Artificial Intelligence used to create new aluminum alloys – IAM Network

Scientists in Japan have developed a machine learning approach that predicts the elements and manufacturing processes needed to obtain an aluminum alloy with specific, desired mechanical properties. The approach, published in the journal Science and Technology of Advanced Materials, could facilitate the discovery of new materials.Aluminum alloys contain elements such as magnesium, manganese, silicon, zinc, and copper. The combination of these elements and the manufacturing process determines how resilient the alloys are to various stresses. For example, 5000 series aluminum alloys contain magnesium and several other elements and are used as a welding material in buildings, cars, and pressurized vessels. The 7000 series aluminum alloys, which contain zinc and usually magnesium and copper, are most commonly used in bicycle frames.Experimenting with various combinations of elements and manufacturing processes to fabricate aluminum alloys is time-consuming and expensive.