Python for Chemistry: An introduction to Python algorithms, Simulations, and Programing for Chemistry

1. Understanding Python Functions for Chemistry
 Introduction
 Structure
 Dictionary for atomic numbers and atomic masses
 Adding elements to the dictionary
 Updating elements in the dictionary
 Deleting elements from the dictionary
 Atomic mass percentage from molecular formula
 Data module for physical and chemical constants
 Molar gas constant from Boltzmann’s constant
 Estimation of volume of an ideal gas
 Quantum efficiency of photochemical reactions
 Fetching R f data of amino acids from .csv file
 Fetching selective data for amino acids from .csv file
 Converting 'amino_acids.csv' to dictionary
 Estimation of rate constant with data as a list
 Exporting rate constant data to .csv
 math module
 Power of 10 (e)
 pH metric acid-base titration
 R.M.S and average velocity of ideal gas molecules
 Rate constant from activation energy
 Calculating sine (angle) from radians
 Estimating bond length from the bond angle
 Priority for arithmetical operators
 Quotient and modulo operators
 Assignment operators
 Comparison operators
 Logical operators
 Identity operators
 Membership operators
 cmath module
 Scrutinizing user input data
 Tackling of errors in user inputs
 Number of electrons transferred in a redox reaction
 Conditions and loops
 if … elif … else statements
 Error handling with if … else loops
 Nested loops
 while loops
 for loops
 range() function
 Fetching selective rows of amino_acid.csv file
 timer() function
 Recording concentration with time (reaction rate)
 Recursion
 Predicting spin–spin coupling in NMR spectra
 Lambda function
 Conclusion
 2. Computations in Chemistry with NumPy
 Introduction
 Structure
 Why NumPy
 Dimension in arrays
 Indexing for arrays
 Negative indexing
 Shape of an array
 Reshaping the arrays
 Slicing of arrays
Iterating the arrays
 Entropy calculation for Beryllium compounds
 Concatenating arrays
 Concatenating 1-D arrays
 Concatenating based on axis values
 np.stack() function with axis 0 and 1
 Stacking arrays along rows, columns, and height
 Transpose of arrays
 Distribution coefficient for phenol
 Association factor of phenol in H 2 O and CHCl 3 75
 Important functions in NumPy
 Balancing equation by matrix row echelon form
 Solving systems of linear equations
 Equilibrium reactions and Quadratic equation
 Coefficients for 3 rd order polynomial equations
 Interpolations for unknown variables
 Reading and writing .csv file
 Lagrange interpolation – Viscosity of glycerol
 Basics of Lagrange interpolation
 3 rd order polynomial fit for viscosity of glycerol
 Conclusion
 3. Interpolation, Physico-chemical Constants, and Units with SciPy
 Introduction
 Structure
 SciPy for scientific computations
 Built-in scientific constants
 List of scientific constants
 Default unit for physical and chemical constants
 Base units for physical and chemical constants
 Interconversion of units
 SI prefixes
 Binary prefixes
 Current density – Electrochemical deposition of Cu
 Interconversion of units of pressure
 Interconversion of units of time
 Interconversion of units of length
 Interconversion of units of angle
 Interconversion of units of temperature
 Interconversion of units of energy
 Interconversion of units of power
 Interconversion of units of force
 Interconversion of units of different dimensions
 Interconversion of temperature units
 Sub packages
 SciPy Integration
 Integration with quad
 Integration with romberg
 Integration in NMR spectra – number of H atoms
 Roots of an equation
 Interpolation of viscosity of glycerol
 Cubic splines for irregular intervals with three data points
 Cubic splines for irregular intervals with higher accuracy
 Cubic Spline interpolation – Viscosity of glycerol
 Solving system of linear equations
 Straight line curve fitting – II order reactions
 Balancing chemical equations with matrices – Combustion of hexane
 Finding minima for a function – Vapor pressure
 Statistical functions
 Conclusion
 4. SymPy for Symbolic Computations in Chemistry
 Introduction
 Structure
 Why SymPy
 Basics of symbolic calculations
Differential derivatives with diff() module
 Integration with integrate() module
 Solving equations
 Matrix operations
 Binomial functions
 Sets
 Rate of a formation of CH 3 COOH by fermentation from I derivative
 Estimation of charge in an electrochemical cell – Definite integral
 Stoichiometric coefficient of a reaction – Matrix row echelon form
 Solving simultaneous arbitrary equations for concentrations
 Equilibrium reactions and quadratic equation
 Conclusion
 5. Interactive Plotting of Physico-chemical Data with Matplotlib
 Introduction
 Structure
 Why Matplotlib
 2D line graph
 Optimizing marker styles
 Optimizing line styles
 Font style
 Grid lines
 Tick marks
 Tick mark intervals
 Subplot
 Multiple data sets in a plot
 Data legend
 Bar charts
 Bar chart for thermodynamic parameters
 Pie chart – Composition of electrodeposited Ni-Co magnetic alloy
 Conclusion
 6. Introduction to Cheminformatics with RDKit
 Introduction
 Structure
 Installation and importing RDKit
 Chemical structure from SMILES
 Structure of molecule from .mol file
 Conversion of .mol to SMILES
 Kekule form of SMILES
 SMILES to .mol blocks
 Saving .mol in local directory
 Fetching number of atoms
 Fetching individual atoms
 Fetching bond types
 Position in ring (Boolean)
 Ring size (Boolean)
 Working with .sdf formats
 Stereochemical notation in molecules
 Highlighting bonds and atoms
 Conclusion
 7. ChemFormula for Atomic and Molecular Data
 Introduction
 Structure
 Installation and importing ChemFormula
 Formats for molecular formula
 To check radioactivity (Boolean)
 Fetching number of individual elements
 Estimation of molar / atomic mass
 Mass fraction / atomic percentage
 Calculating elemental fractions in %
 Conclusion
 8. Chemlib for Physico-chemical Parameters
 Introduction
Structure
 Installation and importing chemlib
 Fetching elemental data
 Molar mass and atomic percentage
 Number of moles and molecules
 Empirical formula
 Combustion reaction
 Balancing the chemical equation
 Finding limiting reagent
 pH and pOH
 Molarity calculation
 Electrode potential of an electrochemical cell
 Electrolysis
 Cathodic current efficiency (CCE)
 Frequency and wavelength of electromagnetic radiation
 Energy of an electron in Bohr orbital
 Conclusion
 9. ChemPy for Computations in Chemistry
 Introduction
 Structure
 Installation and importing ChemPy
 Fetching molar mass of compounds
 LaTeX, Unicode and .html formats
 Balancing the chemical equation
 Stoichiometric molar mass fractions
 Balancing equations of ionic equilibria
 Ionic strength
 .chemistry.Reaction module
 Web publishing the reaction
 LaTeX form for reactions
 Unicode form for reactions
 Number of phases
 Reaction rates
 Segregating elements with atomic number
 Derived units
 .kinetics.arrhenius module
 Conclusion
 10. Mendeleev Package For Atomic and Ionic Data
 Introduction
 Structure
 Installation and importing Mendeleev
 Fetching properties of element
 Fetching oxidation states of an element
 Ionization energies of an element
 Fetching isotopic parameters
 Fetching ionic radii and crystal radii
 Effective nuclear charge
 Electronegativity
 Fetching elemental data
 Conclusion
 11. Computations of Parameters of Electrolytes with PyEQL
 Introduction
 Structure
 Installation and importing pyEQL
 Density of the solutions
 Specific conductance
 Ionic strength
 Weight of the ionic components
 Activity coefficients
 Diffusion coefficients
 Functions related to molecular formula
 Solution parameters
 Simulation of ionic conductance
Osmotic pressure
 Data for kinematic and dynamic viscosities
 Units for ionic concentration
 Conclusion
 12. STK Module for Molecular Structures
 Introduction
 Structure
 Installation and importing stk
 Molecule with a specific functional group more than one
 Constructing polymeric reaction from monomers
 Constructing cage structures
 Optimizing the structure of molecules with rdkit
 Covalent organic frameworks
 Metal complexes
 Conclusion