Automatic functional material biochemical synthesis workstation based on artificial intelligence

Abstract

The invention relates to an automatic functional material biochemical synthesis workstation based on artificial intelligence. The workstation comprises a desktop robot hardware platform and an intelligent control analysis center which is in communication connection with the desktop robot hardware platform and includes a database and software. The desktop robot hardware platform is provided with araw material area, a reaction area, a test area, an evaluation area and a video monitoring area. The intelligent control analysis center can drive a three-axis mechanical arm to drive a pipette to prepare raw materials in a raw material area and can also inject the raw materials into a porous reaction plate and a porous microwell plate to be supplied to a visual module below a reaction area. A test detector in the test area and an evaluation detector in an evaluation area acquire data, the intelligent control analysis center performs calculation, analysis and machine learning, calculation andoutput are performed according to a preset model, and a high-throughput test, testing and iterative optimization of functional materials are realized. A closed loop of ''design-test-representation-learning-redesign'' is quickly completed in a low-cost and multi-cycle manner, and preparation and digital manufacturing of a novel functional material are realized.

Description

technical field [0001] The invention relates to the technical field of research and development of high-throughput functional materials, in particular to a biochemical synthesis test workstation based on digital manufacturing combined with artificial intelligence and robots and automatic screening, preparation, characterization and testing of new functional materials. Background technique [0002] The traditional research and development process of functional materials is costly and time-consuming, and has high requirements for the efficiency and repeatability of experiments. The inefficiency and waste of experiments will be a great consumption of research costs and talents. If only relying on manual operation is not only time-consuming, but also prone to errors, which will greatly affect the repeatability of experimental results. On the other hand, traditional methods have obvious deficiencies in predicting the relationship between material properties, components, and proce...

AI Technical Summary

Problems solved by technology

[0002] The traditional research and development process of functional materials is costly and time-consuming, and has high requirements for the efficiency and repeatability of experiments. The inefficiency and waste of experiments will be a great consumption of research costs and talents

If you only rely on manual operation, it is not only time-consuming, but also prone to errors, which will greatly affect the repeatability of experimental results

On the other hand, traditional methods have obvious deficiencies in predicting the relationship between material properties and composition, processing conditions, etc.

In addition, some toxic solid reagents have great risks in the process of extraction and weighing, which may not only cause harm to experimenters, but also cause uncontrollable pollution to the environment

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