This 3-day workshop will broadly cover four following themes focusing on the challenges and opportunities in Crystal Structure Prediction (CSP):
- Recent advances in CSP methods
- Examples of CSP application for molecular crystals
- Examples of CSP application for inorganic crystals
- Where can Machine Learning help CSP
- How to use CSP to accelerate design of functional materials
- How to construct the search space to conduct high-throughput calculations
- How to parameterise fast chemical models such as forcefields and machine learning models using first-principles and experimental data
- How to usefully use the information from high-throughput calculations
- What can the materials science community and molecular crystals community learn from each other
