Development of a versatile, accurate AI prediction technique even with a small number of experiments

Researchers have used the chemical materials open platform framework to develop an AI technique capable of increasing the accuracy of machine learning-based predictions of material properties (e.g., strength, brittleness) through efficient use of material structural data obtained from only a small number of experiments. This technique may expedite the development of various materials, including polymers.


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Source: ScienceDaily