Search result: Catalogue data in Spring Semester 2020
|Process Engineering Master|
|151-0116-10L||High Performance Computing for Science and Engineering (HPCSE) for Engineers II||W||4 credits||4G||P. Koumoutsakos, S. M. Martin|
|Abstract||This course focuses on programming methods and tools for parallel computing on multi and many-core architectures. Emphasis will be placed on practical and computational aspects of Uncertainty Quantification and Propagation including the implementation of relevant algorithms on HPC architectures.|
|Objective||The course will teach |
- programming models and tools for multi and many-core architectures
- fundamental concepts of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences
|Content||High Performance Computing:|
- Advanced topics in shared-memory programming
- Advanced topics in MPI
- GPU architectures and CUDA programming
- Uncertainty quantification under parametric and non-parametric modeling uncertainty
- Bayesian inference with model class assessment
- Markov Chain Monte Carlo simulation
Class notes, handouts
|Literature||- Class notes|
- Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein
- CUDA by example, J. Sanders and E. Kandrot
- Data Analysis: A Bayesian Tutorial, D. Sivia and J. Skilling
- An introduction to Bayesian Analysis - Theory and Methods, J. Gosh, N. Delampady and S. Tapas
- Bayesian Data Analysis, A. Gelman, J. Carlin, H. Stern, D. Dunson, A. Vehtari and D. Rubin
- Machine Learning: A Bayesian and Optimization Perspective, S. Theodorides
|Prerequisites / Notice||Students must be familiar with the content of High Performance Computing for Science and Engineering I (151-0107-20L)|
|151-0118-00L||Applied Machine Learning for Engineers |
Number of participants limited to 40.
|W||4 credits||3G||B. Vennemann|
|Abstract||Introduction to the most frequently used methods of machine learning, including regression, classification, dimensionality reduction and selected topics of deep learning, including artificial neural networks, convolutional neural networks, recurrent neural networks and autoencoders. This lecture has a strong practical focus with programming sessions.|
|Objective||An understanding of the various tools within the machine learning landscape. Ability to select an appropriate method and to build, train and evaluate a model using Scikit-learn and Keras.|
|Content||Data preprocessing, regression, classification, dimensionality reduction, artificial neural networks, convolutional neural networks, recurrent neural networks, autoencoders.|
|Lecture notes||Lecture notes will be distributed electronically.|
|Prerequisites / Notice||Basic knowledge of the Python programming language. This course is mainly targeted towards master-level students of mechanical or process engineering.|
|151-0206-00L||Energy Systems and Power Engineering||W||4 credits||2V + 2U||R. S. Abhari, A. Steinfeld|
|Abstract||Introductory first course for the specialization in ENERGY. The course provides an overall view of the energy field and pertinent global problems, reviews some of the thermodynamic basics in energy conversion, and presents the state-of-the-art technology for power generation and fuel processing.|
|Objective||Introductory first course for the specialization in ENERGY. The course provides an overall view of the energy field and pertinent global problems, reviews some of the thermodynamic basics in energy conversion, and presents the state-of-the-art technology for power generation and fuel processing.|
|Content||World primary energy resources and use: fossil fuels, renewable energies, nuclear energy; present situation, trends, and future developments. Sustainable energy system and environmental impact of energy conversion and use: energy, economy and society. Electric power and the electricity economy worldwide and in Switzerland; production, consumption, alternatives. The electric power distribution system. Renewable energy and power: available techniques and their potential. Cost of electricity. Conventional power plants and their cycles; state-of-the -art and advanced cycles. Combined cycles and cogeneration; environmental benefits. Solar thermal power generation and solar photovoltaics. Hydrogen as energy carrier. Fuel cells: characteristics, fuel reforming and combined cycles. Nuclear power plant technology.|
|Lecture notes||Vorlesungsunterlagen werden verteilt|
|151-0208-00L||Computational Methods for Flow, Heat and Mass Transfer Problems||W||4 credits||4G||D. W. Meyer-Massetti|
|Abstract||Numerical methods for the solution of flow, heat & mass transfer problems are presented and illustrated by analytical & computer exercises.|
|Objective||Knowledge of and practical experience with discretization and solution methods for computational fluid dynamics and heat and mass transfer problems|
|Content||- Introduction with application examples, steps to a numerical solution|
- Classification of PDEs, application examples
- Finite differences
- Finite volumes
- Method of weighted residuals, spectral methods, finite elements
- Stability analysis, consistency, convergence
- Numerical solution methods, linear solvers
The learning materials are illustrated with practical examples.
|Lecture notes||Slides to be completed during the lecture will be handed out.|
|Literature||References are provided during the lecture. Notes in close agreement with the lecture material are available (in German).|
|Prerequisites / Notice||Basic knowledge in fluid dynamics, thermodynamics and programming (lecture: "Models, Algorithms and Data: Introduction to Computing")|
|151-0224-00L||Fuel Synthesis Engineering||W||4 credits||3V||B. Bulfin|
|Abstract||This course will include a revision of chemical engineering fundamentals and the basics of processes modelling for fuel synthesis technologies. Using this as a background we will then study a range of fuel production technologies, including established fossil fuel processing and emerging renewable fuel production processes.|
|Objective||1) Develop an understanding of the fundamentals of chemical process engineering, including chemical thermodynamics, molecular theory and kinetics. |
2) Learn to perform basic process modelling using some computational methods in order to analyse fuel production processes.
3) Using the fundamentals as a background, we will study a number of different fuel production processes, both conventional and emerging technologies.
|Content||Theory: Chemical equilibrium thermodynamics, reaction kinetics, and catalysis. |
Processes modelling: An introduction to using cantera to model chemical processes. This part of the course includes an optional project, where the student will perform a basic analysis of a natural gas to methanol conversion process.
Fuel synthesis topics: Conventional fuel production including oil refinery, upgrading of coal and natural gas, and biofuel. Emerging renewable fuel technologies including the conversion of renewable electricity to fuels via electrolysis, the conversion of heat to fuels via thermochemical cycles, and some other speculative fuel production processes.
|Lecture notes||Will be available electronically.|
|Literature||A) Physical Chemistry, 3rd edition, A. Alberty and J. Silbey, 2001|
B) Chemical Reaction Engineering, 3rd Edition, Octave Levenspiel, 1999
C) Fundamentals of industrial catalytic processes, C. H. Bartholomew, R. J. Farrauto, 2011;
|Prerequisites / Notice||Some previous studies in chemistry and chemical engineering are recommended, but not absolutely necessary. Experience with either Python or Matlab is also recommended.|
|151-0280-00L||Advanced Techniques for the Risk Analysis of Technical Systems||W||4 credits||2V + 1U||G. Sansavini|
|Abstract||The course provides advanced tools for the risk/vulnerability analysis and engineering of complex technical systems and critical infrastructures. It covers application of modeling techniques and design management concepts for strengthening the performance and robustness of such systems, with reference to energy, communication and transportation systems.|
|Objective||Students will be able to model complex technical systems and critical infrastructures including their dependencies and interdependencies. They will learn how to select and apply appropriate numerical techniques to quantify the technical risk and vulnerability in different contexts (Monte Carlo simulation, Markov chains, complex network theory). Students will be able to evaluate which method for quantification and propagation of the uncertainty of the vulnerability is more appropriate for various complex technical systems. At the end of the course, they will be able to propose design improvements and protection/mitigation strategies to reduce risks and vulnerabilities of these systems.|
|Content||Modern technical systems and critical infrastructures are complex, highly integrated and interdependent. Examples of these are highly integrated energy supply, energy supply with high penetrations of renewable energy sources, communication, transport, and other physically networked critical infrastructures that provide vital social services. As a result, standard risk-assessment tools are insufficient in evaluating the levels of vulnerability, reliability, and risk. |
This course offers suitable analytical models and computational methods to tackle this issue with scientific accuracy. Students will develop competencies which are typically requested for the formation of experts in reliability design, safety and protection of complex technical systems and critical infrastructures.
Specific topics include:
- Introduction to complex technical systems and critical infrastructures
- Basics of the Markov approach to system modeling for reliability and availability analysis
- Monte Carlo simulation for reliability and availability analysis
- Markov Chain Monte Carlo for applications to reliability and availability analysis
- Dependent, common cause and cascading failures
- Complex network theory for the vulnerability analysis of complex technical systems and critical infrastructures
- Basic concepts of uncertainty and sensitivity analysis in support to the analysis of the reliability and risk of complex systems under incomplete knowledge of their behavior
Practical exercitations and computational problems will be carried out and solved both during classroom tutorials and as homework.
|Lecture notes||Slides and other materials will be available online|
|Literature||The class will be largely based on the books:|
- "Computational Methods For Reliability And Risk Analysis" by E. Zio, World Scientific Publishing Company
- "Vulnerable Systems" by W. Kröger and E. Zio, Springer
- additional recommendations for text books will be covered in the class
|Prerequisites / Notice||Fundamentals of Probability|
|151-0902-00L||Micro- and Nanoparticle Technology||W||6 credits||2V + 2U||S. E. Pratsinis, M. Eggersdorfer, A. Güntner, G. Kelesidis, K. Wegner|
|Abstract||Introduction to fundamentals of micro- and nanoparticle synthesis and processing. Characterization of suspensions, sampling and measuring techniques; basics of gas-solid and liquid-solid systems; fragmentation, coagulation, growth, separation, fluidization, filtration, mixing, transport, coatings. Particle processing in manufacture of catalysts, sensors, nanocomposites and chemical commodities.|
|Objective||Introduction to design methods of mechanical processes, scale-up laws and optimal use of materials and energy|
|Content||Characterisation of particle suspensions and corresponding measuring techniques; basic laws of gas / solids resp. Liquid / solids systems; unit operations of mechanical processing:|
desintegration, agglomeration, screening, air classifying, sedimentation, filtration, particle separation from gas streams, mixing, pneumatic conveying. Synthesis of unit operations to process systems in chemical industry, cement industry etc.
|Lecture notes||Mechanical Process Engineering I|
|151-0926-00L||Separation Process Technology I||W||4 credits||3G||M. Mazzotti|
|Abstract||Non-empirical design of gas-liquid, vapor-liquid, and liquid-liquid separation processes for ideal and non-ideal systems, based on mass transfer phenomena and phase equilibrium.|
|Objective||Non-empirical design of gas-liquid, vapor-liquid, and liquid-liquid separation processes for ideal and non-ideal systems, based on mass transfer phenomena and phase equilibrium.|
|Content||Methods for the non empirical design of equilibrium stage separations for ideal and non-ideal systems, based on mass transfer phenomena and phase equilibrium. Topics: introduction to the separation process technology. Phase equilibrium: vapor/liquid and liquid/liquid. Flash vaporization: binary and multicomponent. Equilibrium stages and multistage cascades. Gas absorption and stripping. Continuous distillation: design methods for binary and multicomponent systems; continuous-contact equipment; azeotropic distillation, equipment for gas-liquid operations. Liquid/liquid extraction. The lecture is supported by a web base learning tool, i.e. HyperTVT.|
|Lecture notes||Lecture notes available|
|Literature||Treybal "Mass-transfer operations" oder Seader/Henley "Separation process principles" oder Wankat "Equilibrium stage separations" oder Weiss/Militzer/Gramlich "Thermische Verfahrenstechnik"|
|Prerequisites / Notice||Prerequisite: Stoffaustausch|
A self-learning web-based environment is available (HyperTVT):
|151-0928-00L||CO2 Capture and Storage and the Industry of Carbon-Based Resources||W||4 credits||3G||M. Mazzotti, L. Bretschger, N. Gruber, C. Müller, M. Repmann, T. Schmidt, D. Sutter|
|Abstract||Carbon-based resources (coal, oil, gas): origin, production, processing, resource economics. Climate change: science, policies. CCS systems: CO2 capture in power/industrial plants, CO2 transport and storage. Besides technical details, economical, legal and societal aspects are considered (e.g. electricity markets, barriers to deployment).|
|Objective||The goal of the lecture is to introduce carbon dioxide capture and storage (CCS) systems, the technical solutions developed so far and the current research questions. This is done in the context of the origin, production, processing and economics of carbon-based resources, and of climate change issues. After this course, students are familiar with important technical and non-technical issues related to use of carbon resources, climate change, and CCS as a transitional mitigation measure.|
The class will be structured in 2 hours of lecture and one hour of exercises/discussion. At the end of the semester a group project is planned.
|Content||Both the Swiss and the European energy system face a number of significant challenges over the coming decades. The major concerns are the security and economy of energy supply and the reduction of greenhouse gas emissions. Fossil fuels will continue to satisfy the largest part of the energy demand in the medium term for Europe, and they could become part of the Swiss energy portfolio due to the planned phase out of nuclear power. Carbon capture and storage is considered an important option for the decarbonization of the power sector and it is the only way to reduce emissions in CO2 intensive industrial plants (e.g. cement- and steel production). |
Building on the previously offered class "Carbon Dioxide Capture and Storage (CCS)", we have added two specific topics: 1) the industry of carbon-based resources, i.e. what is upstream of the CCS value chain, and 2) the science of climate change, i.e. why and how CO2 emissions are a problem.
The course is devided into four parts:
I) The first part will be dedicated to the origin, production, and processing of conventional as well as of unconventional carbon-based resources.
II) The second part will comprise two lectures from experts in the field of climate change sciences and resource economics.
III) The third part will explain the technical details of CO2 capture (current and future options) as well as of CO2 storage and utilization options, taking again also economical, legal, and sociatel aspects into consideration.
IV) The fourth part will comprise two lectures from industry experts, one with focus on electricity markets, the other on the experiences made with CCS technologies in the industry.
Throughout the class, time will be allocated to work on a number of tasks related to the theory, individually, in groups, or in plenum. Moreover, the students will apply the theoretical knowledge acquired during the course in a case study covering all the topics.
|Lecture notes||Power Point slides and distributed handouts|
|Literature||IPCC Special Report on Global Warming of 1.5°C, 2018.|
IPCC AR5 Climate Change 2014: Synthesis Report, 2014. www.ipcc.ch/report/ar5/syr/
IPCC Special Report on Carbon dioxide Capture and Storage, 2005. www.ipcc.ch/activity/srccs/index.htm
The Global Status of CCS: 2014. Published by the Global CCS Institute, Nov 2014.
|Prerequisites / Notice||External lecturers from the industry and other institutes will contribute with specialized lectures according to the schedule distributed at the beginning of the semester.|
|151-0931-00L||Seminar on Particle Technology||Z||0 credits||3S||S. E. Pratsinis|
|Abstract||The latest advances in particle technology are highlighted focusing on aerosol fundamentals in connection to materials processing and nanoscale engineering. Students attend and give research presentations for the research they plan to do and at the end of the semester they defend their results and answer questions from research scientists. Familiarize the students with the latest in this field.|
|Objective||The goal of the seminar is to introduce and discuss newest developments in particle science and engineering. Emphasis is placed on the oral presentation of research results, validation and comparison with existing |
data from the literature. Students learn how to organize and deliver effectively a scientific presentation and how to articulate and debate scientific results.
|Content||The seminar addresses synthesis, characterization, handling and modeling of particulate systems (aerosols, suspensions etc.) for applications in ceramics, catalysis, reinforcements, pigments, composites etc. on the examples of newest research developments. It comprises particle - particle interactions, particle - fluid interactions and the response of the particulate system to the specific application.|
|Prerequisites / Notice||Voraussetzungen: Particle Technology (30-902) or Particulate Processes (151-0903-00)|
|151-0940-00L||Modelling and Mathematical Methods in Process and Chemical Engineering||W||4 credits||3G||M. Mazzotti|
|Abstract||Study of the non-numerical solution of systems of ordinary differential equations and first order partial differential equations, with application to chemical kinetics, simple batch distillation, and chromatography.|
|Objective||Study of the non-numerical solution of systems of ordinary differential equations and first order partial differential equations, with application to chemical kinetics, simple batch distillation, and chromatography.|
|Content||Development of mathematical models in process and chemical engineering, particularly for chemical kinetics, batch distillation, and chromatography. Study of systems of ordinary differential equations (ODEs), their stability, and their qualitative analysis. Study of single first order partial differential equation (PDE) in space and time, using the method of characteristics. Application of the theory of ODEs to population dynamics, chemical kinetics (Belousov-Zhabotinsky reaction), and simple batch distillation (residue curve maps). Application of the method of characteristic to chromatography.|
|Lecture notes||no skript|
|Literature||A. Varma, M. Morbidelli, "Mathematical methods in chemical engineering," Oxford University Press (1997) |
H.K. Rhee, R. Aris, N.R. Amundson, "First-order partial differential equations. Vol. 1," Dover Publications, New York (1986)
R. Aris, "Mathematical modeling: A chemical engineer’s perspective," Academic Press, San Diego (1999)
|151-0944-00L||Case Studies on Earth's Natural Resources|
Does not take place this semester.
|W||3 credits||3S||M. Mazzotti|
|Abstract||By working on case studies, built around everyday consumer products, and by applying engineering principles (e.g. material and energy balances), students will gain insight into natural resources, their usage in today's society, the challenges and the opportunities ensuing from the need to make their use long-term sustainable.|
|Objective||The students are supposed to gain insight about our natural resources, and how their usage and supply relate to our society and to us as individuals. The students will analyse how the natural resources form and change, how they are extracted and used, and how we can utilize them in a sustainable way.|
|Content||The students will analyze processes and products in terms of their use of natural resources. The study will use everyday consumer products as examples, will use engineering principles together with physics and chemistry fro the analysis, and will be based on documentation collected by the students withe the help of lecturer and assistants. Through these examples, the students will be made familiar with issues about the circular economy and recycling.|
|Lecture notes||Handouts during the class.|
|Literature||Walther, John V., "Earth's natural resources", (2014) Jones & Bartlett Learning // Oberle, B., Bringezu, S., Hatfield-Dodds, S., Hellweg, S., Schandl, H., Clement, J., "Global Resources Outlook 2019: Natural resources for the future we want - A Report of the International Resource Panel", (2019) United Nations Environment Programme.|
|Prerequisites / Notice||Students must be enrolled in a MSc or doctoral program at ETH Zurich.|
|151-0946-00L||Macromolecular Engineering: Networks and Gels||W||4 credits||4G||M. Tibbitt|
|Abstract||This course will provide an introduction to the design and physics of soft matter with a focus on polymer networks and hydrogels. The course will integrate fundamental aspects of polymer physics, engineering of soft materials, mechanics of viscoelastic materials, applications of networks and gels in biomedical applications including tissue engineering, 3D printing, and drug delivery.|
|Objective||The main learning objectives of this course are: 1. Identify the key characteristics of soft matter and the properties of ideal and non-ideal macromolecules. 2. Calculate the physical properties of polymers in solution. 3. Predict macroscale properties of polymer networks and gels based on constituent chemical structure and topology. 4. Design networks and gels for industrial and biomedical applications. 5. Read and evaluate research papers on recent research on networks and gels and communicate the content orally to a multidisciplinary audience.|
|Lecture notes||Class notes and handouts.|
|Literature||Polymer Physics by M. Rubinstein and R.H. Colby; samplings from other texts.|
|Prerequisites / Notice||Physics I+II, Thermodynamics I+II|
|151-1906-00L||Multiphase Flow||W||4 credits||3G||H.‑M. Prasser|
|Abstract||Basics in multiphase flow systems,, mainly gas-liquid, is presented in this course. An introduction summarizes the characteristics of multi phase flows, some theoretical models are discussed. Following we focus on pipe flow, film and bubbly/droplet flow. Finally specific measuring methods are shown and a summary of the CFD models for multiphases is presented.|
|Objective||This course contributes to a deep understanding of complex multiphase systems and allows to predict multiphase conditions to design appropriate systems/apparatus. Actual examples and new developments are presented.|
|Content||The course gives an overview on following subjects: Basics in multiphase systems, pipeflow, films, bubbles and bubble columns, droplets, measuring techniques, multiphase flow in microsystems, numerical procedures with multiphase flows.|
|Lecture notes||Lecturing notes are available (copy of slides or a german script) partly in english|
|Literature||Special literature is recommended for each chapter.|
|Prerequisites / Notice||The course builds on the basics in fluidmechanics.|
|151-2016-00L||Radiation Imaging for Industrial Applications||W||4 credits||2V + 1U||H.‑M. Prasser, R. Adams|
|Abstract||The course gives an overview of the physics and practical principles of imaging techniques using ionizing radiation such as X-rays, gamma photons, and neutrons in the context of various industrial (non-medical) challenges. This includes the interaction of radiation with matter, parameters affecting imaging performance, source and detector technology, image processing, and tomographic techniques.|
|Objective||Understanding of the principles and applicability of various radiation-based imaging techniques including radiography and tomography to various industrial challenges.|
|Content||principles of radiation imaging; physics of interaction of radiation with matter (X-ray, gamma, neutron); X-ray source physics and technology; neutron source physics and technology; radiation detection principles; radiation detection as applied to imaging; radiography (image quality parameters, image processing); computed tomography (image reconstruction techniques, artifacts, image processing); overview of more exotic techniques (e.g. dual modality, fast neutrons, time of flight); general industrial applications, security applications; special issues in dynamic imaging and example applications; PET/PEPT imaging; nuclear energy applications|
|Lecture notes||Lecture slides will be provided, as well as references for further reading|
|Literature||- Wang, Industrial Tomography: Systems and Applications|
- Knoll, Radiation Detection and Measurement
- Kak & Slaney, Principles of Computerized Tomographic Imaging
|Prerequisites / Notice||Recommended courses (not binding): 151-0163-00L Nuclear Energy Conversion, 151-2035-00L, Radiobiology and Radiation Protection, 151-0123-00L, Experimental Methods for Engineers, MATLAB skills for exercises.|
|227-0966-00L||Quantitative Big Imaging: From Images to Statistics||W||4 credits||2V + 1U||P. A. Kaestner, M. Stampanoni|
|Abstract||The lecture focuses on the challenging task of extracting robust, quantitative metrics from imaging data and is intended to bridge the gap between pure signal processing and the experimental science of imaging. The course will focus on techniques, scalability, and science-driven analysis.|
|Objective||1. Introduction of applied image processing for research science covering basic image processing, quantitative methods, and statistics.|
2. Understanding of imaging as a means to accomplish a scientific goal.
3. Ability to apply quantitative methods to complex 3D data to determine the validity of a hypothesis
|Content||Imaging is a well established field and is rapidly growing as technological improvements push the limits of resolution in space, time, material and functional sensitivity. These improvements have meant bigger, more diverse datasets being acquired at an ever increasing rate. With methods varying from focused ion beams to X-rays to magnetic resonance, the sources for these images are exceptionally heterogeneous; however, the tools and techniques for processing these images and transforming them into quantitative, biologically or materially meaningful information are similar. |
The course consists of equal parts theory and practical analysis of first synthetic and then real imaging datasets. Basic aspects of image processing are covered such as filtering, thresholding, and morphology. From these concepts a series of tools will be developed for analyzing arbitrary images in a very generic manner. Specifically a series of methods will be covered, e.g. characterizing shape, thickness, tortuosity, alignment, and spatial distribution of material features like pores. From these metrics the statistics aspect of the course will be developed where reproducibility, robustness, and sensitivity will be investigated in order to accurately determine the precision and accuracy of these quantitative measurements. A major emphasis of the course will be scalability and the tools of the 'Big Data' trend will be discussed and how cluster, cloud, and new high-performance large dataset techniques can be applied to analyze imaging datasets. In addition, given the importance of multi-scale systems, a data-management and analysis approach based on modern databases will be presented for storing complex hierarchical information in a flexible manner. Finally as a concluding project the students will apply the learned methods on real experimental data from the latest 3D experiments taken from either their own work / research or partnered with an experimental imaging group.
The course provides the necessary background to perform the quantitative evaluation of complicated 3D imaging data in a minimally subjective or arbitrary manner to answer questions coming from the fields of physics, biology, medicine, material science, and paleontology.
|Lecture notes||Available online.|
|Literature||Will be indicated during the lecture.|
|Prerequisites / Notice||Ideally students will have some familiarity with basic manipulation and programming in languages like Python, Matlab, or R. Interested students who are worried about their skill level in this regard are encouraged to contact Per Anders Kaestner directly (email@example.com).|
More advanced students who are familiar with Python, C++, (or in some cases Java) will have to opportunity to develop more of their own tools.
|529-0191-01L||Electrochemical Energy Conversion and Storage Technologies||W||4 credits||3G||L. Gubler, E. Fabbri, J. Herranz Salañer|
|Abstract||The course provides an introduction to the principles and applications of electrochemical energy conversion (e.g. fuel cells) and storage (e.g. batteries) technologies in the broader context of a renewable energy system.|
|Objective||Students will discover the importance of electrochemical energy conversion and storage in energy systems of today and the future, specifically in the framework of renewable energy scenarios. Basics and key features of electrochemical devices will be discussed, and applications in the context of the overall energy system will be highlighted with focus on future mobility technologies and grid-scale energy storage. Finally, the role of (electro)chemical processes in power-to-X and deep decarbonization concepts will be elaborated.|
|Content||Overview of energy utilization: past, present and future, globally and locally; today’s and future challenges for the energy system; climate changes; renewable energy scenarios; introduction to electrochemistry; electrochemical devices, basics and their applications: batteries, fuel cells, electrolyzers, flow batteries, supercapacitors, chemical energy carriers: hydrogen & synthetic natural gas; electromobility; grid-scale energy storage, power-to-gas, power-to-X and deep decarbonization, techno-economics and life cycle analysis.|
|Lecture notes||all lecture materials will be available for download on the course website.|
|Literature||- M. Sterner, I. Stadler (Eds.): Handbook of Energy Storage (Springer, 2019).|
- C.H. Hamann, A. Hamnett, W. Vielstich; Electrochemistry, Wiley-VCH (2007).
- T.F. Fuller, J.N. Harb: Electrochemical Engineering, Wiley (2018)
|Prerequisites / Notice||Basic physical chemistry background required, prior knowledge of electrochemistry basics desired.|
|529-0633-00L||Heterogeneous Reaction Engineering||W||4 credits||3G||J. Pérez-Ramírez, C. Mondelli|
|Abstract||Heterogeneous Reaction Engineering equips students with tools essential for the optimal development of heterogeneous processes. Integrating concepts from chemical engineering and chemistry, students will be introduced to the fundamental principles of heterogeneous reactions and will develop the necessary skills for the selection and design of various types of idealized reactors.|
|Objective||At the end of the course the students will understand the basic principles of catalyzed and uncatalyzed heterogeneous reactions. They will know models to represent fluid-fluid and fluid-solid reactions; how to describe the kinetics of surface reactions; how to evaluate mass and heat transfer phenomena and account for their impact on catalyst effectiveness; the principle causes of catalyst deactivation; and reactor systems and protocols for catalyst testing.|
|Content||The following components are covered: |
- Fluid-fluid and fluid-solid heterogeneous reactions.
- Kinetics of surface reactions.
- Mass and heat transport phenomena.
- Catalyst effectiveness.
- Catalyst deactivation.
- Strategies for catalyst testing.
These aspects are exemplified through modern examples.
For each core topic exercises are assigned and evaluated.
The course also features an industrial lecture.
|Lecture notes||A dedicated script and lecture slides are available in printed form during the course.|
|Literature||H. Scott Fogler: Elements of Chemical Reaction Engineering, Prentice Hall, New Jersey, 1992|
O. Levenspiel: Chemical Reaction Engineering, 3rd edition, John Wiley & Sons, New Jersey, 1999
Further relevant sources are given during the course.
|636-0111-00L||Synthetic Biology I|
Attention: This course was offered in previous semesters with the number: 636-0002-00L "Synthetic Biology I". Students that already passed course 636-0002-00L cannot receive credits for course 636-0111-00L.
|W||4 credits||3G||S. Panke, J. Stelling|
|Abstract||Theoretical & practical introduction into the design of dynamic biological systems at different levels of abstraction, ranging from biological fundamentals of systems design (introduction to bacterial gene regulation, elements of transcriptional & translational control, advanced genetic engineering) to engineering design principles (standards, abstractions) mathematical modelling & systems desig|
|Objective||After the course, students will be able to theoretically master the biological and engineering fundamentals required for biological design to be able to participate in the international iGEM competition (see www.igem.ethz.ch).|
|Content||The overall goal of the course is to familiarize the students with the potential, the requirements and the problems of designing dynamic biological elements that are of central importance for manipulating biological systems, primarily (but not exclusively) prokaryotic systems. Next, the students will be taken through a number of successful examples of biological design, such as toggle switches, pulse generators, and oscillating systems, and apply the biological and engineering fundamentals to these examples, so that they get hands-on experience on how to integrate the various disciplines on their way to designing biological systems.|
|Lecture notes||Handouts during classes.|
|Literature||Mark Ptashne, A Genetic Switch (3rd ed), Cold Spring Haror Laboratory Press|
Uri Alon, An Introduction to Systems Biology, Chapman & Hall
|Prerequisites / Notice||1) Though we do not place a formal requirement for previous participation in particular courses, we expect all participants to be familiar with a certain level of biology and of mathematics. Specifically, there will be material for self study available on https://bsse.ethz.ch/bpl/education/lectures/synthetic-biology-i/download.html as of mid January, and everybody is expected to be fully familiar with this material BEFORE THE CLASS BEGINS to be able to follow the different lectures. Please contact firstname.lastname@example.org for access to material|
2) The course is also thought as a preparation for the participation in the international iGEM synthetic biology summer competition (www.syntheticbiology.ethz.ch, http://www.igem.org). This competition is also the contents of the course Synthetic Biology II. https://bsse.ethz.ch/bpl/education/lectures/synthetic-biology-i/download.html
| Multidisciplinary Courses|
The students are free to choose individually from the Course Catalogue of ETH Zurich, ETH Lausanne and the Universities of Zurich and St. Gallen.
|» Course Catalogue of ETH Zurich|
|151-1008-00L||Semester Project Process Engineering |
Only for Process Engineering MSc.
The subject of the Master Thesis and the choice of the supervisor (ETH-professor) are to be approved in advance by the tutor.
|Abstract||The semester project is designed to train the students in the solution of specific engineering problems. This makes use of the technical and social skills acquired during the master's program. Tutors propose the subject of the project, elaborate the project plan, and define the roadmap together with their students, as well as monitor the overall execution.|
|Objective||The semester project is designed to train the students in the solution of specific engineering problems. This makes use of the technical and social skills acquired during the master's program.|
Access to the company list and request for recognition under www.mavt.ethz.ch/praxis.
No registration required via myStudies.
|O||8 credits||external organisers|
|Abstract||The main objective of the minimum twelve-week internship is to expose Master’s students to the industrial work environment. The aim of the Industrial Internship is to apply engineering knowledge to practical situations.|
|Objective||The aim of the Industrial Internship is to apply engineering knowledge to practical situations.|
|GESS Science in Perspective|
|» see Science in Perspective: Type A: Enhancement of Reflection Capability|
|» Recommended Science in Perspective (Type B) for D-MAVT|
|» see Science in Perspective: Language Courses ETH/UZH|
|151-1005-00L||Master's Thesis Process Engineering |
Students who fulfill the following criteria are allowed to begin with their Master's Thesis:
a. successful completion of the bachelor program;
b. fulfilling of any additional requirements necessary to gain admission to the master programme;
c. successful completion of the semester project and industrial internship;
d. achievement of 28 ECTS in the category "Core Courses".
The Master's Thesis must be approved in advance by the tutor and is supervised by a professor of ETH Zurich.
To choose a titular professor as a supervisor, please contact the D-MAVT Student Administration.
|Abstract||Master's programs are concluded by the master's thesis. The thesis is aimed at enhancing the student's capability to work independently toward the solution of a theoretical or applied problem. The subject of the master's thesis, as well as the project plan and roadmap, are proposed by the tutor and further elaborated with the student.|
|Objective||The thesis is aimed at enhancing the student's capability to work independently toward the solution of a theoretical or applied problem.|