Designing and 3D Printing Alloys with High Strength, Ductility, Damage Tolerance, and Fatigue Properties by Developing Gradient in their Microstructure
Abstract
Approved for Public ReleaseTitle: Designing and 3D Printing Alloys with High Strength, Ductility, Damage Tolerance, and Fatigue Prop erties by Developing Gradient in their MicrostructureThe unique capabilities of making a gradient microstructure for improving the m echanical properties of metals and alloys, including the strength, ductility, damage tolerance and fatigue resistance, have been pro ven in a broad range of experimental works in the past few years. This gradient can be in the form of making a pre-designed distribu tion of grain sizes, introducing hierarchical architectures, or altering the density of nano twins or dual phase nano-bands at the m icroscale of the bulk material. However, despite being uniquely efficient, in practice making metals with a graded microstructures h as been entirely restricted to a narrow category of simple geometries. This limitation is because the gradient in the architecture o f the microstructure is generally implemented by means of performing some plastic deformation techniques on the surface of the bulk material, and the surface is not accessible in complex geometries. Also, all the available methods for making the gradient in the mi crostructure need sophisticated post-processing steps, that are time consuming, expensive, and accompanied with uncertainty such tha t with a high chance all the samples fabricated by these methods differ from each other, case by case.Surprisingly, 3D printing have some inherent features that can be employed to overcome all these challenges. During 3D printing of alloys, the processing paramete rs (and consequently the microstructure) can change point by point in the volume of the part. Although the processing parameters are normally kept constant during fabrication of a device, in this research we propose an alternative method in which: (i) the microstr ucture of any complex geometry is designed with a pre-defined gradient that improves the static and/or fatigue properties of the mat erial, (ii) a Neural Network-based algorithm is constructed and utilized to find out how the processing parameters need to be change d in the space during 3D printing to fabricate the designed graded microstructure, and (iii) the 3D printer s software is customized to manufacture the material with varying the processing parameters during 3D printing and making the designed gradient microstructu re. In the proposed method, the gradient in the microstructure will not be only restricted to a variation in the grains size, but in stead we will have control on the size and shape of multiple microstructural features, including subgranular cells, grains and meltp ools. Also, this method will be able to benefit from introducing hierarchy in the microstructure, a method that although has been re cognized to be uniquely efficient in improving the defect tolerance and fatigue resistance in materials, its implication has only be en limited to some specific categories of materials such as polymers, not metals and alloys, because of the manufacturing challenges .This research will be twofold: (I) a novel 3D printing methodology will be introduced to manufacture metallic components with engin eered microstructures, and consequently exceptional mechanical properties, and (II) during the course of this research, a broad rang e of novel experimental and computational frameworks will be developed which will elaborate our fundamental understanding of multipl e unknown aspects of 3D printing of metals.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 20, 2021
- Source ID
- N000142112781
Entities
People
- Reza Mirzaeifar
Organizations
- Office of Naval Research
- United States Navy
- Virginia Tech