Mar 23, 2019 | Updated: 12:48 PM EDT

A theoretical model can now help the manufacturing industry to save both time and money

Mar 11, 2019 11:05 AM EDT


A material that is used as a coating for metal cutting tools is a titanium-aluminum nitride. With the aid of this material's thin film, the cutting edge of a tool that is coated becomes harder, and the lifetime of the tool a lot longer. A particular feature of the coated surface is that it becomes even harder while it is being cut, this process is known as age hardening.

Kostas Sarakinos, associate professor in materials science at Linköping University, describes the titanium-aluminum nitride as a workhorse in the manufacturing industry.

However, this material is sensitive to high temperature. A few minutes within the cutting process in hard material subjects the cutting edge of the tool to a very high pressure that it is heated to almost 900 degrees or even above. At high temperatures like 700 degrees, the material is not harmed, but it starts to degrade at higher temperatures. The edge loses its sharpness, and it softens.

Until this day, no one has been able to determine what happens at the atomic level inside the thin film during the process of cutting the material. It has been possible to simulate the properties of the combination of aluminum, titanium, and nitrogen and they are a complex mix. There has been no possible conclusion drawn from the results.

"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 from the Division of Theoretical Physics.

The theoretical model that they've created can calculate the forces between the atoms that are in the material. The theoretical model is based on the method that was known previously, and it has been successfully used in simple material systems. Complex combinations of materials require calculations that demand a lot of time, and it is only possible by using a supercomputer. The researchers from the Linkoping University has optimized these time-demanding calculations by implementing machine learning algorithms which are the predecessor of artificial intelligence.

"The agreement is very good," says Kostas Sarakinos, Head of the Nanoscale Engineering Division. "It's important that we have calculated also properties that we know because then we can be sure that the calculations and predictions of the model are reliable."

The researchers from the Linkoping University is hoping that this method will be useful for companies in the manufacturing industry, which can help them save a lot of time and money by creating tools with resistance to wear and greater hardness.

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