Computational Techniques for Materials at the Nano-scale (MAT 306)

2024 Spring
Faculty of Engineering and Natural Sciences
Materials Sci.& Nano Eng.(MAT)
3
6
Canan Atılgan canan@sabanciuniv.edu,
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English
Undergraduate
--
Formal lecture,Interactive lecture,Group tutorial,Laboratory
Interactive,Learner centered,Communicative,Discussion based learning,Task based learning,Simulation
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Programs\Type Required Core Elective Area Elective
Computer Science and Engineering *
Computer Science and Engineering *
Electronics Engineering *
Electronics Engineering *
Materials Science and Nano Engineering *
Materials Science and Nano Engineering (Previous Name: Materials Science and Engineering) *
Mechatronics Engineering *
Mechatronics Engineering *
Microelectronics *
Molecular Biology, Genetics and Bioengineering *
Molecular Biology, Genetics and Bioengineering (Pre. Name: Biological Sciences and Bioengineering) *
Telecommunications *

CONTENT

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.

OBJECTIVE

To introduce various modeling techniques operative at a broad range of 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.

LEARNING OUTCOMES

  • Interpret the problem of time and length scales in molecular modeling by relating the type of the problem to the available modeling technique.
  • 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.
  • Apply simple statistical models from machine learning to identify conformational states of molecules.
  • Apply probability and statistics concepts to derive the Boltzmann and Maxwell distributions.
  • 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.
  • Perform normal mode analysis on nanoparticles and relate the output to vibrational spectroscopy experiments and the function of the nanomaterial.
  • Set-up and run molecular dynamics simulations on complex systems such as polymers and proteins.
  • Make physics-based descriptions of the main ingredients of a simulation such as the Verlet algorithm, periodic boundary conditions, selection of time step.
  • Calculate thermodynamic (e.g. temperature, pressure, heat capacity), and kinetic properties (diffusion constant, various relaxation times) from simulated trajectories.

PROGRAMME OUTCOMES

1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 1

2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 3

3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects; have the ability to continue to educate him/herself. 4

4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 4

5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 4

1. Possess sufficient knowledge of mathematics, science, fundamental engineering, computational methods and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 5

2. Identify, define, formulate and solve complex engineering problems while considering the UN Sustainable Development Goals; choose and apply suitable analysis, design, estimation/prediction and modeling methods for this purpose. 5

3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; use information technologies effectively. 5

4. Have the ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling creative current and future requirements. 3

5. Use research methods, including conducting literature reviews, designing experiments, performing experiments, collecting data, analyzing results, and interpreting results, to investigate complex engineering problems or discipline-specific research topics. 5

6. Possess knowledge of business practices such as project management, risk management, change management, and economic feasibility analysis; awareness on entrepreneurship and innovation. 1

7. Possess knowledge of impact of engineering solutions on society, health and safety, the economy, sustainability, and the environment within the framework of the UN Sustainable Development Goals; awareness on legal outcomes of engineering solutions; awareness of acting impartially and inclusively without any form of discrimination; act in accordance with ethical principles, possessing knowledge of professional and ethical responsibilities. 2

8. Communicate effectively, both orally and in writing, on technical subjects, considering the diverse characteristics of the target audience (such as education, language, and profession). 3

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Quiz 40
Assignment 50
Participation 10

RECOMENDED or REQUIRED READINGS

Textbook

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