Module #1 Introduction to Computational Thermodynamics Overview of computational thermodynamics, its importance, and applications
Module #2 Thermodynamic Fundamentals Review of thermodynamic principles, laws, and equations of state
Module #3 Computational Tools for Thermodynamics Introduction to computational tools and software used in thermodynamics, such as MATLAB, Python, and Thermo-Calc
Module #4 Phase Equilibria and Phase Diagrams Computational methods for predicting phase equilibria and constructing phase diagrams
Module #5 Thermodynamic Property Prediction Computational methods for predicting thermodynamic properties, such as Gibbs energy, entropy, and heat capacity
Module #6 Calphad Methodology Introduction to the CALPHAD (Calculation of Phase Diagrams) methodology and its applications
Module #7 Thermodynamic Databases Overview of thermodynamic databases, such as SGTE, COST, and NIST
Module #8 Molecular Dynamics Simulations Introduction to molecular dynamics simulations, including the basics of MD, potential energy functions, and simulation algorithms
Module #9 Monte Carlo Simulations Introduction to Monte Carlo simulations, including the basics of MC, Metropolis algorithm, and importance sampling
Module #10 Density Functional Theory Introduction to Density Functional Theory (DFT), its principles, and applications in materials science
Module #11 Thermodynamic Integration Computational methods for thermodynamic integration, including the Frenkel-Ladd method and the Einstein method
Module #12 Free Energy Calculations Computational methods for free energy calculations, including the thermodynamic integration method and the Bennett acceptance ratio method
Module #13 Chemical Kinetics and Reaction Modeling Introduction to chemical kinetics, reaction rates, and reaction modeling using computational methods
Module #14 Transport Properties Computational methods for predicting transport properties, such as diffusivity, viscosity, and thermal conductivity
Module #15 Interfacial Phenomena and Surface Thermodynamics Computational methods for studying interfacial phenomena and surface thermodynamics
Module #16 Case Studies in Materials Science Applications of computational thermodynamics and simulations in materials science, including case studies on alloys, ceramics, and polymers
Module #17 High-Throughput Computing and Machine Learning Introduction to high-throughput computing and machine learning methods for accelerating computational thermodynamics and simulations
Module #18 Validation and Verification of Computational Methods Importance of validation and verification in computational thermodynamics and simulations, including methods for error estimation and uncertainty quantification
Module #19 Thermodynamic Modeling of Battery Materials Applications of computational thermodynamics and simulations in the development of battery materials
Module #20 Thermodynamic Modeling of Fuel Cells Applications of computational thermodynamics and simulations in the development of fuel cells
Module #21 Thermodynamic Modeling of Biomaterials Applications of computational thermodynamics and simulations in the development of biomaterials
Module #22 Thermodynamic Modeling of Energy Storage Materials Applications of computational thermodynamics and simulations in the development of energy storage materials
Module #23 Thermodynamic Modeling of Catalytic Materials Applications of computational thermodynamics and simulations in the development of catalytic materials
Module #24 Thermodynamic Modeling of Advanced Materials Applications of computational thermodynamics and simulations in the development of advanced materials, including nanomaterials and metamaterials
Module #25 Thermodynamic Modeling of Environmental Systems Applications of computational thermodynamics and simulations in environmental systems, including climate modeling and geochemistry
Module #26 Thermodynamic Modeling of Biological Systems Applications of computational thermodynamics and simulations in biological systems, including protein-ligand interactions and biochemical reactions
Module #27 Thermodynamic Modeling of Food Science and Technology Applications of computational thermodynamics and simulations in food science and technology, including food processing and quality control
Module #28 Thermodynamic Modeling of Pharmaceuticals Applications of computational thermodynamics and simulations in pharmaceutical development, including drug design and delivery
Module #29 Thermodynamic Modeling of Aerospace Materials Applications of computational thermodynamics and simulations in aerospace materials, including propulsion systems and heat shields
Module #30 Course Wrap-Up & Conclusion Planning next steps in Computational Thermodynamics and Simulations career
