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Laser Process Prints Defect-free Custom Alloy Parts

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A study from a Texas A&M University research team could make it easier to print uniform, defect-free parts using the laser bed powder fusion 3D-printing technique with metal alloys.

The researchers systematically investigated the effects of alloy composition on the printability and solidification of microstructures, to better understand how alloy composition, process variables, and thermodynamics affected additively manufactured parts. Through 3D-printing experiments, they defined the alloy chemistries and process parameters required to optimize alloy properties and print superior, identical parts at the microscale. Using machine learning, they created a formula that can be used with any type of alloy to help prevent nonuniformity.
A new method developed by Texas A&M researchers optimizes alloy properties and process parameters to create superior 3D-printed metal parts. Shown here is a colorized electron micrograph of a nickel powder alloy used in the study. Courtesy of Raiyan Seede.
A new method developed by Texas A&M researchers optimizes alloy properties and process parameters to create superior 3D-printed metal parts. Shown here is a colorized electron micrograph of a nickel powder alloy used in the study. Courtesy of Raiyan Seede.

Alloy metal powders used for additive manufacturing can contain a mixture of metals, such as nickel, aluminum, and magnesium, at different concentrations. During laser bed powder fusion 3D printing, these powders cool rapidly after they are heated by a laser beam. The different metals in the alloy powder have different cooling properties and solidify at different rates. This inconsistency can create microscopic flaws, or microsegregation.

“When the alloy powder cools, the individual metals can precipitate out,” researcher Raiyan Seede said. “Imagine pouring salt in water. It dissolves right away when the amount of salt is small, but as you pour more salt, the excess salt particles that do not dissolve start precipitating out as crystals. In essence, that’s what is happening in our metal alloys when they cool quickly after printing.” Seede said this defect appears as tiny pockets containing a slightly different concentration of the metal ingredients than what is found in other areas of the printed part.

The researchers investigated the solidification microstructures of four binary nickel-based alloys. In experiments, they studied the physical phase for each alloy at different temperatures and at increasing concentrations of the other metal in the nickel-based alloy. Using detailed phase diagrams, the researchers determined the chemical composition of each alloy that would cause the least microsegregation during additive manufacturing.

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Next, the researchers melted a single track of the alloy metal powder at different laser settings and determined the laser powder bed fusion process parameters that would deliver porosity-free parts.
A scanning electron microscope image of a single laser scan cross-section of a nickel and zinc alloy. Here, dark, nickel-rich phases interleave lighter phases with uniform microstructure. A pore can also be observed in the melt pool structure. Courtesy of Raiyan Seede.
A scanning electron microscope image of a single laser scan cross-section of a nickel and zinc alloy. Dark, nickel-rich phases interleave lighter phases with uniform microstructure. A pore can also be observed in the melt pool structure. Courtesy of Raiyan Seede. 

The information obtained from the phase diagrams, combined with the results from the single-track experiments, provided the team with a comprehensive analysis of the laser settings and nickel-based alloy compositions that could yield a porosity-free printed part without microsegregation.

The researchers next trained machine-learning models to identify patterns in the single-track experimental data and phase diagrams, to develop an equation for microsegregation that could be used with any alloy. Seede said the equation is designed to predict the extent of segregation given the alloy’s solidification range and material properties and laser’s power and speed.

“We take deep dives into fine-tuning the microstructure of alloys so that there is more control over the properties of the final printed object at a much finer scale than before,” Seede said.

As the use of alloys in AM increases, so will the challenges to printing parts that meet or exceed manufacturing quality standards. The Texas A&M study will enable manufacturers to optimize alloy chemistry and process parameters so that alloys can be designed specifically for additive manufacturing and manufacturers can control microstructures locally.

“Our methodology eases the successful use of alloys of different compositions for additive manufacturing without the concern of introducing defects, even at the microscale,” professor Ibrahim Karaman said. “This work will be of great benefit to the aerospace, automotive, and defense industries that are constantly looking for better ways to build custom metal parts.”

Professor Raymundo Arroyavé and professor Alaa Elwany, who collaborated with Seede and Karaman on the research, said that the methodology can easily be adapted by industries to build sturdy, defect-free parts with their alloy of choice.

The research was published in Additive Manufacturing (www.doi.org/10.1016/j.addma.2021.102258).

Published: October 2021
Glossary
machine learning
Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers to improve their performance on a specific task through experience or training. Instead of being explicitly programmed to perform a task, a machine learning system learns from data and examples. The primary goal of machine learning is to develop models that can generalize patterns from data and make predictions or decisions without being...
additive manufacturing
Additive manufacturing (AM), also known as 3D printing, is a manufacturing process that involves creating three-dimensional objects by adding material layer by layer. This is in contrast to traditional manufacturing methods, which often involve subtracting or forming materials to achieve the desired shape. In additive manufacturing, a digital model of the object is created using computer-aided design (CAD) software, and this digital model is then sliced into thin cross-sectional layers. The...
nano
An SI prefix meaning one billionth (10-9). Nano can also be used to indicate the study of atoms, molecules and other structures and particles on the nanometer scale. Nano-optics (also referred to as nanophotonics), for example, is the study of how light and light-matter interactions behave on the nanometer scale. See nanophotonics.
laser powder bed fusion
Laser powder bed fusion (LPBF) is a type of additive manufacturing (AM) or 3D printing technology that uses a high-power laser to selectively fuse or melt layers of powdered material to build up a three-dimensional object. This process is particularly common in metal additive manufacturing, where it is sometimes referred to as selective laser melting (SLM) or direct metal laser sintering (DMLS). Key features of laser powder bed fusion include: Powder bed: The process begins with a thin...
3d printing
3D printing, also known as additive manufacturing (AM), is a manufacturing process that builds three-dimensional objects layer by layer from a digital model. This technology allows the creation of complex and customized structures that would be challenging or impossible with traditional manufacturing methods. The process typically involves the following key steps: Digital design: A three-dimensional digital model of the object is created using computer-aided design (CAD) software. This...
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