Abstract: A high-throughput method for preparing anticorrosion coatings, includes the steps of: treating surfaces of sample substrates to be coated by removing oxide layers, and placing the treated substrates on specimen fixture trays; determining solution data based on types and composition ranges of corrosion inhibitors planned for anticorrosion coating preparation; preparing solutions based on the solution data, adding the solutions to designated test tubes, and thoroughly mixing with primer coats to obtain coating solutions; dispensing the formulated coating solutions onto the surfaces of the sample substrates to be coated using a pipette, and applying coatings using a coating application robotic arm in a high-throughput anticorrosion coating preparation platform; transferring the applied sample substrates to an ultraviolet (UV) radiation station, and performing irradiation to achieve thermal curing; and transferring the entire specimen fixture tray to a designated position using a gantry robotic arm.

Abstract: A high-throughput method for preparing anticorrosion coatings, includes the steps of: treating surfaces of sample substrates to be coated by removing oxide layers, and placing the treated substrates on specimen fixture trays; determining solution data based on types and composition ranges of corrosion inhibitors planned for anticorrosion coating preparation; preparing solutions based on the solution data, adding the solutions to designated test tubes, and thoroughly mixing with primer coats to obtain coating solutions; dispensing the formulated coating solutions onto the surfaces of the sample substrates to be coated using a pipette, and applying coatings using a coating application robotic arm in a high-throughput anticorrosion coating preparation platform; transferring the applied sample substrates to an ultraviolet (UV) radiation station, and performing irradiation to achieve thermal curing; and transferring the entire specimen fixture tray to a designated position using a gantry robotic arm.

Abstract: A method and device for drug combination design by a high-throughput platform and machine learning for optimizing is provided, including: constructing an initial data set for machine learning using the high-throughput platform; inputting the initial data set into a plurality of machine learning models, and training the plurality of regression models; predicting unknown D-amino acid mixtures using the machine learning models and an efficient global optimization algorithm; and conducting experimental iterative feedback on a candidate mixture formula, and conducting high-throughput performance screening on drug combinations of D-amino acid mixtures and a plurality of antibiotics optimized by machine learning. The performance screened is the drug resistance of bacteria to antibiotics, and antibacterial efficiency and cytotoxicity of the drug combinations.