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Meeting MS&T24: Materials Science & Technology
Symposium Understanding High Entropy Materials via Data Science and Computational Approaches
Presentation Title Characterization of Thermal Sprayed Ultrahard Coatings for Stamping Die Surfaces from Refractory High Entropy Alloys Designed Using DFT Calculations
Author(s) Iver E. Anderson, Duane D. Johnson, Prashant Singh, Rameshwari Naorem, Yun Bai, Bill Lenling, Kyle Quillin, Irina Downs, Jim Watts, John Koppes, Nicolas Argibay
On-Site Speaker (Planned) Iver E. Anderson
Abstract Scope Better sheet metal stamping processes, especially for aluminum alloy sheet, could achieve greater manufacturing efficiency for lightweight automotive panels. Lighter vehicles from these panels will improve gas mileage for ICE vehicles and extend driving range for electric vehicles. Wear resistant die coatings are being developed from gas atomized powders of ultrahard refractory high-entropy alloys (RHEAs) developed by AMES and SNL-NM using DFT methods. These powder-based thermal spray coatings are intended to extend the life of automotive sheet metal stamping die inserts and my may minimize the need for die lubricants. These initial collaborations with Ford involve wear test specimens that are HVOF (high velocity oxy-fuel) coated with O2/kerosene and O2/H2 torches with at least 100µm layers on flat and grooved steel (carbon-steel, 304SS, D2, or S7) coupons. Results of microstructure and hardness analysis and initial wear and forming tests are reported. Support from USDOE-EERE-AMMTO through Ames Laboratory Contract No. DE-AC02-07CH11358.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A First Principles High Throughput Screening Method for Corrosion Resistant High Entropy Materials
Analyzing, Understanding, and Guided Design of Solid Disordering by the Density of Atomistic States (DOAS)
Characterization of Thermal Sprayed Ultrahard Coatings for Stamping Die Surfaces from Refractory High Entropy Alloys Designed Using DFT Calculations
Contributions to Diffusion in Complex Materials Quantified with Machine Learning
Design Metastability in High-Entropy Alloys by Tailoring Unstable Fault Energies
Electronic-Structure-Guided Tailoring of Refractory High-Entropy Alloys for Extreme Environment
Electronic Descriptors for Dislocation Deformation Behavior and Intrinsic Ductility in bcc High-Entropy Alloys
Entropy for Energy: High-Entropy Materials for Energy Applications
Factors Affecting Calculated Properties of RHEAs Using Density Functional Theory
From BIG-Data to HOT-Properties of High-Entropy Carbides and Carbo-Nitrides
Grain Boundary Segregation-Driven Elemental Patterning Amplifies Chemical Short-Range Order in NiCoCr
Lattice Correspondence Analyses of Phase Transformations in a High Entropy Alloy
Machine Learning Design of Additively Manufacturable Tungsten-Based Refractory Multi Principle Element Alloys with Enhanced Strength at Extreme Temperatures
Modeling Distribution of Unstable Stacking Fault Energy in bcc Refractory High-Entropy Alloys and its Implication to Ductility Assessment
Predicting Intrinsic Ductility of Refractory High Entropy Alloys
Predictive Screening of Phase Stability in High-Entropy Borides
Screening High-Entropy Oxide Compositions Using Machine Learned Interatomic Potential
Spinel-Structured Precipitate Morphology in High-Entropy Mg0.2Ni0.2Co0.2Cu0.2Zn0.2O Epitaxial Films: Thermodynamic and Phase-Field Investigations
ULTERA: A Data Ecosystem for High Entropy Materials (HEMs)
Using Materials Informatics to Quantify Complex Correlations Linking Structure, Properties and Processing in High-Entropy Alloys
Utilizing Atomistic Calculations for Processing High-Value Magnetic Material Derived from FeNiMoW

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