227-0161-00L Molecular and Materials Modelling
| Semester | Spring Semester 2021 |
| Lecturers | D. Passerone, C. Pignedoli |
| Periodicity | yearly recurring course |
| Language of instruction | English |
Courses
| Number | Title | Hours | Lecturers | ||||
|---|---|---|---|---|---|---|---|
| 227-0161-00 V | Molecular and Materials Modelling A hands-on course on atomistic simulations (classical and ab initio) applied to realistic systems. The exercises, focused on the analysis of calculations performed on the most advanced packages installed in the Lugano supercomputing center, will be in part based on Jupyter notebooks. Thus a basic knowledge of python is desirable. | 2 hrs |
| D. Passerone, C. Pignedoli | |||
| 227-0161-00 U | Molecular and Materials Modelling A hands-on course on atomistic simulations (classical and ab initio) applied to realistic systems. The exercises, focused on the analysis of calculations performed on the most advanced packages installed in the Lugano supercomputing center, will be in part based on Jupyter notebooks. Thus a basic knowledge of python is desirable. | 2 hrs |
| D. Passerone, C. Pignedoli |
Catalogue data
| Abstract | The course introduces the basic techniques to interpret experiments with contemporary atomistic simulation, including force fields or ab initio based molecular dynamics and Monte Carlo. Structural and electronic properties will be simulated hands-on for realistic systems. The modern methods of "big data" analysis applied to the screening of chemical structures will be introduced with examples. |
| Objective | The ability to select a suitable atomistic approach to model a nanoscale system, and to employ a simulation package to compute quantities providing a theoretically sound explanation of a given experiment. This includes knowledge of empirical force fields and insight in electronic structure theory, in particular density functional theory (DFT). Understanding the advantages of Monte Carlo and molecular dynamics (MD), and how these simulation methods can be used to compute various static and dynamic material properties. Basic understanding on how to simulate different spectroscopies (IR, X-ray, UV/VIS). Performing a basic computational experiment: interpreting the experimental input, choosing theory level and model approximations, performing the calculations, collecting and representing the results, discussing the comparison to the experiment. |
| Content | -Classical force fields in molecular and condensed phase systems -Methods for finding stationary states in a potential energy surface -Monte Carlo techniques applied to nanoscience -Classical molecular dynamics: extracting quantities and relating to experimentally accessible properties -From molecular orbital theory to quantum chemistry: chemical reactions -Condensed phase systems: from periodicity to band structure -Larger scale systems and their electronic properties: density functional theory and its approximations -Advanced molecular dynamics: Correlation functions and extracting free energies -The use of Smooth Overlap of Atomic Positions (SOAP) descriptors in the evaluation of the (dis)similarity of crystalline, disordered and molecular compounds |
| Lecture notes | A script will be made available and complemented by literature references. |
| Literature | D. Frenkel and B. Smit, Understanding Molecular Simulations, Academic Press, 2002. M. P. Allen and D.J. Tildesley, Computer Simulations of Liquids, Oxford University Press 1990. C. J. Cramer, Essentials of Computational Chemistry. Theories and Models, Wiley 2004 G. L. Miessler, P. J. Fischer, and Donald A. Tarr, Inorganic Chemistry, Pearson 2014. K. Huang, Statistical Mechanics, Wiley, 1987. N. W. Ashcroft, N. D. Mermin, Solid State Physics, Saunders College 1976. E. Kaxiras, Atomic and Electronic Structure of Solids, Cambridge University Press 2010. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 4 credits |
| Examiners | D. Passerone, C. Pignedoli |
| Type | graded semester performance |
| Language of examination | English |
| Repetition | Repetition only possible after re-enrolling for the course unit. |
| Admission requirement | Attendance to the lecture is strongly advised since the lecturers are giving the necessary complements to students with possible background gaps in a particular topic. Attendance to the exercises is also necessary to get acquainted with the simulation method and scientific computing with hands-on activities. Full support will be given by teachers and assistants during the exercises and by E-Mail. |
| Additional information on mode of examination | The final grade will be the result of a 45 minutes individual oral exam on the course topics (75%) and a group project that will be performed by groups of 3 to 5 students during the semester (25%). In this "miniature research project", the student groups will pick up a project from a list provided by the teacher. These projects are "extended exercises" (compared to the ones performed in class). The project will consist of performing simulations, improving Jupyter notebooks for the data analysis, writing a short report containing data assessment and interpretation, as well as presenting the results with a few slides (one representative person per group). |
Learning materials
| Main link | Web page of our research group in computational nanoscience. |
| Only public learning materials are listed. | |
Groups
| No information on groups available. |
Restrictions
| There are no additional restrictions for the registration. |
