cutting materials

A new model improves the resistance of hard cutting materials

Researchers at Linköping University, in Sweden, have developed a theoretical model that improves the resistance of hard cutting materials, enabling simulations for showing what happens as they degrade. The model will enable manufacturing industries to save time and money. 

Titanium-aluminium nitride is a ceramic material commonly used as a coating for metal cutting tools. With the aid of a titanium-aluminium nitride thin film, the cutting edge of a coated tool becomes harder, and the lifetime of the tool longer. The coated surface becomes even harder during the cutting process, a phenomenon that is known as age hardening. The alloy is, however, sensitive to high temperature: a few minutes of cutting operation in a truly hard material subjects the cutting edge to such a high pressure that it is heated to nearly 900 degrees or above. The material is unharmed up to 700 degrees, but it starts to degrade at higher temperatures. The edge softens and loses sharpness.

Until now, no one has been able to determine what happens at the atomic level inside the thin film during the cutting process. It has only been possible to partially simulate the properties of the complex combination of titanium, aluminium and nitrogen, and it has not been possible to draw any conclusions from the results.

The researchers spent four years developing a reliable theoretical model that can be used to show exactly what happens in the material. They have used the newly developed model to simulate events in the material, showing which atoms are displaced and the consequences this has for the properties.

“This also means that we can develop strategies to stop the degradation, such as alloying the materials or creating specially-designed nanostructures,” says Davide Sangiovanni, of the Division of Theoretical Physics.

The new theoretical model calculates the forces between the atoms in the material. The model is based on a previously known method that has been successfully used in simple material systems. Complex combinations of materials, however, require time-demanding calculations that are only possible in a supercomputer. The research group from Linköping University (LiU) has optimized these calculations by implementing machine learning algorithms.

The supercomputer at the National Supercomputer Centre at LiU has been used to calculate around 40 alloys of titanium, aluminium and nitrogen, while looking at several properties of the material. The scientists have then compared the results from the calculations with the known properties of the materials.

The researchers hope that the method will be useful for companies in the manufacturing industry, which could save a lot of money by developing tools with greater hardness and resistance.

“For the first time, we can now carry out large-scale classical simulations of atomic structures in one of the material systems most commonly used for metal cutting and forming. The simulations can consider resistance to heat or nanostructures, and they may provide important insight into how the atoms move. The results will help us avoid, or at least delay, degradation of the material,” says Kostas Sarakinos head of the Nanoscale Engineering Division.