Chemical sciences
Study-unit Code
Theoretical chemistry and computational modelling
Andrea Lombardi
  • Andrea Lombardi
  • 42 ore - Andrea Lombardi
Course Regulation
Coorte 2023
Learning activities
Discipline chimiche inorganiche e chimico-fisiche
Academic discipline
Type of study-unit
Obbligatorio (Required)
Type of learning activities
Attività formativa monodisciplinare
Language of instruction
Introduction to the use of computer tools in modern chemistry.
Computable quantities, computability, Touring Machines.
Brief introduction and references to operating systems, editors and programming languages.

- Classification of existing methodologies, in terms of quantum, semiclassical, classical and statistical methods;
Main issues of interest in computational chemistry
- calculation of electronic structure;
- optimization of molecular structures, search for minima on potential energy surfaces
-classification of stationary points, connectivity graphs. Construction of potential energy surfaces
- intermolecular interactions
- classical and quantum molecular dynamics, mixed methods (QM / MM). Machine learning methods applied to computational chemistry, neural networks.

In order to facilitate learning, the main contents of the course are interspersed with periodic references to basic aspects of classical and quantum mechanics and statistics.

The course will be enriched by examples of applications of the techniques and methods studied.

Classroom exercises are planned, carried out through access to virtual clusters.

Teacher seminars and researchers active in the field of computational chemistry will further enrich the course.
Reference texts
Lecture notes and references by the teacher.
Optional textbooks:
-Errol G. Lewars, Computational
-Frank Jensen, Introduction to Computational Chemistry
Educational objectives
Objectives of the course are:
- the theoretical bases of computational chemistry
- a general knowledge of the applications: feasibility, limitations and advantages.
- the development of a practical approach to the application of computational methods to molecular and biomolecular modeling.
Basic knowledge of programming. Basic knowledge of linear algebra and mathematical analysis and group theory. Basic knowledge of classical and quantum mechanics.
Teaching methods
Lectures covering all the arguments of the course. Practical sessions will be carried out on the main arguments of the course, using laptop computers
Other information
Period: March-May 2024.
Where: Library room, third floor of the Dipartimento di Chimica Biologia e Biotecnologie, Via Elce di Sotto 8
Learning verification modality
Oral presentations on topics related to the course

For information on support services for students with disabilities and / or DSA visit the page http://www.unipg.it/disabilita-e-dsa
Extended program
1) Introduction to scientific computing and computational chemistry

1.1 Definition of computational chemistry and its role in contemporary science

1.2 Computing platforms: operating systems (LINUX), "shell" and text editors.

1.3 Survey of programming languages.

1.4 Parallel computing and distributed and cloud computing.

2) Review of classical and quantum mechanics.

2.1 Quantum methods in molecular problems

2.2 Semiclassical and classical methods in molecular dynamics

3) Potential energy surfaces

3.1 Quantum methods for elementary systems

3.2 Intermolecular interactions

3.3 Molecular mechanics and "Force Fields" for complex systems

4) Machine learning 4.1 Machine learning applied to computational chemistry 4.2 Perceptrons and neural networks 5) Molecular dynamics simulations

4.1 Classical molecular dynamics

4.2 QM / MM methods

6) Exploration of potential energy surfaces

search of minima and saddle points
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