Researchers in Russia have created a neural network that can analyze a set of fundamental data and select the strongest amorphous metal alloys. The scientists’ work was published in the journal Metals.
Amorphous alloys are used in mechanical engineering and other industries. Their use is mainly due to their strength properties such as fracture resistance, elasticity, hardness.
Developed by scientists, it analyzes data on the elements of the periodic table – the mass, charge and electronegativity of an atom. Next, it “collects” the alloy and adjusts the ratio of each element in it. Finally, the mechanical properties are determined. The total calculation time is about a few minutes.
One of the researchers, an engineer of the Department of Computational Physics at the Kazan Federal University Maria Doronina, said that data on more than 50,000 amorphous alloys of various compositions were used to train the neural network. Artificial intelligence does not require knowledge of the coordinates and velocities of atoms, which ensures that experts do not go through the laborious process of analyzing the structure of the alloy. Doronina emphasizes that the average calculation error is 12%, which is a good indicator.
Source: Ferra
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