Computational Modelling Techniques

CHEM40242 Computational Modelling Techniques 10 Semester 2 Undergraduate Level 6 Cristina Trujillo del Valle Unit coordinator Department of Chemistry 1 FHEQ level (Framework for Higher Education Qualifications) ' Last part of a Bachelors ' European Credit Transfer & Accumulation System Rating : 5.0 The unit will provide both theoretical and practical foundations of modern computational chemistry over 12 weeks. Students will learn about various computational methods and their applications across a broad range of chemical topics, from molecular orbital theory to machine learning for materials and molecular properties. The course will emphasise the integration of computational chemistry in understanding and predicting molecular phenomena. The unit will provide both theoretical and practical foundations of modern computational chemistry over 12 weeks. Students will learn about various computational methods and their applications across a broad range of chemical topics, from molecular orbital theory to machine learning for materials and molecular properties. The course will emphasise the integration of computational chemistry in understanding and predicting molecular phenomena. The course aims to introduce fundamental principles of scientific computational modelling in the chemical sciences. A range of modelling approaches, numerical algorithms, and the core concepts of computational chemistry will be covered. Students will also develop practical skills through the study of examples using advanced computational tools, including software such as ORCA, VASP, and machine learning frameworks. On successful completion of the course, students should be able to:<ul><li>Demonstrate proficiency in basic Linux commands and the ORCA software environment.</li><li>Apply various computational methods to chemical problems, including DFT, WFT, and solid-state theory. </li><li>Perform calculations on molecular structures and interpret computational data. </li><li>Explore material properties, reaction mechanisms, and spectroscopic behaviours using computational methods. </li><li>Integrate machine learning tools in the computational chemistry context.</li></ul> <ul><li>Ability to work with computational chemistry software, including ORCA, VASP, and machine learning frameworks.</li><li>Strong problem-solving skills applied to chemical data and molecular phenomena.</li><li>Competence in interpreting computational results in the context of real-world chemical systems.</li><li>Familiarity with solid-state physics, molecular modelling, and electronic structure theory.</li></ul> Basics<ul><li>Introduction to basic Linux commands.</li><li>Introduction to ORCA software: Preparing and submitting calculation input files, analysing output.</li></ul>Basis sets<ul><li>Introduction to atomic orbitals and basis sets.</li><li>Creating geometry optimisation input files with various basis sets.</li><li>Selection of appropriate basis sets for different applications.</li></ul>Density Functional Theory (DFT)<ul><li>Exploration of different DFT functionals and their implications.</li><li>Using functionals to calculate electron affinity (EA) and ionization potential (IP), and comparison with experimental data.</li></ul>Wavefunction Theory (WFT)<ul><li>Calculation of dissociation energies using HF, DFT, and CASSCF methods.</li><li>Comparison of calculated values with experimental bond dissociation energies.</li></ul>Transition Metals<ul><li>Exploring the effect of active space on electronic structure in transition metal complexes using CASSCF.</li></ul>Solvation<ul><li>Calculation of absorption spectra using TD-DFT in gas phase, implicit and explicit     solvation models.</li><li>Comparison of calculated spectra with experimental data.</li></ul>Conformational Analysis<ul><li>Identification of stable conformers of a relevant chemical system.</li></ul>Molecular Docking<ul><li>Use of AutoDock Vina to predict ligand-protein interactions.</li><li>Potential Energy Surfaces – Catalysis – Non-covalent Interactions</li><li>Analysis of catalysed versus uncatalysed reactions and the role of non-covalent interactions in catalysis.</li></ul>Solid-state I<ul><li>Basics of solid-state calculations using VASP.</li><li>Calculation of band structures and density of states for polyacetylene wire and graphene.</li></ul>Solid-state II<ul><li>Determination of dielectric functions and optical responses for conjugated organic polymers.</li></ul> 1 Written exam 100% <ul><li>Online support materials include workshop and self study exercises (formative assessments) that allow students to engage in problem solving activities.</li><li>General assistance and feedback from staff during weekly practical workshop sessions.</li><li>Personal feedback on lecture material and workshop examples throughout the course.</li></ul> N <ul><li>Best-Practice DFT Protocols for Basic Molecular Computational Chemistry Angew. Chem. Int. Ed. 2022, 61, e20220573</li><li>Quantum chemistry: Molecular structure and properties in Silico (RSC Theoretical and Computational Chemistry Series), J. J. W. McDouall, RSC Publishing, 2013.</li><li>Solids and Surfaces: A Chemist's View of Bonding in Extended Structures, Roald Hoffmann ISBN: 978-0-471-18710-3</li><li>Essentials of Computational Chemistry: Theories and Models, 2nd Edition, Christopher J. Cramer, ISBN: 978-0-470-09182-1</li></ul> Assessment written exam 2 Lectures 22 76