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Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Hume-Rothery Symposium on First-Principles Materials Design
Presentation Title Establishing links between synthesis, defect landscape, and ion conduction in halide-type solid electrolytes
Author(s) Raphaele J. Clement
On-Site Speaker (Planned) Raphaele J. Clement
Abstract Scope Rocksalt-type halide electrolytes have spurred interest over the past few years due to their high ionic conductivities and stability against high voltage cathodes. While their conduction properties depend sensitively on synthesis conditions, these materials constitute a challenge for characterization. I will show that a combination of synchrotron XRD, NMR, and first principles and molecular dynamics simulations, allows us to determine the origin of high ion conduction, providing key design principles for this family of electrolytes. Our work has revealed that the high conductivity of ball-milled Li3YCl6 stems from the presence of stacking faults in the rocksalt-type structure.[1] Exploring Na3-xY1-xZrxCl6 compounds, we have again found that disorder facilitates ionic diffusion in mixed Y/Zr compositions[2,3], while conduction is affected by polymorphism in Na3YCl6 and Na2ZrCl6. [1] Sebti et al., J. Am. Chem. Soc., 144, 5795 (2022). [2] Wu et al., Nat. Commun., 12(1), 1256 (2021). [3] Sebti et al., in preparation.
Proceedings Inclusion? Planned:
Keywords Computational Materials Science & Engineering, Characterization, Energy Conversion and Storage

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

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
Matterverse.ai - 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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