Abstract
The recent emergence of self-driving labs (SDL) and material acceleration platforms (MAPs) demonstrates the ability of these systems to change the way chemistry and material syntheses will be performed in the future. Especially in conjunction with nano and advanced materials which are generally recognized for their great potential in solving current material science challenges, such systems can make disrupting contributions. Here, we describe in detail MINERVA - an SDL specifically built and designed for the synthesis, purification, and in line characterization of nano and advanced materials. By fully automating these three process steps for seven different materials from five representative, completely different classes of nano and advanced materials (metal, metal oxide, silica, metal organic framework, and core-shell particles) that follow different reaction mechanisms, we demonstrate the great versatility and flexibility of the platform. We further study the reproducibility and particle size distributions of these seven representative materials in depth and show the excellent performance of the platform when synthesizing these material classes. Lastly, we discuss the design considerations as well as the hardware and software components that went into building the platform and make all components publicly available.
Supplementary materials
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Supplementary Information
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It contains additional figures, individual synthesis scripts of all material classes that were discussed in the manuscript and an exemplary log file.
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Supplementary weblinks
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Github Repository
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Repository with the Python code and modules discussed in the text, as well as more extensive feature descriptions, documentations, a video showcasing the MAP and some exemplary synthesis, purification, and characterization steps, and the Arduino code and stl files of the custom-built hardware. It also contains all the Python scripts that were executed for synthesizing the materials discussed in the publication and an exemplary detailed log file.
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