2024
Advanced Methods in Computational Chemistry
Name: Advanced Methods in Computational Chemistry
Code: QUI13583D
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Chemistry
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Sustainable Development Goals
Learning Goals
The main goal of this curricular unit is to provide the students with an overview of molecular simulation techniques, molecular electronic structure calculation methods and intelligent systems in chemistry. The students should obtain a solid knowledge of the underlying concepts and theoretical foundations of simulation techniques, quantum calculations and intelligent systems. They should become familiar with the most important methods of each type of calculation.
Contents
Quantum Chemistry: Hückel, semi-empirical and ab initio methods. Density functional theory.
Quantum dynamics: Time evolution of a quantum system. Time dependent Density functional theory. Electronic transitions.
Molecular simulation: Molecular dynamics. Simulations in the micro-canonical, canonical (Nosé-Hoover and Berendsen thermostats) and isobaric (Berendsen and Parrinello-Rahman barostats) ensembles. Geometry constraints. Metropolis Monte Carlo. Canonical, isothermic-isobaric, grand canonical and Gibbs ensembles. Non-Boltzmannean sampling. Thermodynamic perturbation theory. Thermodynamic integration method. Free energies calculations.
Intelligent Systems: Knowledge and Knowledge Representation; Reasoning; Degree of Confidence and Quality of Information. Methods and Techniques. Applications to the area of chemistry. In silico experimentation.
Quantum dynamics: Time evolution of a quantum system. Time dependent Density functional theory. Electronic transitions.
Molecular simulation: Molecular dynamics. Simulations in the micro-canonical, canonical (Nosé-Hoover and Berendsen thermostats) and isobaric (Berendsen and Parrinello-Rahman barostats) ensembles. Geometry constraints. Metropolis Monte Carlo. Canonical, isothermic-isobaric, grand canonical and Gibbs ensembles. Non-Boltzmannean sampling. Thermodynamic perturbation theory. Thermodynamic integration method. Free energies calculations.
Intelligent Systems: Knowledge and Knowledge Representation; Reasoning; Degree of Confidence and Quality of Information. Methods and Techniques. Applications to the area of chemistry. In silico experimentation.
Teaching Methods
The teaching / learning is based in the individual work of students, supported by recommended bibliography and notes taken by the students either during classes or through individual research. In the lectures the theory will be exposed, commented and discussed with the students. In practical classes, the subjects developed in the lectures are illustrated with problems of practical examples, resorting frequently to the writing and execution of computer programs or the use of software commonly used in Computational Chemistry to solve the proposed exercises.
The evaluation is carried out by the realization of 3 tests or one final exam and the execution and presentation of a computer lab work. The final score will be calculated from the average of the 3 frequencies or the test score, with a weight of 70%, and the grade of the computational essay, with a weight of 30%.
The evaluation is carried out by the realization of 3 tests or one final exam and the execution and presentation of a computer lab work. The final score will be calculated from the average of the 3 frequencies or the test score, with a weight of 70%, and the grade of the computational essay, with a weight of 30%.
Certificações
