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MAT 306
Computational Techniques for Materials at the Nano-scale

Faculty Faculty of Engineering and Natural Sciences
Semester Spring 2025-2026
Course MAT 306 - Computational Techniques for Materials at the Nano-scale
Time/Place
Time
Week Day
Place
Date
08:40-10:30
Tue
FASS-1076
Feb 16-May 22, 2026
08:40-09:30
Thu
FENS-G059
Feb 16-May 22, 2026
Level of course Undergraduate
Course Credits SU Credit:3, ECTS:6, Basic:2, Engineering:4
Prerequisites -
Corequisites
Course Type Lecture

Instructor(s) Information

Canan Atılgan

Course Information

Catalog Course Description
Modeling techniques operative at the atomistic and mesoscopic time and length scales. All-atom methods; force fields. Conformational searching. Statistical mechanics concepts relevant for molecular simulations. Normal mode analysis in one- and two- dimensions and its relation to spectroscopy. Setting-up molecular dynamics simulations and basic analyses of the trajectories. Introduction to particle-based mesoscopic simulations. Self-organization at the molecular scale.
Course Learning Outcomes:
1. Interpret the problem of time and length scales in molecular modeling by relating the type of the problem to the available modeling technique.
2. Sketch simplified potential energy surfaces of molecular systems, identify their functionally relevant conformations and calculate the energies, given the parameters of a force field describing the molecules.
3. Apply simple statistical models from machine learning to identify conformational states of molecules.
4. Apply probability and statistics concepts to derive the Boltzmann and Maxwell distributions.
5. Relate the influence of conformations of a molecule on its properties by calculating the average properties of a given system based-on the Boltzmann distribution.
6. Perform normal mode analysis on nanoparticles and relate the output to vibrational spectroscopy experiments and the function of the nanomaterial.
7. Set-up and run molecular dynamics simulations on complex systems such as polymers and proteins.
8. Make physics-based descriptions of the main ingredients of a simulation such as the Verlet algorithm, periodic boundary conditions, selection of time step.
9. Calculate thermodynamic (e.g. temperature, pressure, heat capacity), and kinetic properties (diffusion constant, various relaxation times) from simulated trajectories.
Course Objective
To introduce various modeling techniques operative at the atomistic and mesoscopic time and length scales relevant to the understanding of the structure-property relationships of “materials” where a material is defined in the broad sense of anything that is utilized for a particular human defined purpose; to introduce a conceptual framework for the understanding of macroscopic observations of materials from a microscopic viewpoint; to include modeling and simulation on equal footing with experiments in attacking problems; to provide the background for choosing the appropriate technique suited to the system at hand.
Sustainable Development Goals (SDGs) Related to This Course:
Affordable and Clean Energy

Course Materials

Resources:
Supplementary Textbooks: Leach, Molecular Modelling 2nd ed. Prentice Hall (2001). ISBN: 0-582-38210-6

Hinchliffe, Molecular Modeling for Beginners 2nded. Wiley (2008). ISBN: 978-0-470-51314-9

Frenkel & Smit, Understanding Molecular Simulation 2nd ed. Academic Press (2002). ISBN: 0-12-267351-4
Technology Requirements:
laptops to be brought to all classes

Policies