Scientists Use Math To 3D Print The World's Strongest Steel
Aadhya Khatri - Apr 22, 2020
The mathematical model will determine which settings of laser are the best for reducing flaws in steel and making it stronger
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Experts from the U.S Air Force and the Texas A&M University said they had found a new method to 3D print the world’s strongest kind of steel and several other metals, with a tremendous help of math.
This technology has the same underlying principles as powder welding. It involves using lasers to melt steel powder. A mathematical model will determine which settings of laser are the best for reducing flaws.

The team shared that the framework for the invention used the Eagar-Tsai model to predict the geometry of the melt pool. The model is calibrated with single-track experiments.
One of the advantages of this model is that it is computationally inexpensive, meaning it requires only a small amount of processing power This term is usually used when referring to a new method that can help save lots of time.
The answer to the question of why math can make stronger metal lies in a handful of facts about 3D printing and steel. The kind of metal the researchers pay particular attention to is called martensite steel. It is made by using extreme cooling so that carbon is trapped inside the metal's structure.
Carbon steels can be brittle and the technique of additive manufacturing, another term to call 3D printing, may create porosities, or flaws, to the final products. These flaws are small holes inside the structure that can weaken steels.

What researchers did to reduce porosities was to varying the intensity of the laser used and also its pulses to fine-tune their 3D printing model.
What comes next for the researchers is to continue tuning until their mathematical model can predict if particular settings work or not.
This invention could help steel manufacturers save a ton of time and material going waste when they experiment with 3D printing. Better, it might even entice them to start looking into 3D printing as a promising manufacturing method.
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