• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Learning outcomes

Upon successful completion of this course, students will be able to:

1. identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.

   Contribution to Program Outcomes

   1. Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.
   2. Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
   3. An ability to design and conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or discipline-specific research topics.
   4. Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.

   Method of assessment

   1. Written exam
   2. Homework assignment
2. select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.

   Contribution to Program Outcomes

   1. Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.
   2. Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
   3. An ability to design and conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or discipline-specific research topics.

   Method of assessment

   1. Written exam
   2. Homework assignment
3. gain adequate knowledge of mathematics, science and mechanical engineering disciplines; ability to use theoretical and applied knowledge in these fields in solving complex engineering problems

   Contribution to Program Outcomes

   1. Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.
   2. Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
   3. An ability to design and conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or discipline-specific research topics.
   4. Ability to work effectively in disciplinary and multi-disciplinary teams; individual working skills.

   Method of assessment

   1. Written exam
   2. Homework assignment

Contents
Week 1:	Molecular modeling, intermolecular forces
Week 2:	General overview of computer simulations Homework 1
Week 3:	Classical thermodynamics, thermal equilibrium
Week 4:	Probability distributions and thermodynamic averaging Homework 2
Week 5:	Statistical ensembles and fluctuations
Week 6:	Introduction Molecular dynamics, Various schemes for integration Homework 3
Week 7:	Inter and Intra molecular forces, Introduction to force fields
Week 8:	Week 8: Methods for partial atomic charges, Various ensembles (NVE, NVT, NPT, NPH) Homework 4
Week 9:	Various ensembles (NVE, NVT, NPT, NPH) Midterm Exam
Week 10:	Periodic boundary conditions and neighbor lists, implementation of thermostats and barostats Homework 5
Week 11:	Monte Carlo Simulations, Rigid Body Monte Carlo, Various sampling methods
Week 12:	Particle based MC simulations, Biased Monte Carlo. Free energy calculations
Week 13:	Umbrella sampling, Free energy perturbation
Week 14:	Some Applications of Molecular Simulations
Week 15*:	--
Week 16*:	Final Exam
Textbooks and materials:	1- Frenkel, D., & Smit, B. (2001). Understanding molecular simulation: from algorithms to applications, Elsevier. 2- Michael P Allen and Dominic J Tildesley. Computer simulation of liquids. Oxford university press, 2017;
Recommended readings:	1- Statistical Mechanics: Theory and Molecular Simulation (Oxford Graduate Texts) 1st Edition by Mark E. Tuckerman 2- McQuarrie, D. A. Statistical Mechanics, University Science Books, 2000 * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:	9	35
Other in-term studies:		0
Project:		0
Homework:	2,4,6,8,10	20
Quiz:		0
Final exam:	16	45
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	4	14
Own studies outside class:	3.5	14
Practice, Recitation:	0	0
Homework:	5	5
Term project:	0	0
Term project presentation:	0	0
Quiz:	0	0
Own study for mid-term exam:	8	1
Mid-term:	2	1
Personal studies for final exam:	8	1
Final exam:	3	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)