๐งช Chemical Engineering
ASE (Atomic Simulation Environment)
Description: A set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations.
Use Case: Used in molecular modeling, material science, and chemical reaction simulations.
Documentation: ASE Documentation
GitHub Repository: ASE GitHub
Cantera
Description: An open-source suite of tools for problems involving chemical kinetics, thermodynamics, and transport processes.
Use Case: Used for solving problems in combustion, chemical kinetics, and thermodynamic calculations.
Documentation: Cantera Documentation
GitHub Repository: Cantera GitHub
ChemPy
Description: A Python package useful for solving problems in chemistry.
Use Case: Chemical kinetics, equilibrium, and thermodynamics calculations.
Documentation: ChemPy Documentation
GitHub Repository: ChemPy GitHub
CoolProp
Description: A thermophysical property database and wrappers for several programming languages.
Use Case: Used for thermodynamic calculations and property evaluations in chemical engineering.
Documentation: CoolProp Documentation
GitHub Repository: CoolProp GitHub
DWSIM
Description: An open-source chemical process simulator.
Use Case: Chemical process modeling, simulation, design, optimization, and analysis.
Documentation: DWSIM Documentation
GitHub Repository: DWSIM GitHub
Matplotlib
Description: A plotting library for creating static, animated, and interactive visualizations.
Use Case: Generating plots and charts for visualizing chemical engineering data and simulation results.
Documentation: Matplotlib Documentation
GitHub Repository: Matplotlib GitHub
NumPy
Description: The fundamental package for scientific computing with Python.
Use Case: Handling numerical computations for process simulations and calculations in chemical engineering.
Documentation: NumPy Documentation
GitHub Repository: NumPy GitHub
Pandas
Description: Data analysis and manipulation library.
Use Case: Organizing and analyzing chemical process data, laboratory results, and operational data.
Documentation: Pandas Documentation
GitHub Repository: Pandas GitHub
Pyomo
Description: An open-source software package for formulating and solving large-scale optimization problems.
Use Case: Used in process optimization, design, and operational decision-making in chemical engineering.
Documentation: Pyomo Documentation
GitHub Repository: Pyomo GitHub
RDKit
Description: An open-source cheminformatics software.
Use Case: Cheminformatics, molecular modeling, and chemical structure analysis.
Documentation: RDKit Documentation
GitHub Repository: RDKit GitHub
Scikit-learn
Description: Machine learning in Python.
Use Case: Predictive modeling and data analysis in chemical engineering applications, like process optimization and fault detection.
Documentation: Scikit-learn Documentation
GitHub Repository: Scikit-learn GitHub
SciPy
Description: An open-source Python library used for scientific and technical computing.
Use Case: Technical computations and simulations in chemical engineering research.
Documentation: SciPy Documentation
GitHub Repository: SciPy GitHub
Seaborn
Description: A Python data visualization library based on Matplotlib.
Use Case: Creating informative and attractive statistical graphics in chemical engineering research and data analysis.
Documentation: Seaborn Documentation
GitHub Repository: [Seaborn GitHub](https://github.com
/mwaskom/seaborn)
SymPy
Description: A Python library for symbolic mathematics.
Use Case: Solving symbolic equations and expressions in chemical process modeling and reaction engineering.
Documentation: SymPy Documentation
GitHub Repository: SymPy GitHub
TensorFlow
Description: An open-source software library for machine learning applications.
Use Case: Developing machine learning models for process optimization, predictive maintenance, and system identification in chemical engineering.
Documentation: TensorFlow Documentation
GitHub Repository: TensorFlow GitHub
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