Driven by the global carbon neutrality goal, the research and development of silicone materials has ushered in a new wave of AI technology empowerment. Recently, a domestic technology company announced that its "AI-ORGANOSILICON" platform developed based on deep learning algorithms has successfully optimized the synthesis process of polysilazane (PSZ) coatings, improving the high temperature resistance of new energy vehicle battery packs by 40%, and is expected to extend the life of power batteries to more than 10 years.


As a new type of ceramic precursor material, polysilazane is widely used in the field of lithium battery separator coatings due to its excellent corrosion resistance and thermal stability. However, traditional research and development requires repeated testing of different ratios, and the cycle is as long as several months. Through the analysis of 300,000 sets of experimental data by the AI model, the researchers screened out the best synthesis path in just two weeks, reducing the coating thickness to less than 5 microns while maintaining ultra-high temperature protection at 1800℃. The technology has entered the test stage of the Ningde Times and BYD supply chain.


In addition, AI technology has also promoted the innovation of silicone resin in the field of consumer electronics. In the folding screen model that a mobile phone brand is about to release, the "super elastic silicone hinge coating" designed by AI simulation can withstand 500,000 folding tests, and its hardness is 25% higher than the previous generation. Industry analysts pointed out that in 2024, the innovation of silicone materials driven by AI will leverage a market size of at least 80 billion yuan, especially in the fields of new energy and flexible electronics.
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