The course is intended to provide an introduction to the computational techniques used in molecular modeling and simulations, and to illustrate how these techniques can be used to describe and/or predict the behavior of physical, chemical and biological phenomena.

D1 - Knowledge and understanding skills
At the end of the course the student should know the basic principles of molecular simulations in materials and process engineering.
D2 - Ability to apply knowledge and understanding
The student shoul be able to apply a choice among the different molecular simulation techniques to solve problems in materials and process engineering.
D3 - Autonomy of judgment
The student should be able to critically and analytically apprise the results obtained from molecular simulations.
D4 - Communicative skills
The student should acquire a technical language and to be able to describe the computational experiments.
D5 - Learning skills
The student should be able to design a molecular simulation experiment in materials and process engineering.

General chemistry, organic chemistry, thermodynamics, basic physics and mathematics.

1. Introduction to molecular simulation.
a. Coordinate systems.
b. Potential energy surfaces.
c. Molecular models and graphics.
d. Molecular surfaces.
e. Computer hardware and software.
f. Length and energy scales and units.
g. Computational chemistry literature.
h. Basic math concepts.
i. Examples and hands on.

2. Molecular mechanics: empirical and ab initio force fields.
a. General concepts of force field in molecular mechanics.
b. Bond terms.
c. Non-bonded terms.
i. Electrostatic interactions.
ii. van der Waals interactions.
e. General and specific force fields.
f. Energy function derivatives ion molecular mechanics.
g. Examples and hands on.

3. Molecular energy minimization and analytical methods for molecular energy surfaces exploration.
a. Introduction to minimization methods.
b. First order minimization methods.
c. The Newton-Raphson method.
d. Criteria for choosing a minimization method.
e. Examples and hands on.

4. Computer-based atomistic molecular dynamics simulation methods.
a. Practical aspects of atomistic molecular dynamics.
b. Estimation of thermodynamic and structural quantities.
c. Phase-space.
d. Boundary conditions.
e. Statistical ensembles for molecular simulations.
f. Monitoring equilibrium in molecular simulations.
g. Potential energy truncation methods.
h. Methods for handling long range forces.
i. Analysis of simulations results and error estimation.
j. Examples and hands on.

5. Mesoscopic molecular simulations.
a. Practical aspects of mesoscopic simulations.
b. Description of conformational spaces and density distributions.
c. Phase-space.
d. Boundary conditions.
e. Methods and theories of molecular mesoscale simulations.
f. Coarse-graining methods.
g. Dissipative Particle Dynamics (DPD) theory.
h. Methods for estimating DPD parameters.
i. Analysis of DPD simulation results and error estimation.
j. Examples and hands on.

Molecular Modelling for Beginners (Alan Hinchliffe, Wiley)

Molecular Modeling: Principles and Applications (Andrew R. Leach; Prentice Hall)

1. Introduction to molecular simulation.
a. Coordinate systems.
b. Potential energy surfaces.
c. Molecular models and graphics.
d. Molecular surfaces.
e. Computer hardware and software.
f. Length and energy scales and units.
g. Computational chemistry literature.
h. Basic math concepts.
i. Examples and hands on.

2. Molecular mechanics: empirical and ab initio force fields.
a. General concepts of force field in molecular mechanics.
b. Bond terms.
c. Non-bonded terms.
i. Electrostatic interactions.
ii. van der Waals interactions.
e. General and specific force fields.
f. Energy function derivatives ion molecular mechanics.
g. Examples and hands on.

3. Molecular energy minimization and analytical methods for molecular energy surfaces exploration.
a. Introduction to minimization methods.
b. First order minimization methods.
c. The Newton-Raphson method.
d. Criteria for choosing a minimization method.
e. Examples and hands on.

4. Computer-based atomistic molecular dynamics simulation methods.
a. Practical aspects of atomistic molecular dynamics.
b. Estimation of thermodynamic and structural quantities.
c. Phase-space.
d. Boundary conditions.
e. Statistical ensembles for molecular simulations.
f. Monitoring equilibrium in molecular simulations.
g. Potential energy truncation methods.
h. Methods for handling long range forces.
i. Analysis of simulations results and error estimation.
j. Examples and hands on.

5. Mesoscopic molecular simulations.
a. Practical aspects of mesoscopic simulations.
b. Description of conformational spaces and density distributions.
c. Phase-space.
d. Boundary conditions.
e. Methods and theories of molecular mesoscale simulations.
f. Coarse-graining methods.
g. Dissipative Particle Dynamics (DPD) theory.
h. Methods for estimating DPD parameters.
i. Analysis of DPD simulation results and error estimation.
j. Examples and hands on.

Class lessons based on power point slides distributed in class; laboratory hands on with dedicated hardware and software.

The textbook chapters required for examination are mode freely available to the students.

Technical report with oral question concerning the computational tests performed.
The student must be able to accurately describe the activities carried out in the laboratory following the following scheme:
• Introduction: Description, using appropriate technical language, of the specific computational technique used.
• Procedure: Description, using precise technical language, of the complete computational process. The ultimate goal is to describe a reproducible procedure by following the points outlined in the report.
• Data Interpretation: The raw data must be appropriately processed and commented upon based on the theory described during the lectures.

Evaluation criteria: The assessment aims to ascertain the knowledge of the topics listed in the curriculum and the ability to apply this knowledge. The grades are expressed according to the following criteria:
Excellent (30-30 cum laude): Excellent knowledge of the subjects, outstanding vocabulary skills, and excellent analytical abilities. The student can brilliantly apply theoretical knowledge to real-life cases.
Very Good (27-29): Good knowledge of the subjects, remarkable vocabulary skills, and good analytical abilities. The student can correctly apply theoretical knowledge to practical cases.
Good (24-26): Good knowledge of the main subjects, decent vocabulary skills. The student demonstrates an adequate ability to apply theoretical knowledge to real-life cases.
Satisfactory (21-23): The student does not show full mastery of the main teaching topics but possesses fundamental knowledge. Still, they demonstrate satisfactory vocabulary skills and sufficient ability to apply theoretical knowledge to real-life cases.
Sufficient (18-20): Minimal knowledge of the main teaching topics and technical vocabulary, limited ability to adequately apply theoretical knowledge to real-life cases.
Insufficient (<18): The student does not possess an acceptable knowledge of the contents of the different topics in the curriculum.

4. Quality education.