
- •COMPUTATIONAL CHEMISTRY
- •CONTENTS
- •PREFACE
- •1.1 WHAT YOU CAN DO WITH COMPUTATIONAL CHEMISTRY
- •1.2 THE TOOLS OF COMPUTATIONAL CHEMISTRY
- •1.3 PUTTING IT ALL TOGETHER
- •1.4 THE PHILOSOPHY OF COMPUTATIONAL CHEMISTRY
- •1.5 SUMMARY OF CHAPTER 1
- •REFERENCES
- •EASIER QUESTIONS
- •HARDER QUESTIONS
- •2.1 PERSPECTIVE
- •2.2 STATIONARY POINTS
- •2.3 THE BORN–OPPENHEIMER APPROXIMATION
- •2.4 GEOMETRY OPTIMIZATION
- •2.6 SYMMETRY
- •2.7 SUMMARY OF CHAPTER 2
- •REFERENCES
- •EASIER QUESTIONS
- •HARDER QUESTIONS
- •3.1 PERSPECTIVE
- •3.2 THE BASIC PRINCIPLES OF MM
- •3.2.1 Developing a forcefield
- •3.2.2 Parameterizing a forcefield
- •3.2.3 A calculation using our forcefield
- •3.3 EXAMPLES OF THE USE OF MM
- •3.3.2 Geometries and energies of polymers
- •3.3.3 Geometries and energies of transition states
- •3.3.4 MM in organic synthesis
- •3.3.5 Molecular dynamics and Monte Carlo simulations
- •3.4 GEOMETRIES CALCULATED BY MM
- •3.5 FREQUENCIES CALCULATED BY MM
- •3.6 STRENGTHS AND WEAKNESSES OF MM
- •3.6.1 Strengths
- •3.6.2 Weaknesses
- •3.7 SUMMARY OF CHAPTER 3
- •REFERENCES
- •EASIER QUESTIONS
- •HARDER QUESTIONS
- •4.1 PERSPECTIVE
- •4.2.1 The origins of quantum theory: blackbody radiation and the photoelectric effect
- •4.2.2 Radioactivity
- •4.2.3 Relativity
- •4.2.4 The nuclear atom
- •4.2.5 The Bohr atom
- •4.2.6 The wave mechanical atom and the Schrödinger equation
- •4.3.1 Introduction
- •4.3.2 Hybridization
- •4.3.3 Matrices and determinants
- •4.3.4 The simple Hückel method – theory
- •4.3.5 The simple Hückel method – applications
- •4.3.6 Strengths and weaknesses of the SHM
- •4.4.1 Theory
- •4.4.2 An illustration of the EHM: the protonated helium molecule
- •4.4.3 The extended Hückel method – applications
- •4.4.4 Strengths and weaknesses of the EHM
- •4.5 SUMMARY OF CHAPTER 4
- •REFERENCES
- •EASIER QUESTIONS
- •5.1 PERSPECTIVE
- •5.2.1 Preliminaries
- •5.2.2 The Hartree SCF method
- •5.2.3 The HF equations
- •5.2.3.1 Slater determinants
- •5.2.3.2 Calculating the atomic or molecular energy
- •5.2.3.3 The variation theorem (variation principle)
- •5.2.3.4 Minimizing the energy; the HF equations
- •5.2.3.5 The meaning of the HF equations
- •5.2.3.6a Deriving the Roothaan–Hall equations
- •5.3 BASIS SETS
- •5.3.1 Introduction
- •5.3.2 Gaussian functions; basis set preliminaries; direct SCF
- •5.3.3 Types of basis sets and their uses
- •5.4 POST-HF CALCULATIONS: ELECTRON CORRELATION
- •5.4.1 Electron correlation
- •5.4.3 The configuration interaction approach to electron correlation
- •5.5.1 Geometries
- •5.5.2 Energies
- •5.5.2.1 Energies: Preliminaries
- •5.5.2.2 Energies: calculating quantities relevant to thermodynamics and to kinetics
- •5.5.2.2a Thermodynamics; “direct” methods, isodesmic reactions
- •5.5.2.2b Thermodynamics; high-accuracy calculations
- •5.5.2.3 Thermodynamics; calculating heats of formation
- •5.5.2.3a Kinetics; calculating reaction rates
- •5.5.2.3b Energies: concluding remarks
- •5.5.3 Frequencies
- •Dipole moments
- •Charges and bond orders
- •Electrostatic potential
- •Atoms-in-molecules
- •5.5.5 Miscellaneous properties – UV and NMR spectra, ionization energies, and electron affinities
- •5.5.6 Visualization
- •5.6 STRENGTHS AND WEAKNESSES OF AB INITIO CALCULATIONS
- •5.7 SUMMARY OF CHAPTER 5
- •REFERENCES
- •EASIER QUESTIONS
- •HARDER QUESTIONS
- •6.1 PERSPECTIVE
- •6.2 THE BASIC PRINCIPLES OF SCF SE METHODS
- •6.2.1 Preliminaries
- •6.2.2 The Pariser-Parr-Pople (PPP) method
- •6.2.3 The complete neglect of differential overlap (CNDO) method
- •6.2.4 The intermediate neglect of differential overlap (INDO) method
- •6.2.5 The neglect of diatomic differential overlap (NDDO) method
- •6.2.5.2 Heats of formation from SE electronic energies
- •6.2.5.3 MNDO
- •6.2.5.7 Inclusion of d orbitals: MNDO/d and PM3t; explicit electron correlation: MNDOC
- •6.3 APPLICATIONS OF SE METHODS
- •6.3.1 Geometries
- •6.3.2 Energies
- •6.3.2.1 Energies: preliminaries
- •6.3.2.2 Energies: calculating quantities relevant to thermodynamics and kinetics
- •6.3.3 Frequencies
- •6.3.4 Properties arising from electron distribution: dipole moments, charges, bond orders
- •6.3.5 Miscellaneous properties – UV spectra, ionization energies, and electron affinities
- •6.3.6 Visualization
- •6.3.7 Some general remarks
- •6.4 STRENGTHS AND WEAKNESSES OF SE METHODS
- •6.5 SUMMARY OF CHAPTER 6
- •REFERENCES
- •EASIER QUESTIONS
- •HARDER QUESTIONS
- •7.1 PERSPECTIVE
- •7.2 THE BASIC PRINCIPLES OF DENSITY FUNCTIONAL THEORY
- •7.2.1 Preliminaries
- •7.2.2 Forerunners to current DFT methods
- •7.2.3.1 Functionals: The Hohenberg–Kohn theorems
- •7.2.3.2 The Kohn–Sham energy and the KS equations
- •7.2.3.3 Solving the KS equations
- •7.2.3.4a The local density approximation (LDA)
- •7.2.3.4b The local spin density approximation (LSDA)
- •7.2.3.4c Gradient-corrected functionals and hybrid functionals
- •7.3 APPLICATIONS OF DENSITY FUNCTIONAL THEORY
- •7.3.1 Geometries
- •7.3.2 Energies
- •7.3.2.1 Energies: preliminaries
- •7.3.2.2 Energies: calculating quantities relevant to thermodynamics and kinetics
- •7.3.2.2a Thermodynamics
- •7.3.2.2b Kinetics
- •7.3.3 Frequencies
- •7.3.6 Visualization
- •7.4 STRENGTHS AND WEAKNESSES OF DFT
- •7.5 SUMMARY OF CHAPTER 7
- •REFERENCES
- •EASIER QUESTIONS
- •HARDER QUESTIONS
- •8.1 FROM THE LITERATURE
- •8.1.1.1 Oxirene
- •8.1.1.2 Nitrogen pentafluoride
- •8.1.1.3 Pyramidane
- •8.1.1.4 Beyond dinitrogen
- •8.1.2 Mechanisms
- •8.1.2.1 The Diels–Alder reaction
- •8.1.2.2 Abstraction of H from amino acids by the OH radical
- •8.1.3 Concepts
- •8.1.3.1 Resonance vs. inductive effects
- •8.1.3.2 Homoaromaticity
- •8.2 TO THE LITERATURE
- •8.2.1 Books
- •8.2.2 The Worldwide Web
- •8.3 SOFTWARE AND HARDWARE
- •8.3.1 Software
- •8.3.2 Hardware
- •8.3.3 Postscript
- •REFERENCES
- •INDEX
Chapter 3
Molecular Mechanics
We don’t give a damn where the electrons are.
Words to the author, from the president of a well-known chemical company, emphasizing his firm’s position on basic research.
3.1PERSPECTIVE
Molecular mechanics (MM) [1] is based on a mathematical model of a molecule as a collection of balls (corresponding to the atoms) held together by springs (corresponding to the bonds) (Fig. 3.1). Within the framework of this model, the energy of the molecule changes with geometry because the springs resist being stretched or bent away from some “natural” length or angle, and the balls resist being pushed too closely together. The mathematical model is thus conceptually very close to the intuitive feel for molecular energetics that one obtains when manipulating molecular models of plastic or metal: the model resists distortions (it may break!) from the “natural” geometry that corresponds to the bond lengths and angles imposed by the manufacturer, and in the case of space-filling models, atoms cannot be forced too closely together. The MM model clearly ignores electrons.
The principle behind MM is to express the energy of a molecule as a function of its resistance toward bond stretching, bond bending, and atom crowding, and to use this energy equation to find the bond lengths, angles, and dihedrals corresponding to the minimum-energy geometry – or more precisely, to the various possible potential energy surface minima (chapter 2). In other words, MM uses a conceptually mechanical model of a molecule to find its minimum-energy geometry (for flexible molecules, the geometries of the various conformers). The form of the mathematical expression for the energy, and the parameters in it, constitute a forcefield, and MM methods are sometimes called forcefield methods. The term arises because the negative of the first derivative of the potential energy of a particle with respect to displacement along some direction is the force on the particle; a “forcefield” E(x, y, z coordinates of atoms) can be differentiated to give the force on each atom.

44 Computational Chemistry
The method makes no reference to electrons, and so cannot (except by some kind of empirical algorithm) throw light on electronic properties like charge distributions or nucleophilic and electrophilic behaviour. Note that MM implicitly uses the Born– Oppenheimer approximation, for only if the nuclei experience what amounts to a static attractive force, whether from electrons or springs, does a molecule have a distinct geometry (section 2.3).
An important point, which students sometimes have a problem with, is that the concept of a bond is central to MM, but not essential – although often useful – in electronic structure calculations. In MM a molecule is defined by the atoms and the bonds, which latter are regarded almost literally as springs holding the atoms together. Usually, bonds are placed where the rules for drawing structural formulas require them, and to do a MM calculation you must specify each bond as single, double, etc., since this tells the program how strong a bond to use (sections 3.2.1 and 3.2.2). In an electronic structure calculation – ab initio (chapter 5), semiempirical (SE) (chapter 6), and density functional theory (chapter 7) – a molecule is defined by the relative positions of its atomic nuclei, the charge, and the “multiplicity” (which follows easily from the number of unpaired electrons). An oxygen nucleus and two protons with the right x, y, z coordinates, no charge, and multiplicity one (no unpaired electrons) is a water molecule. There is no need to mention bonds here, although the chemist might wish to somehow extract this useful concept from this picture of nuclei and electrons. This can be done by calculating the electron density and associating a bond with, for example, a path along which electron density is concentrated, but there is no unique definition of a bond in electronic structure theory. It is worth noting, too, that in some graphical interfaces used in computational chemistry bonds are specified by the user, while in others they are shown by the program depending on the separation of pairs of atoms. The novice may find it disconcerting to see a specified bond still displayed even when a change in geometry has moved a pair of atoms far apart, or to see a bond vanish when a pair has moved beyond the distance recognized by some fudge factor.
Historically [2], MM seems to have begun as an attempt to obtain quantitative information about chemical reactions at a time when the possibility of doing quantitative quantum mechanical (chapter 4) calculations on anything much bigger than the hydrogen molecule seemed remote. Specifically, the principles of MM, as a potentially general method for studying the variation of the energy of molecular systems