Computational Thermodynamics and Simulations
( 30 Modules )

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

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Computational Thermodynamics and Simulations ( 30 Modules )

Computational Thermodynamics and Simulations
( 30 Modules )