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Tiarks, Jordan

Publications and source records attributed to Tiarks, Jordan.

Theory-guided design of duplex-phase multi-principal-element alloys

Density-functional theory (DFT) is used to identify phase-equilibria in multi-principal-element and high-entropy alloys (MPEAs/HEAs), including duplex-phase and eutectic microstructures. Here, a combination of composition-dependent formation energy and electronic-structure-based ordering parameters were used to identify a transition from FCC to BCC favoring mixtures, and these predictions experimentally validated in the Al-Co-Cr-Cu-Fe-Ni system. A sharp crossover in lattice structure and dual-phase stability as a function of composition were predicted via DFT and validated experimentally. The impact of solidification kinetics and thermodynamic stability was explored experimentally using a range of techniques, from slow (castings) to rapid (laser remelting), which showed a decoupling of phase fraction from thermal history, i.e., phase fraction was found to be solidification rate-independent, enabling tuning of a multi-modal cell and grain size ranging from nanoscale through macroscale. Strength and ductility tradeoffs for select processing parameters were investigated via uniaxial tension and small-punch testing on specimens manufactured via powder-based additive manufacturing (directed-energy deposition). This work establishes a pathway for design and optimization of next-generation multiphase superalloys via tailoring of structural and chemical ordering in concentrated solid solutions.

36 MATERIALS SCIENCE↗

CFD Simulations of Metal Powder Production by Gas Atomization

Many crucial components in energy production, e.g., stationary gas turbines and A-USCS power plants, are desirable to manufacture by additive manufacturing (AM) with the full development of the materials and processes. Typical gas atomized (GA) feedstock for metal AM is produced in spherical powder form, but often inefficiently with a wide size distribution and with reduced quality, e.g., having internal porosity, heavily oxidized surfaces, and “satellites” that degrade printing and build quality. The proposed project aims to significantly enhance the efficiency/precision and, moreover, the quality of metal powder production by computational fluid dynamics (CFD) simulations, probing the details of the physical processes occurring in supersonic gas atomizers. The goals are improving the desired powder size range yield and quality of GA powder, reducing material and energy production costs, and helping fulfill the immense the potential of AM, thereby enhancing the competitiveness of US manufacturing and of energy and transport sectors.

36 MATERIALS SCIENCE↗

Extreme hardness at high temperature with a lightweight additively manufactured multi-principal element superalloy

Materials are needed that can tolerate increasingly harsh environments, especially ones that retain high strength at extreme temperatures. Higher melting temperature alloys, like those consisting primarily of refractory elements, can greatly increase the efficiency of turbomachinery used in grid electricity production worldwide. Existing alloys, including Ni- and Co-based superalloys, used in components like turbine blades, bearings, and seals, remain a performance limiting factor due to their propensity, despite extensive optimization efforts, for softening and diffusion-driven elongation at temperatures often well above half their melting point. To address this critical materials challenge, we present results from integrating additive manufacturing and alloy design to guide significant improvements in performance via traditionally difficult-to-manufacture refractory alloys. We present an example of a multi-principal element alloy (MPEA), consisting of five refractory elements and aluminum, that exhibited high hardness and specific strength surpassing other known alloys, including superalloys. The alloy shows negligible softening up to 800°C and consists of four compositionally distinct phases, in distinction to previous work on MPEAs. Density functional theory calculations reveal a thermodynamic explanation for the observed temperature-independent hardness and favorability for the formation of this multiplicity of phases.

36 MATERIALS SCIENCE↗

Concentric Ring Gas Atomization Die Design for Optimized Particle Production

In partnership with Linde plc (formerly Praxair, Inc.), Ames Laboratory will further develop and commercialize its concentric-ring high pressure gas atomization (CR-HPGA) gas-die technology with a goal to improve the precision of metal powder production in a desired size range and quality. The successful commercialization of this technology could reduce production cost of metal powders and improve reliability of this industrial process, increasing specialty alloy powder availability for new applications and adoption into additive manufacturing and multiple materials sectors. The project scope is to [1] utilize AMES compressible gas flow and melt break-up models to explore a wide swath of parameter space available for the CR-HPGA technology, identifying the most promising gas-die designs for fabrication, [2] verify and optimize the new gas-die design, fabricate it and select preferred operating parameters by gas-only flow imaging and aspiration pressure measurements, down-selecting gas compositions and atomization parameters for full scale testing, [3] perform pilot-scale atomization trials with Al and/or Cu alloys of a new CR-HPGA gas-die at selected parameters, [4] evaluate gas-die performance by comparing resulting powder size distribution and powder quality attributes with equivalent powders made by conventional close-coupled HPGA technology, and [5] assess (through Praxair partnership) reduction in operational costs of new CR-HPGA gas-die through the use of an inert gas recovery/recycling system. In partnership with Praxair, Inc., the team, led by Ames Laboratory senior metallurgist Iver Anderson, intend to demonstrate the performance of an optimized CR-HPGA gas-die design in a pilot scale atomizer and better understand the design and operational controls to increase overall benefits for precision metal powder production.

42 ENGINEERING↗

Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data

In this work, we propose instance segmentation as a useful tool for image analysis in materials science. Instance segmentation is an advanced technique in computer vision which generates individual segmentation masks for every object of interest that is recognized in an image. Using an out-of-the-box implementation of Mask R-CNN, instance segmentation is applied to images of metal powder particles produced through gas atomization. Leveraging transfer learning allows for the analysis to be conducted with a very small training set of labeled images. As well as providing another method for measuring the particle size distribution, we demonstrate the first direct measurements of the satellite content in powder samples. After analyzing the results for the labeled data dataset, the trained model was used to generate measurements for a much larger set of unlabeled images. The resulting particle size measurements showed reasonable agreement with laser scattering measurements. The satellite measurements were self-consistent and showed good agreement with the expected trends for different samples. Finally, we present a small case study showing how instance segmentation can be used to measure spheroidite content in the UltraHigh Carbon Steel DataBase, demonstrating the flexibility of the technique.

36 MATERIALS SCIENCE↗