- •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
38 |
Computational Chemistry |
|
The |
structure has two degrees of freedom: a bond length (the two bonds are the |
|
same length) and a bond angle. The |
structure has three degrees of freedom: two |
bond lengths and a bond angle. The optimization algorithm has more variables to cope with in the case of the lower-symmetry structure. A moderately high-level geometry
optimization and frequencies job on |
dimethyl ether, took 5.7 min, but |
|
on the |
ether 6.8 min (actually, small molecules like water, and low-level calcula- |
tions, show a levelling effect, taking only seconds and requiring about the same time regardless of symmetry).
What do we mean by a better geometry ? Although a successful geometry optimization will give essentially the same geometry from a slightly distorted input structure as from one with the perfect symmetry of the molecule in question, corresponding bond lengths and angles (e.g. the four C–H bonds and the two HCH angles of ethene) will not be exactly the same. This can confuse an analysis of the geometry, and carries over into the calculation of other properties like, say, charges on atoms – corresponding atoms should have exactly the same charges. Thus both esthetic and practical considerations encourage us to aim for the exact symmetry that the molecule should possess.
2.7SUMMARY OF CHAPTER 2
The PES is a central concept in computational chemistry. A PES is the relationship – mathematical or graphical – between the energy of a molecule (or a collection of molecules) and its geometry.
Stationary points on a PES are points where |
for all where |
is a geomet- |
||
ric parameter. The stationary points of chemical interest are minima |
|
|||
for all |
and transition states or first-order saddle points; |
|
for one |
|
along the reaction coordinate (IRC), and |
for all other |
Chemistry is the study of |
||
PES stationary points and the pathways connecting them. |
|
|
||
The |
Born–Oppenheimer approximation |
says that in a |
molecule the |
nuclei are |
essentially stationary compared to the electrons. This is one of the cornerstones of computational chemistry because it makes the concept of molecular shape (geometry) meaningful, makes possible the concept of a PES, and simplifies the application of the Schrödinger equation to molecules by allowing us to focus on the electronic energy and add in the nuclear repulsion energy later.
Geometry optimization is the process of starting with an input structure “guess” and finding a stationary point on the PES. The stationary point found will normally be the one closest to the input structure, not necessarily the global minimum. A transition state optimization usually requires a special algorithm, since it is more demanding than that required to find a minimum. Modern optimization algorithms use analytic first derivatives and (usually numerical) second derivatives.
It is usually wise to check that a stationary point is the desired species (a minimum or a transition state) by calculating its vibrational spectrum (its normal-mode vibrations). The algorithm for this works by calculating an accurate Hessian (force constant matrix) and diagonalizing it to give a matrix with the “direction vectors” of the normal modes, and a diagonal matrix with the force constants of these modes. A procedure of “mass- weighting” the force constants gives the normal-mode vibrational frequencies. For a
The Concept of the Potential Energy Surface 39
minimum all the vibrations are real, while a transition state has one imaginary vibration, corresponding to motion along the reaction coordinate. The criteria for a transition state are appearance, the presence of one imaginary frequency corresponding to the reaction coordinate, and an energy above that of the reactant and the product. Besides serving to characterize the stationary point, calculation of the vibrational frequencies enables one to predict an IR spectrum and provides the ZPE. The ZPE is needed for accurate comparisons of the energies of isomeric species. The accurate Hessian required for calculation of frequencies and ZPE’s can be obtained either numerically or analytically (faster, but much more demanding of hard drive space).
REFERENCES
[1](a) S. S. Shaik, H. B. Schlegel, and S. Wolfe, “Theoretical Aspects of Physical Organic
Chemistry: the Mechanism,” Wiley, New York, 1992. See particularly Introduction and chapters 1 and 2. (b) R. A. Marcus, Science, 1992, 256, 1523. (c) For a very abstract and mathematical but interesting treatment, see P. G. Mezey, “Potential Energy Hypersurfaces,” Elsevier, New York, 1987. (d) J. I. Steinfeld, J. S. Francisco, and W. L. Hase, “Chemical Kinetics and Dynamics,” 2nd edn., Prentice Hall, Upper Saddle River, New Jersey, 1999.
[2] I. N. Levine, “Quantum Chemistry,” 5th edn., Prentice Hall, Upper Saddle River, NJ, 2000, section 4.3.
[3]Reference [1a], pp. 50–51.
[4]K. N. Houk, Y. Li, and J. D. Evanseck, Angew. Chem. Int. Ed. Engl., 1992, 31, 682.
[5]P. Atkins, “Physical Chemistry,” 6th edn, Freeman, New York, 1998, pp. 830–844.
[6]R. Marcelin, Annales de Physique, 1915, 3, 152. Potential energy surface: p. 158.
[7]H. Eyring, J. Chem Phys., 1935, 3, 107.
[8]H. Eyring and M. Polanyi, Z. Physik Chem., 1931, B, 12, 279.
[9]M. Born and J. R. Oppenheimer, Ann. Physik., 1927, 84, 457.
[10]A standard molecular surface, corresponding to the size as determined experimentally (e.g. by X-ray diffraction) encloses about 98 per cent of the electron density. See e.g. R. F. W. Bader, M. T. Carroll, M. T. Cheeseman, and C. Chang, J. Am. Chem. Soc., 1987, 109, 7968.
[11]For some rarefied but interesting ideas about molecular shape see P. G Mezey, “Shape in Chemistry,” VCH, New York, 1993.
[12]X. K. Zhang, J. M. Parnis, E. G. Lewars, and R. E. March, Can. J. Chem., 1997, 75, 276.
[13]See e.g. (a) A. R. Leach, “Molecular Modelling. Principles and Applications,” Longman, Essex, UK, 1996, chapter 4. (b) F. Jensen, “Introduction to Computational Chemistry,” Wiley, New York, 1999, chapter 14.
[14]W. J. Hehre, “Practical Strategies for Electronic Structure Calculations,” Wavefunction Inc., Irvine, CA, 1995, p. 9.
[15]I. N. Levine, “Quantum Chemistry,” 5th edn, Prentice Hall, Upper Saddle River, NJ, 2000, p. 65.
[16]A. P. Scott and L. Radom, J. Phys. Chem., 1996, 100, 16502.
[17]J. B. Foresman and Æ. Frisch, “Exploring Chemistry with Electronic Structure Methods,” 2nd edn., Gaussian Inc., Pittsburgh, PA, 1996, pp. 173–211.
40 Computational Chemistry
[18]P. Atkins, “Physical Chemistry,” 6th edn, Freeman, New York, 1998, chapter 15.
[19]I. N. Levine, “Quantum Chemistry,” 5th edn, Prentice Hall, Upper Saddle River, NJ, 2000, chapter 12.
EASIER QUESTIONS
1.What is a PES (give the two viewpoints)?
2.Explain the difference between a relaxed PES and a rigid PES.
3.What is a stationary point? What kinds of stationary points are of interest to chemists, and how do they differ?
4.What is a reaction coordinate?
5.Show with a sketch why it is not correct to say that a transition state is a maximum on a PES.
6.What is the Born-Oppenheimer approximation, and why is it important?
7.Explain, for a reaction how the potential energy change on a PES is related to the enthalpy change of the reaction. What would be the problem with calculating a free energy/geometry surface?
Hint: Vibrational frequencies are normally calculated only for stationary points.
8.What is geometry optimization? Why is this process for transition states (often called transition state optimization) more challenging than for minima?
9.What is a Hessian? What uses does it have in computational chemistry?
10.Why is it usually good practice to calculate vibrational frequencies where practical, although this often takes considerably longer than geometry optimization?
HARDER QUESTIONS
1.The Born–Oppenheimer principle is often said to be a prerequisite for the concept of a PES. Yet the idea of a PES (Marcelin, 1915) predates the Born–Oppenheimer
principle (1927). Discuss.
2.How high would you have to lift a mole of water for its gravitational potential energy to be equivalent to the energy needed to dissociate it completely into hydroxyl
radicals and hydrogen atoms? The strength of the O–H bond is about the gravitational acceleration g at the Earth’s surface (and out to hundreds of km) is about What does this indicate about the role of gravity in chemistry?
3.If gravity plays no role in chemistry, why are vibrational frequencies different for, say, C–H and C–D bonds?
4.We assumed that the two bond lengths of water are equal. Must an acyclic molecule have equal A–B bond lengths? What about a cyclic molecule
5.Why are chemists but rarely interested in finding and characterizing second-order and higher saddle points (hilltops)?
6.What kind(s) of stationary points do you think a second-order saddle point connects?
7.If a species has one calculated frequency very close to what does that tell you about the (calculated) PES in that region?
The Concept of the Potential Energy Surface 41
8.The ZPE of many molecules is greater than the energy needed to break a bond;
e.g. the ZPE of hexane is about while the strength of a C–C or a C–H bond is only about Why then do such molecules not spontaneously decompose?
9.Only certain parts of a PES are chemically interesting: some regions are flat and featureless, while yet other parts rise steeply and are thus energetically inaccessible. Explain.
10.Consider two PESs for the A, a plot of energy vs. the H–C bond length, and B, a plot of energy vs. the HCN angle. Recalling that HNC is the higher-energy species (Fig. 2.19), sketch qualitatively the diagrams A and B.
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