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Meeting Materials Science & Technology 2019
Symposium Ceramics and Glasses Simulations and Machine Learning
Presentation Title Impact of Carbon Morphology on Mechanical Properties of SiCO Ceramics
Author(s) Shariq Haseen, Peter Kroll
On-Site Speaker (Planned) Shariq Haseen
Abstract Scope We show that carbon morphology, its distribution and bonding topology, affects the mechanical properties of SiCO ceramics. Such SiCO ceramics consist of a SiCO glass matrix and an embedded “free” carbon phase. SiCO models are generated with identical composition but different morphologies of the “free” carbon phase through molecular dynamics simulations using a Tersoff potential. Subsequently, we compute elastic properties and analyze the impact of morphology, composition, and density. A key outcome is that models with identical composition and density, but different “free” carbon morphologies, exhibit different shear moduli and Young’s moduli. “Free” carbon morphologies are tailored through annealing temperatures and holding times and vary from dispersed small units to graphene-like segregations and tubular structures within a SiCO glass matrix. Therefore, a “rule-of-mixture” based on composition or volume content does not correctly predict mechanical properties in SiCO, and instead morphologies of the constituents and their mutual interaction must be considered.
Proceedings Inclusion? Definite: At-meeting proceedings

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Atomistic Modeling of Fundamental Deformation Mechanisms in MAX Phases
Development of Boron Oxide Potentials for Computer Simulations of Multi-component Oxide Glasses
Embedding Machine Learning in the Physics of Disordered Solids
Exploring Molecular Dynamics Descriptors to Improve Machine Learning Predictions of Glass Forming Ability
Force-Enhanced Refinement of the Atomic Structure of Silicate Glasses
Genesis of “Free” Carbon in Silicon Oxycarbide Ceramics
Impact of Carbon Morphology on Mechanical Properties of SiCO Ceramics
Machine Learning-aided Development of Empirical Force-fields for Glassy Materials
Machine Learning and Energy Minimization Approaches for Crystal Structure Predictions: A Review and New Horizons
Machine Learning Applied to Zeolite Synthesis Enabled by Automatic Literature Data Extraction
Machine Learning to Predict the Elastic Properties of Glasses
Peridynamics Modeling of Impact-induced Crack Patterns in Glass
Physics-Based Machine Learning Models for High Throughput Screening of Novel Scintillator Chemistries
Predicting Nuclear Magnetic Resonance Parameters in Ceramics Using Density Functional Theory
Prediction of Compressive Strength and Modulus of Elasticity of Concrete Using Machine Learning Models
Reactive MD Simulations of Polysiloxanes: Modeling the Polymer-to-Ceramic Route towards Silicon Oxycarbide Ceramics
Role of Multi-state Hydrogen during Mayenite Electride Formation by First-principles Calculation
The Stability, Structure and Properties of the Zeta Phase in the Transition Metal Carbides
The Thermophysical Properties of TcO2
Thermal Conductivity of a Glass Material by First-principles Molecular Dynamics: The Case of GeTe4
Tuning Electronic Properties in II-IV-V2 Semiconductors via Sub-lattice Configurational Disorder

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