- •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
364 Computational Chemistry
better than those from RHF calculations, at least in many cases. An extensive comparison of AM1 with ab initio and density functional methods for calculating geometries and relative energies is given in Hehre’s book [58]. Consistently good calculated reaction energies and especially activation energies require correlated ab initio methods (sections 5.4.2 and 5.5.2) or DFT methods (chapter 7). It is interesting that AM1 and PM3, which were parameterized mainly to give good energies (heats of formation) actually provide quite good geometries but energies of only modest quality.
6.3.3 Frequencies
The general remarks and the theory concerning frequencies in section 5.5.3, apply to SE frequencies too, but the zero-point energies are usually not needed, since the SE energy is normally not adjusted by adding the ZPE (section 6.2.5.2). As with ab initio calculations, SE frequencies are used to characterize a species as a minimum or a transition state (or a higher-order saddle point), and to get an idea of what the IR spectrum looks like. As with ab initio frequencies too, in SE methods the wavenumbers (frequencies) of vibrations are calculated from a mass-weighted second-derivative matrix (a hessian) and intensities are calculated from the changes in dipole moment accompanying the vibrations. Like their ab initio counterparts, SE frequencies are higher than the experimental ones; presumably this is at least partly due to the harmonic approximation, as was discussed in section 5.5.3.
Correction factors improve the fit between SE calculated and experimentally measured spectra, but the agreement does not become as good as does the fit of corrected
Semiempirical Calculations 365
ab initio to experimental spectra. This is because deviations from experiment are less systematic for SE than for ab initio methods (a characteristic that has been noted for errors in SE energies [68]). For AM1 calculations, correction factors of 0.9235 [69] and 0.9532 [70], and for PM3, factors of 0.9451 [69] and 0.9761 [70], have been recommended. A factor of 0.86 has been recommended for SAM1 for non-H stretches [71]. However, the variation of the correction factor with the kind of frequency is bigger for SE than for ab initio calculations; for example, for correcting carbonyl stretching frequencies, examination of a few molecules indicated (author’s work) that (at least for C, H, O compounds) correction factors of 0.83 (AM1) and 0.86 (PM3) give a much better fit to experiment. In Table 6.4 the factors of Ref. [69] were used. The after-correction deviations from experiment are considerably larger for AM1 and PM3 than for even moderate-level ab initio calculations: about 35% of the SE frequencies deviated by more than 10% from experiment, compared with 21% for HF/3–21G and 10% for HF/6-31G* [70].
366 Computational Chemistry
The calculated intensities of SE vibrations are much more approximate than those for ab initio vibrations (the latter are typically within 30% of the experimental intensity at the MP2 level), which is somewhat surprising, since SE (AM1 and PM3) dipole moments, from the vibrational changes of which intensities are calculated, are fairly accurate (section 6.3.4). Note that unlike the case with UV spectra, IR intensities are rarely actually measured; rather, one usually simply visually classifies a band as strong, medium, etc., by comparison with the strongest band in the spectrum. An idea of the reliability of SE frequencies and intensities is given by the IR spectra in Figs 6.5–6.8, which compare experimental spectra with semiempirical (AM1 and PM3) and ab initio (MP2/6-31G*) spectra, for the same four compounds (acetone, benzene, dichloromethane, methanol) shown in Figs 5.33–5.36. The SE spectra are based on the data in Table 6.4; the experimental and MP2 spectra are the ones used in Figs 5.33–5.36. Recall that the MP2/6-31G* IRs of these four compounds do not differ dramatically from the spectra calculated at the HF/3-21G(*) and HF/6-31G* levels. The indication is that SE IR spectra tend to overemphasize the intensities of the strongest bands at the expense of the weaker, with the result that the spectra (after one discards the weakest bands) show fewer bands than experimental or ab initio calculated spectra. Thus if one ignores bands with less than 2% of the intensity of the strongest band (the carbonyl stretch), the AM1 and PM3 spectra of acetone show only carbonyl stretch, while with the 2% cutoff the MP2/6-31G* spectrum has 11 bands and matches the experimental spectrum tolerably well (Fig. 6.5). The semiempirical IRs of benzene (Fig. 6.6) are not bad, but those of dichloromethane (Fig. 6.7) and methanol Fig. 6.8) are also significantly sparser than the experimental and MP2 spectra. Of these four compounds, the SE methods do the best job for benzene, which has only two kind of
Semiempirical Calculations 367