This robot at CNM can perform the 1) processing experiments by: (i) preparing desired solutions (e.g., temperature, solvents and concentrations) in vials through a pipetting head and a heating-stirring module; (ii) depositing solutions into thin films with programmable processing parameters (e.g., coating speed, temperature) on different substrates (e.g., glass, wafer, plastic) through a directional solution-coating module; (iii) post-treating thin films at controllable temperature for designed time via an annealing module. Furthermore, the robot platform can 2) characterize each sample right after processing by different purpose-built modulus, such as bright field and polarized photography via imaging module, (polarized) UV-Vis-NIR reflection and transmission spectroscopy via spectrometer module, electronic property characterization via Keithley electrical station module. This robot platform is controlled using flexible, open-source Python software, which facilitates the rapid implementation of experiments. As a custom workflow, this robot is ideal for testing machine learning algorithms such in continuous parameter spaces.
A ML-integrated modular robotic material processing/characterization platform, which consists of five closely integrated components: Modular lab Robotic, Data extraction tools, Database and cloud services, Training software, and Active learning library.