Modelling and Data Tools for Materials Scientists

MATS31101 Modelling and Data Tools for Materials Scientists 10 Semester 1 Undergraduate Level 6 Thomas Flint Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Last part of a Bachelors ' European Credit Transfer & Accumulation System Rating : 5.0 This unit introduces key techniques for the manipulation and processing of data from experiments and simulations and a range of approaches to simulating the properties and behaviour of materials. It presents the theory underlying these techniques, explains when and how they can be used and provides an opportunity for hands-on experience in using them. The unit will be delivered via computer laboratory workshops using the software Python. This unit introduces key techniques for the manipulation and processing of data from experiments and simulations and a range of approaches to simulating the properties and behaviour of materials. It presents the theory underlying these techniques, explains when and how they can be used and provides an opportunity for hands-on experience in using them. The unit will be delivered via computer laboratory workshops using the software Python, which will cover:<ul> <li>Statistical analysis of experimental and simulation data, curve fitting and the science behind algorithms employed in data analysis.</li> <li>A selection of modelling methods available to simulate the behaviour of materials across a range of length scales from the molecular to the continuum level.</li> <li>The domain of applicability of each of the modelling techniques, along with some illustrative examples (both at an elementary level to aid understanding and from the current literature to demonstrate utility).</li> <li>A more detailed exposition of the theoretical basis of some key materials modelling techniques, for example: molecular dynamics, the phase-field method and the finite element method.</li></ul> This unit aims to:<ol> <li> Introduce a range of data processing and analysis tools relevant to materials scientists and develop an understanding of how they work and a practical ability to use them through hands-on exercises</li> <li> Explain the concept of materials simulation, the different techniques available, the theory underlying those techniques and the types of problems they can be used to solve</li> <li> Provide hands-on experience of using modelling techniques to explore the behaviour of materials    </li></ol>  A greater depth of the learning outcomes will be covered in the following sections: <ul> <li> Knowledge and understanding</li> <li> Intellectual skills</li> <li> Practical skills</li> <li> Transferable skills and personal qualities</li> </ul> Upon completing this unit, you should be able to:a)      Fit datasets with appropriate mathematical functions and quantitatively assess the quality of the fits.b)      Characterise data using statistics and construct robust statements to communicate statistical findingsc)      Use simulation techniques to predict the response of materials under given physical conditionsd)      Draw clear conclusions from the outcome of simulations, appropriate to the degree of approximation inherent in the model and the simulation design Upon completing this unit, you should be able to:a)     Translate real-world, physical problems into a form that can be solved with a computer This unit will be primarily delivered via enquiry-based learning in a computer laboratory. Hands-on learning will be reinforced by assessed computational course work. Supplementary lectures will be given to explain important theoretical concepts prior to the computer workshops. Recommended textbooks, web resources and electronic supporting information (on Blackboard) will also be provided.  2 Written assignment (inc essay) 100% Written and verbal N There is no compulsory reading material for the course. You may find the following textbook useful:Scopatz and Huff, 2015. Effective Computation in Physics. O’Reilly Media.  Lectures 20 0 80