TYC Materials Modelling Course - THOMAS YOUNG CENTRE

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All sessions are on Wednesdays 1-3pm in UCL Physics E7 (Ground floor) unless otherwise stated.

Course Content

High throughput computation and structure prediction – Chris Pickard, University of Cambridge

LT A1/3, Top floor, UCL Physics

Week 22 – Wednesday 24 March 2027

Accurate ab initio simulations of condensed phases and surfaces – Angelos Michaelides, University of Cambridge

LT A1/3, Top floor, UCL Physics

Week 21 – Wednesday 17 March 2027

Quantum Monte Carlo – Yasmine Al-Hamdani, UCL & Naples

LT A1/3, Top floor, UCL Physics

Week 20 – Wednesday 10 March 2027

Electronic excitations, GW, Bethe-Salpeter equation, GF – Johannes Lischner, Imperial College London

LT A1/3, Top floor, UCL Physics

Weeks 18 & 19 – Wednesday 24 February & 3 March 2027

An introduction to the GW method

Introduction to GW, the concept of a Green’s Function and Feynman diagrams

Introduction to vibrations of molecules and crystals – Lev Kantorovich, King’s College London

LT A1/3, Top floor, UCL Physics

Weeks 16 & 17 – Wednesday 10 & 17 February 2027

Introduction to vibrations of molecules and crystals_1
Introduction to vibrations of molecules and crystals_2
Introduction to vibrations of molecules and crystals_3

Quantum statistical mechanics and applications – Venkat Kapil, UCL

Will introduce the path-integral formulation of quantum statistical mechanics and how it can be implemented using molecular dynamics to estimate equilibrium properties; will discuss how to model quantum dynamics and discuss case studies where inclusion of quantum statistical mechanics is needed to describe material properties.

LT A1/3, Top floor, UCL Physics

Week 15 – Wednesday 3 February 2027

Fitting forcefields using Machine Learning and other techniques – Venkat Kapil, UCL

Will consider different ways to represent the potential energy landscape as a sum of local contributions of atomic potential energies, and compare state-of-the-art machine-learning architectures and will address the challenge of dataset generation, model validation and look at some applications.

LT A1/3, Top floor, UCL Physics

Week 14 – Wednesday 27 January 2027

Using graph neural networks – Keith Butler, UCL

LT A1/3, Top floor, UCL Physics

Week 13 – Wednesday 20 January 2027

Lecture slides

Data-driven modelling and artificial intelligence – Aron Walsh, Imperial College London

LT A1/3, Top floor, UCL Physics

Will introduce the different ways in which materials data and statistical models can be used to explore structure-property relationships and support materials design.

Week 12 – Wednesday 13 January 2027

AI for Materials lecture slides

Umbrella Sampling, Markov State Models (with tutorial), Adaptive biasing, Metadynamics – Edina Rosta and Matteo Salvalaglio, UCL

LT A1/3, Top floor, UCL Physics

Weeks 9, 10 & 11 – Wednesday 25 November, 2 & 9 December 2026

Umbrella Sampling lecture notes
Free Energy lecture notes
Statistically-Optimal Markov Chain Models in Biomolecular Simulations
Enhanced Sampling

Molecular Dynamics: MD, ab initio MD, time stepping algorithms, classical MD, BO MD, thermostats – Jochen Blumberger, UCL

LT A1/3, Top floor, UCL Physics

Weeks 7 & 8, Wednesday 11 & 18 November 2026

Born-Oppenheimer Approximation
Classical Approximation of Nuclear Motion
Molecular Dynamics and Time Stepping Algorithms
Born Oppenheimer Approximation Lecture Slides
Classical Approximation of Nuclear Motion Lecture Slides
Molecular Dynamics Simulation
Born Oppenheimer Molecular Dynamics
Time averages ensembles thermostat
Born Oppenheimer Molecular Dynamics lecture slides
Time averages ensembles thermostat lecture slides

Solid state and molecular quantum chemistry and beyond:

Limitations of DFT/mean-field methods, electron correlation, LDA+U, post-mean-field methods, embedding methods
Hartree-Fock, Hybrid DFT, Local basis sets, Limitations and strengths of different basis representations