Welcome to Computational Problem Solving in the Chemical Sciences

Part 1. Introduction to Python Computations

• Chapter 1: Introduction to Python for the Chemical Sciences
• Chapter 2: Essential Python Packages for the Chemical Sciences
• Chapter 3: Control Structures in Python

Part 2. Numerical Methods in Python

• Chapter 4: Chemical Reaction Equilibria and Roots of Equations
• Chapter 5: Chemical Bonding and Numerical Integration
• Chapter 6: Balancing Chemical Equations and Systems of Linear Algebraic Equations

Part 3. Statistics — Regression and Correlation

• Chapter 7: Orders of Reaction and Linear Regression Analysis
• Chapter 8: Calibration Data, Confidence Intervals, and Correlation Analysis

Part 4. Introduction to Molecular Simulations

• Chapter 9: Classical Thermodynamics
• Chapter 10: Statistical Thermodynamics
• Chapter 11: Ensembles and Ergodicity

Part 5. Monte Carlo Simulations

• Chapter 12: The Monte Carlo Method
• Chapter 13: Monte Carlo Integration
• Chapter 14: A Basic Monte Carlo Algorithm
• Chapter 15: Nanoparticle Shape and Simulated Annealing
• Chapter 16: Technical Details: Boundary Conditions, Truncation of Interactions, Etc.
• Chapter 17: Lipid Interactions in Membranes and Monte Carlo Simulations
• Chapter 18: Monte Carlo Simulations of Adsorption on Surfaces
• Project 1: Grand Canonical Monte Carlo Simulations of Competitive Adsorption

Part 6. Molecular Dynamics Simulations

• Chapter 19: Molecular Dynamics
• Chapter 20: Verlet Integration
• Chapter 21: Thermostatting
• Chapter 22: Atomic Simulation Environment (ASE)
• Chapter 23: Radial Distribution Function
• Project 2: Molecular Dynamics Simulations of a Polymer Chain

Part 7. Advanced and Emerging Topics in Computational Chemistry

• Chapter 24: Newton-Raphson Method
• Chapter 25: Kinetic Monte Carlo
• Chapter 26: scikit-learn
• Chapter 27: Nested Sampling