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Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Hume-Rothery Symposium on First-Principles Materials Design
Presentation Title Predicting Synthesis and Synthesizability Beyond the DFT Convex Hull
Author(s) Wenhao Sun
On-Site Speaker (Planned) Wenhao Sun
Abstract Scope The computational materials discovery pipeline often remains bottlenecked by the difficulty of synthesizing predicted compounds in the lab. To realize the vision of accelerated materials design, a quantitative and predictive theory of materials synthesis is urgently needed. From a theoretical perspective, three guiding questions for predictive synthesis are: 1) Which compounds designed in silico can be synthesized? 2) For a computationally-designed material, which materials synthesis method—e.g. solid-state, hydrothermal, vapor deposition, etc.—is best to synthesize it? 3) Within the parameter space of that synthesis method, what synthesis ‘recipe’ can lead to a phase-pure synthesis of the predicted compound? I will illustrate how careful consideration of the local thermodynamic conditions where materials nucleate can help us anticipate which stable or metastable phases which may form during synthesis. Guided by these insights, solid-state chemists can more rationally navigate the thermodynamic and kinetic energy landscape towards the targeted synthesis of desired materials.
Proceedings Inclusion? Planned:
Keywords Computational Materials Science & Engineering, Ceramics, Modeling and Simulation

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
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
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
Probabilistic Approach to Materials Modeling
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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