Important notice
The course guide is provisional.
The PDF version of the course guide may take a few days to become available in the DDD.
Soft Matter Simulation: Application to Bio-nanomaterials
Code: 45739Credits: 3
| Degree programme | Type | Course |
|---|---|---|
| Applied Nanoscience: From Materials to Devices | OP | 1 |
Contact lecturer
- Name :
- Jordi Faraudo Gener
- Email :
- jordi.faraudo@uab.cat
Teaching staff
- Jean-Didier Pierre Marechal
Group languages
You can consult this information at the end of the document.
Prerequisites
There are no prior academic requirements to enroll in it. As this is a computational-based course, an interest in programing and computing in general is desirable. Previous knowledge of Python or other programming languages is helpful, but not essential.
Objectives
The objective of this course is to provide computational simulation methods to study softmatter nanometric systems. The broad term softmatter include many materials organized (and self-organized) at the nanoscale in a state between solid and liquid, in which entropy, order and disorder play a substantial role. They include but are not limited to polymers, hydrogels, liquid crystals, vesicles, nanoparticles (organic and inorganic) and supramolecular materials to biological matter (from biomolecules such as nucleic acids, proteins, lipids and their aggregates up to viruses). The course will cover some of the basic theoretical concepts employed to describe these nanosystems (such as fluctuations and noise, self-assembly or docking and molecular recognition) from a practical, computational perspective.
Learning outcomes
- CA19 (Design the modelling of soft materials using appropriate simulation techniques.) Design the modelling of soft materials using appropriate simulation techniques.
- CA20 (Compare the results of the soft matter simulation with experimental data of the property under study when these exist.) Compare the results of the soft matter simulation with experimental data of the property under study when these exist.
- KA18 (Identify the most appropriate computational technique in the description of interaction processes between nanomaterials and biological entities.) Identify the most appropriate computational technique in the description of interaction processes between nanomaterials and biological entities.
- KA19 (Identify the equations that govern Newtonian molecular dynamics and structure dynamics.) Identify the equations that govern Newtonian molecular dynamics and structure dynamics.
- SA24 (Use free molecular dynamics software to study biological processes and their interaction with nanomaterials.) Use free molecular dynamics software to study biological processes and their interaction with nanomaterials.
- SA25 (Program growth and biological processes in Matlab or Python.) Program growth and biological processes in Matlab or Python.
- SA26 (Analyse the fundamental capabilities and constraints of soft matter simulation techniques based on the terms included in the model.) Analyse the fundamental capabilities and constraints of soft matter simulation techniques based on the terms included in the model.
Contents
The subject consists of two differentiated parts:
- Introduction to softmatter simulation: Introduction to basic simulation techniques (atomistic and coarse-grain Molecular dynamics and MonteCarlo). Introductory examples of selected softmatter systems (possible cases are polymers, nanoparticles in solution, self-assembly of nanoobjects, nanopores).
- Application to bionanosystems: In-depth application of the methods to biomolecular systems, with particular emphasis to proteins as a paradigmatic example.
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Practical sessions | 38 | 1.52 | CA19, CA20, KA18, KA19, SA24, SA26 |
| Inverted class preparation using support materials | 24 | 0.96 | CA19, CA20, KA18, KA19, SA24, SA26 |
| Final Project | 10 | 0.4 | CA19, CA20, KA18, KA19, SA24, SA26 |
The methodology will follow an active learning model, based on the partially flipped class methodology. In general, the sessions will proceed as practical sessions in which the protocol will be the following:
1. A few days before class, students receive introductory material to the theoretical and practical knowledge of the practice. (Introductory videos by teachers, study documents, internet links, etc.). It can include some basic exercises to solve.
2. On the scheduled day of each session, the teachers briefly recapitulate the fundamental concepts and the students develop practical cases under the supervision of the instructor.
3. At the end of the session, students will have to solve an online test in person and lasting between 10 and 20 minutes. It is not allowed to take the test from any other classroom or place other than the one assigned by the face-to-face class.
At the end of the module, a more advanced project, related to the contents of the course, will be solved by the students, including an oral presentation.
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Session test for each practical session (9 tests) | 45% | 3 | 0.12 | KA18, KA19, SA24, SA25, SA26 |
| Portfolio of classwork | 10% | 0 | 0 | CA19, CA20, KA18, KA19, SA25, SA26 |
| Final Project | 45% | 0 | 0 | CA19, CA20, KA18, KA19, SA24, SA25, SA26 |
A continuous evaluation will be carried out using the following instruments:
a) Compulsory session tests at the end of the practical sessions (around 9 tests will be scheduled, subject to change) lasting between 10 and 20 minutes. It is not allowed to take the test from any other classroom or place other than the one assigned by the face-to-face class.
b) A synthesis, final project that consists of a more advanced project based on the course contents that will be carried out by the student. The delivery from the project includes the original data (and all the necessary evidence to demonstrate authorship of the work), a report written by the student and an oral presentation.
We also require to maintain a portfolio of the simulations developed during the module, which will be evaluated.
The continuous evaluation activities have the objective of evaluating the daily follow-up of the subject and therefore they are not subject to retake.
NOTE: The use of AI tools is only allowed for those specific cases or specific tasks explicitly authorized by the instructor.
Bibliography
Computer Simulation of Soft Matter:
1.- Carbone, P. (2025). Computational Methods for the Multiscale Modeling of Soft Matter. (1st ed.). Elsevier Science & Technology. Available in the library and online for UAB students.
Computer Simulation methods:
1.- Frenkel, D., & Smit, B. (2023). Understanding Molecular Simulation: From Algorithms to Applications (Third edition). Elsevier Science & Technology. Available in the library and online for UAB students.
2.- Berendsen, H. J. C. (2007). Simulating the Physical World: Hierarchical Modeling from Quantum Mechanics to Fluid Dynamics (1st ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511815348 Available in the library and online for UAB students.
3.- Jensen, F. (2017). Introduction to Computational Chemistry (3e éd.). John Wiley & Sons. Available in the library and online for UAB students.
4.- Leach, A. R. (2001). Molecular modelling: Principles and applications (2nd ed.). Pearson Education. Available in the library.
Introductory texts on Soft Matter:
1.- Dutta, A. K. (2025). Soft Matter : Fundamentals and Applications (1st ed. 2025.). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-0624-5. Available in the library and online for UAB students.
2.- Piazza, R. (2011). Soft matter : the stuff that dreams are made of (1st ed. 2011.). Copernicus Books. https://doi.org/10.1007/978-94-007-0585-2. Available in the library and online for UAB students.
3.- Jones, R. A. L. (Richard A. L. (2007). Soft machines : nanotechnology and life (1st ed.). Oxford University Press. https://doi.org/10.1093/oso/9780198528555.001.0001 Available in the library and online for UAB students.
Software
- Python programming language including scientific libraries
- Google Collab
- VMD molecular visualization software
- OpenMM simulation package
- Autodock Vina
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE
| Type of teaching | Group | Language | Semester | Shift |
|---|---|---|---|---|
| (TEm) Theory (master) | 1 | English | first semester | afternoon |