Automated Hyperspectral Characterisation Station for Laboratories

This thesis addresses the gaps between the capabilities and utilisation of robotics and automation in laboratory settings. We introduce an innovative approach to the time- and temperature-dependent characterisation of materials. The challenges posed by manual methods using established laboratory equipment are discussed, and the automated hyperspectral characterisation station is presented as a flexible, higher-throughput, and automated solution. This station integrates robot-aided hyperspectral imaging, complex material characterisation modelling, and automated data analysis, offering a non-destructive automated approach to characterising materials in chemistry and material science laboratories. This work explains the roles of different hardware and software modules that constitute the system, followed by its applications to solve real-world problems. The proposed assembly is shown to be capable of automatically measuring the half-life of biodegradable polymers with throughput and precision higher than those of manual methods. The investigation explores the effects of pH, average molecular weight (Mn), end groups, and blends on the degradation rate of polylactic acid (PLA). Additionally, the developed station is utilised to measure the critical temperature corresponding to phase changes (dissolution and precipitation) of polymers within solvents. The novel contributions of this body of research lie in introducing an adaptable classification station for characterisation and presenting innovative methodologies for measuring polymer degradation rates and polymer-solvent dissolution and precipitation temperatures. The applications of the proposed system are not limited to the cases explored in this work and hold promise for expediting the development of high-throughput screening and characterisation methods within advanced material and chemistry laboratories.