The Centre of Excellence in Coating and Surface Engineering (CE-CSE) at the University of Nottingham has developed a self-driving laboratory designed to automate the development of advanced materials for extreme environments. The system combines two robotic arms, a specially designed liquid-dispensing tool, laboratory equipment and purpose-built software to carry out the full experimental workflow, from measuring and mixing chemical ingredients to high-temperature furnace processing and sample retrieval. The laboratory is guided by an artificial intelligence approach known as active learning, which uses information from previous experiments to identify the most promising material compositions for the next round of investigation. Using this method, the researchers identified and prepared several candidate materials with a pyrochlore crystal structure for evaluation as potential thermal barrier coatings, which act as protective heat shields in aerospace engine components exposed to intense temperatures. Calibration experiments demonstrated accurate liquid dispensing across different fluids, and the system successfully prepared a precursor solution, transferred the material for furnace processing, managed controlled cooling and retrieved the processed sample without manual intervention. According to Professor Tanvir Hussain, the work addresses an important part of the broader challenge of reliable multi-stage automation and creates opportunities for further integration with intelligent experimental planning.