromagnetische Verträglichkeit
- Laborpraktika
Lecture notesVorlesungsunterlagen
LiteratureJ. Hoffmann, Taschenbuch der Messtechnik, Carl Hanser Verlag, 7. Auflage, 2015 (ISBN: 978-3446442719)
A. Küchler, Hochspannungstechnik, Springer Berlin, 4. Auflage, 2017 (ISBN: 978-3662546994)
A. Schwab, Elektromagnetische Verträglichkeit, Springer Verlag, 6. Auflage, 2010 (ISBN: 978-3642166099)
227-0155-00LMachine Learning on Microcontrollers Restricted registration - show details
Registration in this class requires the permission of the instructors. Class size will be limited to 30.
Preference is given to students in the MSc EEIT.
W6 credits3G + 2AM. Magno, L. Benini
AbstractMachine Learning (ML) and artificial intelligence are pervading the digital society. Today, even low power embedded systems are incorporating ML, becoming increasingly “smart”. This lecture gives an overview of ML methods and algorithms to process and extract useful near-sensor information in end-nodes of the “internet-of-things”, using low-power microcontrollers/ processors (ARM-Cortex-M; RISC-V)
Learning objectiveLearn how to Process data from sensors and how to extract useful information with low power microprocessors using ML techniques. We will analyze data coming from real low-power sensors (accelerometers, microphones, ExG bio-signals, cameras…). The main objective is to study in details how Machine Learning algorithms can be adapted to the performance constraints and limited resources of low-power microcontrollers.
ContentThe final goal of the course is a deep understanding of machine learning and its practical implementation on single- and multi-core microcontrollers, coupled with performance and energy efficiency analysis and optimization. The main topics of the course include:

- Sensors and sensor data acquisition with low power embedded systems

- Machine Learning: Overview of supervised and unsupervised learning and in particular supervised learning (Bayes Decision Theory, Decision Trees, Random Forests, kNN-Methods, Support Vector Machines, Convolutional Networks and Deep Learning)

- Low-power embedded systems and their architecture. Low Power microcontrollers (ARM-Cortex M) and RISC-V-based Parallel Ultra Low Power (PULP) systems-on-chip.

- Low power smart sensor system design: hardware-software tradeoffs, analysis, and optimization. Implementation and performance evaluation of ML in battery-operated embedded systems.

The laboratory exercised will show how to address concrete design problems, like motion, gesture recognition, emotion detection, image and sound classification, using real sensors data and real MCU boards.

Presentations from Ph.D. students and the visit to the Digital Circuits and Systems Group will introduce current research topics and international research projects.
Lecture notesScript and exercise sheets. Books will be suggested during the course.
Prerequisites / NoticePrerequisites: Good experience in C language programming. Microprocessors and computer architecture. Basics of Digital Signal Processing. Some exposure to machine learning concepts is also desirable.
227-0162-00LIntegrated Quantum, Statistical, and Information Mechanics for Information Processing
Does not take place this semester.
W4 credits2V + 2US. Tiwari
AbstractComputing with devices as physical objects composed of atoms, electrons and photons is an architected assembly where information is grounded in and transformed in quantum, statistical and information mechanics. This course is an integrated introduction to quantum, statistical, and information mechanics bringing out the common principles of these subjects with an engineering emphasis.
Learning objectiveThis course is an integrated introduction to information-centered foundational ideas to build an understanding of quantum, statistical and information mechanics as applied generally in engineering and specifically in computing. Computing employs hardware and objective manipulation of signals turned into data to access desired information. A logical state of a computer must be represented as a physical state in the hardware. Devices as physical objects have the information grounded in quantum, statistical, and information mechanics. These three science and engineering specialties are our theories for describing and predicting the abstracted behavior. The power dissipation in signal and data manipulation, the speed with which changes happen, the various architectures through which one may affect the change, the error rates, etc. are all grounded in the information that underscores what we practice in quantum mechanics, statistics, solid-state, electronics and information theory. In the quantum approach, information gained arises in the observation. In the statistical approach, it is through the probabilistic extractions. Preservation of information content in the presence of noise and fluctuations leads to dissipation. Inferencing and computation requires information compression through the objective symbolic manipulation and efficient coding. Entanglement and entropy are intrinsic in this probabilistic edifice where the inferences are drawn. Deterministic computing, as in the traditional approach, and non-deterministic computing such as the modern machines learning using neural networks, depend on how the information is manipulated in the midst of this entropy and entanglement. In addition to the introductory integrative understanding of quantum, statistical, and information mechanics, this course helps an understanding of the character of information processing through the traditional computing, quantum computing and neural network techniques.
ContentAn introduction to the basic tenets of quantum mechanics (axioms, operators, observation, perturbation, evolution, mixed states), statistical mechanics (basics of thermodynamics, principles of statistical mechanics, particle statistics, entropy, classical-to-quantum), information mechanics (various entropies, mutual information, data and channels, Bayesian approach, Fisher information, maximum entropy) and their use in exploration of computing via different architectures of computation (BLAS, von Neumann and neural) together with an introductory understanding of quantum computation. This integrated understanding emphasizes physical insights together with a mathematical development.
Lecture notesLecture material and scripts
Prerequisites / NoticeThe course is an introduction to quantum, statistical and information theories for those who have not been exposed to these subjects, but are interested in gaining a useful understanding of them as well as their implications for computing techniques in general.
227-0303-00LAdvanced PhotonicsW6 credits2V + 2U + 1AA. Emboras, M. Burla, A. Dorodnyy
AbstractThe lecture gives a comprehensive insight into various types of nano-scale photonic devices, physical fundamentals of their operation, and an overview of the micro/nano-fabrication technologies. Following applications of nano-scale photonic structures are discussed in details: detectors, photovoltaic cells, atomic/ionic opto-electronic devices and integrated microwave photonics.
Learning objectiveGeneral training in advanced photonic devices with an in-depth understanding of the fundamentals of theory, fabrication, and characterization. Hands-on experience with photonic and optoelectronic device technologies and theory. The students will learn about the importance of advanced photonic devices in energy, communications, digital and neuromorphic computing applications.
ContentThe following topics will be addressed:
• Photovoltaics: basic thermodynamic principles and fundamental efficiency limitations, physics of semiconductor solar cell, overview of existing solar cell concepts and underlying physical phenomena.
• Micro/nano-fabrication technologies for advanced optoelectronic devices: introduction and device examples.
• Comprehensive insight into the physical mechanisms that govern ionic-atomic devices, present the techniques required to fabricate ultra-scaled nanostructures and show some applications in digital and neuromorphic computing.
• Introduction to microwave photonics (MWP), microwave photonic links, photonic techniques for microwave signal generation and processing.
Lecture notesThe presentation and the lecture notes will be provided every week.
Literature“Atomic/Ionic Devices”:
• Resistive Switching: From Fundamentals of Nanoionic Redox Processes to Memristive Device Applications, Daniele Ielmini and Rainer Waser, Wiley-VCH
• Electrochemical Methods: Fundamentals and Applications, A. Bard and L. Faulkner, John Willey & Sons, Inc.

“Photovoltaics”:
• Prof. Peter Wurfel: Physics of Solar Cells, Wiley

“Micro and nano Fabrication”:
• Prof. H. Gatzen, Prof. Volker Saile, Prof. Juerg Leuthold: Micro and Nano Fabrication, Springer

“Microwave Photonics”:
• D. M. Pozar, Microwave Engineering. J. Wiley & Sons, New York, 2005.
• M. Burla, Advanced integrated optical beam forming networks for broadband phased array antenna systems. Enschede, The Netherlands, 2013. DOI: 10.3990/1.9789036507295
• C.H. Cox, Analog optical links: theory and practice. Cambridge University Press, 2006.
Prerequisites / NoticeBasic knowledge of semiconductor physics, physics of the electromagnetic filed and thermodynamics.
227-0330-00LEnergy-Efficient Analog Circuits for IoT SystemsW6 credits2V + 2UT. Jang
AbstractWe are facing a new era of the Internet of things, similarly indicated as Industry 4.0, TSensors, Ubiquitous or The Fog. A miniaturized computer is the key to this innovation that senses, collects and processes information from objects. In this class, based on the recent publications, energy efficient analog IC techniques will be introduced which is the main challenge to reduce the battery size.
Learning objectiveThis class introduces key analog building blocks such as energy harvester, frequency generator, data converter, sensor interface, power converter based on the recent publications for IoT systems including wearable electronics, bio-implantable devices, and environmental sensors.
ContentUltra-low power circuit design methodology and transistor characteristics; Circuit-level design techniques for amplifier, comparator, voltage reference, on-chip oscillator, switched capacitor; IP-level design techniques for energy harvester, data converter, energy harvester and power converters.
Prerequisites / NoticeAnalog Integrated Circuits
227-0376-00LReliability of Electronic Equipment and Systems
The course will be offered for the last time in the Spring Semester 2020 and is merged with 227-0377-10L Physics of Failure and Reliability of Electronic Devices and Systems, a yearly recurring course in the autumn semester.
W4 credits2V + 1UU. Sennhauser, M. Held
AbstractReliability and availability are basic properties for safe and sustainable products in communications, energy and medical technology, air and space applications, and electronics. They are described as stochastic and physical processes and have to be optimized with functionality, environmental impact and life cycle costs in development phase already. The required basics will be taught.
Learning objectiveIntroduction to the concepts and methods of systems engineering for the design and production of reliable devices, equipment, and systems.
ContentQuality assurance of technical systems (introduction); introduction to stochastic processes; reliability analysis; design and investigation of fault-tolerant structures; component selection and qualification; maintainability analysis (introduction); software quality; design rules for reliability, maintainability, and software quality; availability analysis (introduction); reliability tests (introduction).
Lecture notesCopies of relevant transparencies and additional tables
LiteratureReliability Engineering, Springer 2004, ISBN 3-540-40287-X
227-0455-00LTerahertz: Technology and ApplicationsW5 credits3G + 3AK. Sankaran
AbstractThis block course will provide a solid foundation for understanding physical principles of THz applications. We will discuss various building blocks of THz technology - components dealing with generation, manipulation, and detection of THz electromagnetic radiation. We will introduce THz applications in the domain of imaging, sensing, communications, non-destructive testing and evaluations.
Learning objectiveThis is an introductory course on Terahertz (THz) technology and applications. Devices operating in THz frequency range (0.1 to 10 THz) have been increasingly studied in the recent years. Progress in nonlinear optical materials, ultrafast optical and electronic techniques has strengthened research in THz application developments. Due to unique interaction of THz waves with materials, applications with new capabilities can be developed. In theory, they can penetrate somewhat like X-rays, but are not considered harmful radiation, because THz energy level is low. They should be able to provide resolution as good as or better than magnetic resonance imaging (MRI), possibly with simpler equipment. Imaging, very-high bandwidth communication, and energy harvesting are the most widely explored THz application areas. We will study the basics of THz generation, manipulation, and detection. Our emphasis will be on the physical principles and applications of THz in the domain of imaging, sensing, communications, non-destructive testing and evaluations.

The second part of the block course will be a short project work related to the topics covered in the lecture. The learnings from the project work should be presented in the end.
ContentPART I:

- INTRODUCTION -
Chapter 1: Introduction to THz Physics
Chapter 2: Components of THz Technology

- THz TECHNOLOGY MODULES -
Chapter 3: THz Generation
Chapter 4: THz Detection
Chapter 5: THz Manipulation

- APPLICATIONS -
Chapter 6: THz Imaging / Sensing / Communication
Chapter 7: THz Non-destructive Testing
Chapter 8: THz Applications in Plastic & Recycling Industries

PART 2:

- PROJECT WORK -
Short project work related to the topics covered in the lecture.
Short presentation of the learnings from the project work.
Full guidance and supervision will be given for successful completion of the short project work.
Lecture notesSoft-copy of lectures notes will be provided.
Literature- Yun-Shik Lee, Principles of Terahertz Science and Technology, Springer 2009
- Ali Rostami, Hassan Rasooli, and Hamed Baghban, Terahertz Technology: Fundamentals and Applications, Springer 2010
Prerequisites / NoticeBasic foundation in physics, particularly, electromagnetics is required.
Students who want to refresh their electromagnetics fundamentals can get additional material required for the course.
227-0659-00LIntegrated Systems Seminar Information W1 credit1SF. K. Gürkaynak
AbstractIn the "Fachseminar IIS" the students learn to communicate topics, ideas or problems of scientific research by listening to more experienced authors and by presenting scientific work in a conference-like situation for a specific audience.
Learning objectiveThe seminar aims at instructing graduate and PhD students in the basics of presentation techniques, i.e. "how to give a professional talk". Attendees have the possibility to become acquainted with a current topic by a literature study, and to present the results thereof in a 20 minutes talk in English. The participation at the seminar gives also an overview on current problems in modern nanoelectronics and bio-electromagnetics.
ContentThe seminar topics' are design of digital integrated circuits, physical characterization in nanoelectronics and bio-electromagnetics Simulation.

The studens learn how to find the right literature for a certain topic quickly, as well as how to prepare a talk for a scientific conference, i.e. presentation techniques.
Lecture notesPresentation material
Literatureto be discussed with the advisor
227-0622-00LThermal Modeling: From Semiconductor to Medical Devices and Personalized Therapy PlanningW4 credits2V + 1UE. Neufeld, M. Luisier
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.
Learning 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
https://iis-students.ee.ethz.ch/lectures/thermal-modeling/
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.
227-0662-00LOrganic and Nanostructured Optics and Electronics (Course)
Does not take place this semester.
W3 credits2GV. Wood
AbstractThis course examines the optical and electronic properties of excitonic materials that can be leveraged to create thin-film light emitting devices and solar cells. Laboratory sessions provide students with experience in synthesis and optical characterization of nanomaterials as well as fabrication and characterization of thin film devices.
Learning objectiveGain the knowledge and practical experience to begin research with organic or nanostructured materials and understand the key challenges in this rapidly emerging field.
Content0-Dimensional Excitonic Materials (organic molecules and colloidal quantum dots)

Energy Levels and Excited States (singlet and triplet states, optical absorption and luminescence).

Excitonic and Polaronic Processes (charge transport, Dexter and Förster energy transfer, and exciton diffusion).

Devices (photodetectors, solar cells, and light emitting devices).
LiteratureLecture notes and reading assignments from current literature to be posted on website.
227-0662-10LOrganic and Nanostructured Optics and Electronics (Project) Information Restricted registration - show details
Does not take place this semester.
W3 credits2AV. Wood
AbstractThis course examines the optical and electronic properties of excitonic materials that can be leveraged to create thin-film light emitting devices and solar cells. Laboratory sessions provide students with experience in synthesis and optical characterization of nanomaterials as well as fabrication and characterization of thin film devices.
Learning objectiveGain the knowledge and practical experience to begin research with organic or nanostructured materials and understand the key challenges in this rapidly emerging field.
Content0-Dimensional Excitonic Materials (organic molecules and colloidal quantum dots)

Energy Levels and Excited States (singlet and triplet states, optical absorption and luminescence).

Excitonic and Polaronic Processes (charge transport, Dexter and Förster energy transfer, and exciton diffusion).

Devices (photodetectors, solar cells, and light emitting devices).
LiteratureLecture notes and reading assignments from current literature to be posted on website.
Prerequisites / NoticeAdmission is conditional to passing 227-0662-00L Organic and Nanostructured Optics and Electronics (Course)
227-0664-00LTechnology and Policy of Electrical Energy StorageW3 credits2GV. Wood, T. Schmidt
AbstractWith the global emphasis on decreasing CO2 emissions, achieving fossil fuel independence and growing the use of renewables, developing & implementing energy storage solutions for electric mobility & grid stabilization represent a key technology & policy challenge. This course uses lithium ion batteries as a case study to understand the interplay between technology, economics, and policy.
Learning objectiveThe students will learn of the complexity involved in battery research, design, production, as well as in investment, economics and policy making around batteries. Students from technical disciplines will gain insights into policy, while students from social science backgrounds will gain insights into technology.
ContentWith the global emphasis on decreasing CO2 emissions, achieving fossil fuel independence, and integrating renewables on the electric grid, developing and implementing energy storage solutions for electric mobility and grid stabilization represent a key technology and policy challenge. The class will focus on lithium ion batteries since they are poised to enter a variety of markets where policy decisions will affect their production, adoption, and usage scenarios. The course considers the interplay between technology, economics, and policy.

* intro to energy storage for electric mobility and grid-stabilization
* basics of battery operation, manufacturing, and integration
* intro to the role of policy for energy storage innovation & diffusion
* discussion of complexities involved in policy and politics of energy storage
Lecture notesMaterials will be made available on the website.
LiteratureMaterials will be made available on the website.
Prerequisites / NoticeStrong interest in energy and technology policy.
227-0669-00LChemistry of Devices and Technologies Restricted registration - show details
Limited to 30 participants.
W4 credits1V + 2UM. Yarema
AbstractThe course covers basics of chemistry and material science, relevant for modern devices and technologies. The course consists from lecture, laboratory, and individual components. Students accomplish individual projects, in which they study and evaluate a chosen technology from chemistry and materials viewpoints.
Learning objectiveThe course brings relevant chemistry knowledge, tailored to the needs of electrical engineering students. Students will gain understanding of the basic concepts of chemistry and a chemist's intuition through hands-on workshops that combine tutorials and laboratory sessions as well as guidance through individual projects that require interdisciplinary and critical thinking.
Students will learn which materials, reactions, and device fabrication processes are important for nowadays technologies and products. They will gain important knowledge of state-of-the-art technologies from materials and fabrication viewpoints.
ContentStudents will spend 3h per week in the tutorials and practical sessions and additional 4-6h per week working on individual projects.
The goal of the individual student's project is to understand the chemistry related to the manufacture and operation of a specific device or technology (to be chosen from the list of projects). To ensure continued learning throughout the semester, individual projects are evaluated by three interim project reports and by 10 min final presentation.
LiteratureLecture notes will be made available on the website.
227-0707-00LOptimization Methods for EngineersW3 credits2GP. Leuchtmann
AbstractFirst half of the semester: Introduction to the main methods of numerical optimization with focus on stochastic methods such as genetic algorithms, evolutionary strategies, etc.
Second half of the semester: Each participant implements a selected optimizer and applies it on a problem of practical interest.
Learning objectiveNumerical optimization is of increasing importance for the development of devices and for the design of numerical methods. The students shall learn to select, improve, and combine appropriate procedures for efficiently solving practical problems.
ContentTypical optimization problems and their difficulties are outlined. Well-known deterministic search strategies, combinatorial minimization, and evolutionary algorithms are presented and compared. In engineering, optimization problems are often very complex. Therefore, new techniques based on the generalization and combination of known methods are discussed. To illustrate the procedure, various problems of practical interest are presented and solved with different optimization codes.
Lecture notesPDF of a short skript (39 pages) plus the view graphs are provided
Prerequisites / NoticeLecture only in the first half of the semester, exercises in form of small projects in the second half, presentation of the results in the last week of the semester.
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