AI Magnet: Machine Learning in R&D of Permanent Magnet

Artificial intelligence (AI) is a branch of computer science which aim to understand the essence of intelligence and produce a new intelligent machine. The hot research area of AI contains robot, language recognition, image recognition, natural language processing and expert system. Perhaps AI magnet is not only limited to the magnetic component in AI product, but also can be defined as magnets with AI algorithm participated during its R&D stage.

Material can be regarded as the fundamental substance of human life and development. New material technology is also becoming one of the major indicators of world new technology revolution. Material research was purely depending on intuition observation experience thousands of years ago, then formed physical model which marked by law of mathematics equation until several centuries earlier, especially law of thermodynamics. But for many scientific problems, the solution of complex model will take huge manual effort and time. The invention of computer and the development of computing technology has opened the way to simulate the complex models, then density functional theory and molecular dynamics have been applied rapidly just in this era. Generally, material science has gone through three stages included experience, theoretical model and simulation, however, material research is gradually entering the stage which data drives scientific discovery. Especially as the continuous application of high throughput experiment, characterization and calculation, discover knowledge from abundant data will be the main way of the future material research and this data-driren technology has defined as the 4th paradigm of the research of material science.

Research objective of material science is cracking the relationship between processing, structure, properties and performance of material. One important function of data-driven technology is material performance prediction. Material performance prediction model can not only confirm the performance of unknown material without experiments and theoretical calculations, but also able to guide material’s development and design which more important and challenging. For data-driven technology, material design is essentially an optimization problem that search the composition, structure and processing corresponding to the maximum material performance. Material performance is influenced by many factors including chemical composition, physical property, microstructure and processing technique. It should be noted that material performance is not linear with the above factors. Arguably, data-driven technology has significantly economic benefits compared with traditional R&D model.

Machine learning is a computer science of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, but relying on patterns and inference instead. As a core branch and research topic of AI, machine learning has been already served to the R&D of the permanent magnet by Chinese researchers, and that’s why we call it AI magnet.