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Code MAT 306
Term 201602
Title Computational Techniques for Materials Science
Faculty Faculty of Engineering and Natural Sciences
Subject Materials Sci.& Nano Eng.(MAT)
SU Credit 3
ECTS Credit 6.00 / 5.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Instructor(s) Canan At?lgan canan@sabanciuniv.edu,
Detailed Syllabus
Language of Instruction English
Level of Course Undergraduate
Type of Course Click here to view.
Prerequisites
(only for SU students)
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Mode of Delivery Formal lecture,Interactive lecture,Group tutorial,Laboratory
Planned Learning Activities Interactive,Learner centered,Communicative,Discussion based learning,Task based learning,Simulation
Content

Time and length scales in materials science. The nano-micro scale: ab-initio methods, Monte Carlo simulations, molecular dynamics and related techniques. The micro-meso scale: microstructural phenomena, defects, continuum representation. The meso-macro scale: finite element and finite difference methods, polycrystal models. Modeling and simulation at integrated time and length scales.

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 Outcome

Interpret the problem of time and length scales in molecular modeling by relating the type of the problem to the available modeling technique.
Sketch simple potential energy surfaces for systems of up to four particles and identify the global energy minimum and local energy minima on it.
Calculate the energy of conformations of simple molecules of up to six particles, given the parameters of a force field describing the molecule.
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 conformational searching on systems of up to 10 particles by applying systematic and random search methods.
Perform normal mode analysis on systems of up to 10 particles in one and two-dimensions and relate the output to vibrational spectroscopy experiments.
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
 
Common Outcomes For All Programs
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. 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
Common Outcomes ForFaculty of Eng. & Natural Sci.
1 Possess sufficient knowledge of mathematics, science 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; choose and apply suitable analysis 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; possess knowledge of standards used in engineering applications; use information technologies effectively. 5
4 Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 3
5 Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 5
6 Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 1
7 Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 2
Materials Science and Nano Engineering Program Outcomes Core Electives
1 Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 5
2 Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 4
3 Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 5
Molecular Biology, Genetics and Bioengineering Program Outcomes Core Electives
1 Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 4
2 Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 4
Mechatronics Engineering Program Outcomes Area Electives
1 Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 4
2 Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 3
Computer Science and Engineering Program Outcomes Area Electives
1 Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 3
2 Demonstrate knowledge of discrete mathematics and data structures. 4
3 Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 3
Electronics Engineering Program Outcomes Area Electives
1 Use mathematics (including derivative and integral calculations, probability and statistics), basic sciences, computer and programming, and electronics engineering knowledge to design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software. 3
2 Analyze and design communication networks and systems, signal processing algorithms or software using advanced knowledge on differential equations, linear algebra, complex variables and discrete mathematics. 2
Assessment Methods and Criteria
  Percentage (%)
Midterm 30
Exam 20
Assignment 50
Recommended or Required Reading
Readings

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

Course Web http://people.sabanciuniv.edu/canan/mat306.htm