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Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Accelerated Discovery and Insertion of Next Generation Structural Materials
Presentation Title A High-throughput Setup for Materials Exposure to Simultaneous Irradiation-corrosion Conditions
Author(s) Franziska Schmidt, Hyosim Kim, Yongqiang Wang, Peter Hosemann
On-Site Speaker (Planned) Franziska Schmidt
Abstract Scope The development of new materials suitable for irradiation-corrosion environments, such as nuclear reactors, requires extensive testing of proposed alloy compositions. Simultaneous irradiation-corrosion experiments are notoriously complicated, especially if repeatable quantitative results are desired to inform machine learning approaches. We propose a high-throughput approach for such experiments for thin (<10 Ám) bulk samples or deposited thin-films. This is achieved by reducing the corrosive-medium volume, which allows us to produce tens of samples per irradiation, compared to one sample per experiment in similar recent work. A major disadvantage is that the achievable total dpa is inevitably low (<<0.1 dpa). However, the goal is to eliminate those alloys that show unsuitable performance, even at low dpa levels. In this talk, we will show initial results of Fe and stainless steel corrosion by lead-bismuth eutectic under simultaneous proton irradiation and discuss the applicability of this method for other corrosive media.
Proceedings Inclusion? Planned:
Keywords Nuclear Materials, Iron and Steel, Thin Films and Interfaces

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

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

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