THEORY AND SIMULATION OF NANO AND BIOSYSTEMS

The course is classified among the optional courses (related or integrative training activities) of the Master's degree program in Sustainable Chemistry and Technology. It offers students an in-depth study of advanced elements of quantum mechanics (not covered in previous courses) and an introduction to the main numerical calculation techniques for describing molecular and nanostructured systems. Students will also be introduced to the fundamentals of Machine Learning techniques, with a focus on their application in the field of chemistry.

The aim of the course is to train students in the conscious use of modern and powerful simulation techniques for the electronic, vibrational, and spectroscopic properties of (bio)molecules and nanomaterials. A conscious use implies the ability to understand the approximations underlying simulation techniques, to assess the trade-off between accuracy and computational cost, and to evaluate the advantages and disadvantages of different methods concerning a given problem.

This course aims to provide an essential skill in the knowledge background of future chemists, as computational chemistry techniques have already become indispensable tools for interpreting and predicting experimental results in various fields of chemistry, both in academia and industry.

Regular attendance and active participation in the learning activities proposed in the course (lectures, computer-based exercises), along with individual study, will enable students to achieve the following outcomes:

1. Develop an in-depth understanding of nanoscopic systems at a quantum mechanical level, covering different approaches to electronic structure calculations, the treatment of vibrational motion, and response theory to external perturbations.

2. Gain familiarity with fundamental computational chemistry tools (such as those for visualizing structures, orbitals, and vibrations) and software for electronic structure calculations.

The course will make extensive use of mathematical methods; therefore, knowledge of differential and integral calculus, as well as linear algebra, is essential. Additionally, a basic understanding of electromagnetism, optics, and fundamental quantum mechanics is necessary for successful participation in this course.

A good mastery of basic computer skills is required to independently install software in Windows, Linux, or Mac environments, according to personal preferences. Familiarity with programming in MATLAB/Octave or Python is desirable but not mandatory.

1. Quantum Mechanics: complementary topics
- Molecular orbital theory and valence bond theory
- Vibrations in polyatomic molecules
- Time-independent perturbation theory and applications
- Time-dependent perturbation theory and the Fermi's Golden Rule

2. Methods for Electronic Structure Calculation
- Hartree-Fock method
- Density Functional Theory
- Configuration Interaction
- Other methods for excited states

3. Computer Exercises
- Conjugated polyenes: comparison between ab initio and Huckel method
- HCl molecule: geometry, vibrations, potential energy surface, dissociation
- Nucleophilic substitution reaction (SN2): mechanism, pathway, and potential energy barrier
- Simulations in condensed phases (e.g., solution): the polarizable continuum model

4. Introduction to Machine Learning Techniques in Chemistry

P. Atkins, R. S. Friedman, "Molecular Quantum Mechanics", Oxford University Press, 4th Edition, 2005
Attila Szabo, Neil S. Ostlund, "Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory", ‎ Dover Publications, 2012
Richard M. Martin, "Electronic Structure: Basic Theory and Practical Methods", Cambridge University Press, 2008

The exam will consist of an oral test, expected to last around 30 minutes.
The exam will start with a brief presentation prepared by the student (approximately 10 minutes, with slides) on a computational experience, which may be a short project that expands on an exercise done during the course or on a topic agreed upon with the teacher.
The presentation will be followed by a discussion of the student's presentation and the exercises conducted in class. The discussion aims to assess the student's mastery of the techniques used, the understanding of the course's main content, the ability to connect theory, simulations, and experiments, and the ability to communicate clearly and precisely.

oral

The grading scale following the oral exam reflects, as an indicative reference, the following evaluation scheme:

18-21: Basic knowledge of the subject, with essential presentation and possible conceptual gaps. Limited ability to apply the acquired content and establish connections between concepts.
22-24: Fair knowledge of the topics covered, with generally clear but not always in-depth exposition. Partial ability to apply the acquired content and establish connections between concepts.
25-27: Good mastery of the subject, with generally clear and accurate exposition. Ability to connect concepts and apply them to concrete cases with a certain degree of autonomy.
28-30: Excellent knowledge of the topics, with clear and accurate exposition. Ability for critical analysis and advanced application of knowledge.
30 cum laude: Outstanding mastery of the subject, with the ability for original and in-depth elaboration.

Lectures with the support of a blackboard and slides, and computer-based exercises.

Accessibility, Disability and Inclusion

Accommodation and support services for students with disabilities and students with specific learning impairments:
Ca’ Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding supportservices and accommodation available to students with disabilities. This includes students with mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). In the case of disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.