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Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Hume-Rothery Symposium on First-Principles Materials Design
Presentation Title Computational Discovery of Materials with Fast Oxygen Kinetics
Author(s) Dane Morgan, Ryan Jacobs, Jun Meng, Md Sariful Sheikh, Jian Liu
On-Site Speaker (Planned) Dane Morgan
Abstract Scope In this talk we discuss our recent work on using molecular simulations to discover new materials with fast oxygen kinetics. We describe the prediction of BaFe0.125Co0.125Zr0.75O3 as having fast oxygen exchange and transport and demonstrate experimental confirmation of these predictions, including its integration into a solid oxide fuel cell cathode to yield an extremely low area specific resistance. We then describe the successful search for new interstitial oxide conductors, which are relatively rare, and predict multiple new families of these materials. We demonstrate experimentally that La4Mn5Si4O22 is a new interstitial diffuser with fast oxygen exchange and transport and with potential application in solid oxide technologies such as fuel cells and electrolyzers.
Proceedings Inclusion? Planned:
Keywords Energy Conversion and Storage, Modeling and Simulation,


Advances in Natural Language Processing for Building Datasets in Materials
Available methods for predicting materials synthesizability using computational and machine learning approaches
Computational Design of Multicomponent Nanoparticle Morphologies
Computational Discovery of Materials with Fast Oxygen Kinetics
Computational materials design and discovery for next-generation solid-state batteries
Computational tools for the generation of high-dimensional phase diagrams
Design of Novel Electrode and Solid Electrolyte Materials Guided by Crystal Structure Characterization and Understanding
Disorder and degradation in rock-salt-type lithium-ion battery cathodes
Double Descent, Linear Regression, and Fundamental Questions in Alloy Model Building
Dynamic stability design of materials for solid-state batteries
Establishing links between synthesis, defect landscape, and ion conduction in halide-type solid electrolytes
First principle design of high entropy materials for energy storage and conversion
From atom to system - how to build better batteries
Holistic Integration of Experimental and Computational Data and Simple Empirical Models for Diffusion Coefficients of Metallic Solid Solutions
Learning Rules for High-Throughput Screening of Materials Properties and Functions
Linking phenomenological theories of materials to electronic structure
Machine Learning Assisted Materials Generation
Machine Learning for Simulating Complex Energy Materials with Non-Crystalline Structures - A graph deep learning database of materials properties
Microstructure modeling with machine learning
Millisecond-ion Transport in Mixed Polyanion in Energy Materials
New battery chemistry from conventional layered cathode materials for advanced lithium-ion batteries
Origin of the Invar effect
Plasmonic high-entropy carbides
Predicting synthesis and synthesizability beyond the DFT convex hull
Probing Local Structures, Electronic Structures and Defects in Battery Materials by Combining NMR and DFT Calculations
Structure determination – from materials design to characterization
The Stewardship of a Materials Genome
Understanding Complex Materials and Interfaces through Molecular Dynamics Simulations
Understanding key properties of disordered rock-salt Li-ion cathode materials based on ab initio calculations and experiments
William Hume-Rothery Award Lecture: Ab initio Thermodynamics and Kinetics from Alloys to Complex Oxides

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