Unit COMPUTATIONAL CHEMISTRY
- Course
- Chemical sciences
- Study-unit Code
- A001124
- Curriculum
- Theoretical chemistry and computational modelling
- Teacher
- Andrea Lombardi
- Teachers
-
- Andrea Lombardi
- Hours
- 42 ore - Andrea Lombardi
- CFU
- 6
- Course Regulation
- Coorte 2022
- Offered
- 2022/23
- Learning activities
- Caratterizzante
- Area
- Discipline chimiche inorganiche e chimico-fisiche
- Academic discipline
- CHIM/03
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- English
- Contents
- 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
Chemistry
-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. - Prerequisites
- 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 2022.
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