Lucio Isa: Catalogue data in Autumn Semester 2022

Award: The Golden Owl
Name Prof. Dr. Lucio Isa
FieldSoft Materials and Interfaces
Weiche Materialien u. Grenzflächen
ETH Zürich, HCI H 525
Vladimir-Prelog-Weg 1-5/10
8093 Zürich
Telephone+41 44 633 63 76
RelationshipFull Professor

327-0113-00LFoundations of Materials Science I2 credits2GL. Isa
AbstractThe basic physical concepts for the description of materials are taught, partly in self-study, and applied in exercises. Basic atomistic and macroscopic concepts (e.g. phase diagrams, phase transformations, response functions) are introduced through examples. Selected topics are deepened in classroom lectures.
ObjectiveStudents are able to

- name the basic concepts of materials science. (remember, 1)

- describe simple relations between atomic structure and macroscopic properties. (understand, 2)

- calculate basic material-specific quantities. (apply, 3)

- read and interpret phase diagrams, material characteristic (e.g. stress-strain) diagrams and Ashby plots (analyse, 4)
ContentAtomic structure
Crystalline structure and defects
Thermodynamics, phase diagrams and phase transformations
Mechanical and thermal properties of materials
LiteratureMain textbook:
William D. Callister, Jr., David G. Rethwisch
Materials Science and Engineering - An Introduction
8th Ed., Wiley, Hoboken NJ, 2011

Milton Ohring
Engineering Materials Science
Academic Press, 1995,

James F. Shackelford
Introduction to Materials Science for Engineers
5th Ed., Prentice Hall, New Jersey, 2000
327-0505-00LSurfaces, Interfaces and their Applications I3 credits2V + 1UN. Spencer, M. P. Heuberger, L. Isa
AbstractAfter being introduced to the physical/chemical principles and importance of surfaces and interfaces, the student is introduced to the most important techniques that can be used to characterize surfaces. Later, liquid interfaces are treated, followed by an introduction to the fields of tribology (friction, lubrication, and wear) and corrosion.
ObjectiveTo gain an understanding of the physical and chemical principles, as well as the tools and applications of surface science, and to be able to choose appropriate surface-analytical approaches for solving problems.
ContentIntroduction to Surface Science
Physical Structure of Surfaces
Surface Forces (static and dynamic)
Adsorbates on Surfaces
Surface Thermodynamics and Kinetics
The Solid-Liquid Interface
Electron Spectroscopy
Vibrational Spectroscopy on Surfaces
Scanning Probe Microscopy
Introduction to Tribology
Introduction to Corrosion Science
Lecture notesScript Download:
LiteratureScript Download:
Book: "Surface Analysis--The Principal Techniques", Ed. J.C. Vickerman, Wiley, ISBN 0-471-97292
Prerequisites / NoticeChemistry:
General undergraduate chemistry
including basic chemical kinetics and thermodynamics

General undergraduate physics
including basic theory of diffraction and basic knowledge of crystal structures
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Personal CompetenciesCreative Thinkingassessed
Critical Thinkingassessed
327-1207-00LEngineering with Soft Materials5 credits4GJ. Vermant, L. Isa
AbstractIn this course the engineering with soft materials is discussed. First, scaling principles to design structural and functional properties are introduced a. Second, the characterisation techniques to interrogate the structure property relations are introduced, which include rheology, advanced optical microscopies, static and dynamic scattering and techniques for liquid interfaces.
ObjectiveThe learning goals of the course are to introduce the students to soft matter and its technological applications, to see how the structure property relations depend on fundamental formulation properties and processing steps. Students should also be able to select a measurement technique to evaluate the properties.
Lecture notesslides with text notes accompanying each slide are presented.
327-2227-00LMachine Learning (MaP Doctoral School) Restricted registration - show details
Number of participants limited to 15.

Only for doctoral students of the MaP Doctoral School. Priority is given to doctoral students affiliated with the “Soft Materials” thematic track.

All applicants must additionally register by email: Link
6 credits13PL. Isa
AbstractMicroscopy images, irrespective of the specific imaging technique, e.g. optical, electron or atomic force microscopy, are an extremely rich source of quantitative data. With the ever increasing push to enhance spatial and temporal resolution, as well as with the increase of storage and computing power, very large amounts of data are easily generated and require automation for data extraction. From
ObjectiveThis course, aimed at doctoral students, has the goal to guide attendees through a progression from basic machine learning (ML) methods, through the extension of those to increasingly complex analyses all the way to offering the students the possibility to directly apply the concepts learned during the course to their own data.
ContentThe course will combine lectures with hands-on exercises in concentrated blocks across the semester. Students have the possibility to select different blocks, for instance if they already have basic ML programming knowledge. The students will also be able to work on a project related to their research where they apply ML to some imaging data.
Prerequisites / NoticeBasic programming knowledge in Python is required.