ProgramMaster Logo
Conference Tools for 2023 TMS Annual Meeting & Exhibition
Register as a New User
Submit An Abstract
Propose A Symposium
Presenter/Author Tools
Organizer/Editor Tools
About this Abstract
Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Accelerated Discovery and Insertion of Next Generation Structural Materials
Presentation Title A Diffusion Couple Approach to β-Ti Alloy Development: Evaluating the Oxidation Performance of Ti-Fe-X+ Alloys
Author(s) Paraic O'Kelly, Alexander Knowles
On-Site Speaker (Planned) Paraic O'Kelly
Abstract Scope Materials discovery has greatly benefited from ICME utilising thermodynamic databases, however the predictive capability of ICME can be poor when extrapolating to new materials systems away from current understanding, precisely where the largest potential innovations may lie. Recently in the Ti-Fe system, ordered-bcc precipitate-reinforced refractory-metal-based alloys has demonstrated the possibility of β –β’ bcc-superalloys as a new class of high temperature materials. However, the introduction of scale-forming elements is required. The current research applies a diffusion couple approach to generate compositional and microstructural gradients in the Ti-Fe-Al-Cr composition space. As such, the oxidation characteristics of the graded alloy are assessed which offers key insights into composition-microstructure-property relations and a move away from the iterative ingot-by-ingot approach. The experimental results enable a significant down selection of promising discrete quaternary alloys for further study to optimise chemistry, microstructure, environmental and mechanical response.
Proceedings Inclusion? Planned:
Keywords High-Temperature Materials, Titanium, Characterization


A Design Space for Tunable Ceramic-polymer Composites
A Diffusion Couple Approach to β-Ti Alloy Development: Evaluating the Oxidation Performance of Ti-Fe-X+ Alloys
A High-throughput Setup for Materials Exposure to Simultaneous Irradiation-corrosion Conditions
Accelerated Discovery of Novel Titanium Alloys using High-throughput Manufacturing, Characterization and Testing
Accelerating Multimodal Data Collection: A Workflow for Metallic Films
AI and Machine Learning Tools for Development and Analysis of Image Driven 2D Materials
Combinatorial Mechanical Microscopy via Correlated Nanoindentation and EDX Mapping
Computational Design of an Ultra-strong High-entropy Alloy
Computational Design of High Entropy Alloy Hardmetals
Design of a Compact Morphology Cobalt-based Superalloy for Additive Manufacturing
Efficient Conductivity and Hardness Optimization in Cu-Ag-Ni Alloys using Bayesian Active Learning
High-throughput Electric-Field-assisted Sintering and Characterization Techniques for Materials Discovery
High-throughput Prediction of Fracture and Brittle to Ductile Transition in Tungsten using Variable Temperature Nanoindentation
High-throughput Synthesis and Mechanical Characterization of Sputtered Metallic Alloys
How Should You Select an Algorithm for a Materials Discovery Campaign with Multiple Objectives, Complex and High-dimensional Structure-processing-property Relationships, and a Small Adaptive Design Budget?
Machine Learning-assisted Discovery of Novel High Temperature Ni-rich NiTiHfZr Multi-component Shape Memory Alloys
Rapid Characterisation of Active Slip Systems in Titanium Ordered-bcc Compounds using an Algorithm for Automated Indentation Slip Trace Analysis.
Using Machine Intuitive Learning to Predict Advanced Steel Properties

Questions about ProgramMaster? Contact