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Meeting 2022 TMS Annual Meeting & Exhibition
Symposium Frontiers of Materials Award Symposium Session: Data-Driven, Machine-learning Augmented Design and Novel Characterization for Nano-architectured Materials
Presentation Title “Big Data” Characterization of Material Properties and High Temperature Kinetics
Author(s) James Horwath, Peter W. Voorhees, Eric A. Stach
On-Site Speaker (Planned) James Horwath
Abstract Scope Competition between various coarsening and degradation mechanisms in supported nanoparticles inhibits the performance and stability of heterogeneous catalysts. While mean field models provide a physical understanding of the average behavior of the system, these models neglect local effects which are important at the nanoscale. By pairing in situ Transmission Electron Microscopy with unsupervised machine learning for automated image analysis, we quantify the degradation of supported Au nanoparticles at high temperature in real time. After developing a model to predict average particle growth as a function of chamber pressure and temperature, we use evolution trajectories from hundreds of individual nanoparticles to retrieve values for physical properties of the system with high accuracy. Further, by comparing extracted property values with those found in the literature, we characterize the system in terms of properties which are impossible to measure through traditional experiments, such as the distance over which nanoparticles interact.
Proceedings Inclusion? Undecided
Keywords Characterization, Machine Learning, Nanotechnology


Accelerated Discovery of Multi-phase Refractory Alloys through Machine Learning Surrogate Models of CALPHAD
Autonomous X-ray Scattering for the Study of Non-equilibrium Self-assembly
Designing Nano-architectured Materials with a Machine-learning Augmented Framework
Discovery of Nanocomposite Phase Change Memory Materials via Closed-loop Autonomous Combinatorial Experimentation
Intelligent Design of Additively Manufactured Architected Materials
Machine Learning Based Hierarchical Multi-scale Modeling of Mechanical Deformation for Metal-matrix-nano-composites
Volumetric Nanoscale Imaging of DNA-assembled Nanoparticle Superlattices
“Big Data” Characterization of Material Properties and High Temperature Kinetics

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