Instructor:
Luis A. Montero
Teaching Fellow:
[ luis.montero@quimica.uh.cu
; imtvi06@gmail.com
]
Semion K. Saikin [ saykin@fas.harvard.edu
, phone: (617)496-8221]
Class Meeting Time: Tu/Th, 10:00 – 11:30
Location: Mallinkrodt 217
Main References:
Lecture notes and additional references will be provided and will be made available for download from the appropriate websites through the Universidad de La Habana and the mirror at Universidad Autónoma de
Madrid: http://karin.fq.uh.cu/~lmc/modeling_matter_at_nanoscales and http://habana.qfa.uam.es/~lmc/modeling_matter_at_nanoscales .
Some books serve as consulting material like:
1. Cramer, C. J., Essentials of Computational Chemistry. Theories and Models. 2nd. ed.; John Wiley & Sons
Ltd: Chichester, 2004; p 596.
2.
3.
Jensen, F., Introduction to Computational Chemistry. John Wiley & Sons: Chichester, 1999; p 429.
Streitwieser, A., Molecular Orbital Theory for Organic Chemists. John Wiley & Sons: New York, 1961; p
489.
4. Szabo, A.; Ostlund, N. S., Modern quantum chemistry: introduction to advanced electronic structure
theory. First edition, revised ed.; McGraw-Hill: New York, 1989; p 466.
Course Overview:
The course allows students to become familiar with the essentials of modeling the structure of matter at nanoscales and the depending properties, as well as the way that they relate with measurements at human scales. Concepts on modeling, computer representation of nanosystems, origin of interactions between bodies at nanoscales and the different ways of finding the corresponding potential energy surfaces, including both classical and quantum mechanical procedures are described and even detailed when relevant. It is intended for advanced undergraduate students in Chemistry, Physics, Biology, Pharmacy and Biochemistry. It can be also useful for graduate students in the same fields, as well as physicians and engineers. Attendants must handle an essential ground in Mathematics, general Physics and Chemistry and related matters.
Grading Policy:
Class discussions:
Midterm:
Final:
30 % (participation in discussion/review of relevant research literature)
30 % (~3 page literature review on a selected theme)
40 % (Exam)

Lecture Outline:
1. Introduction and overview. Sizes and scales in nature. Models and modeling the nanoworld. Representation of polyatomic systems on computers. Potential energy surfaces (PES) at nanoscales and its physical basis.
2. Energy of molecular processes. Physical nature of molecular interactions. Perturbative description and contributions of the most important terms to PES’s.
3. Empirical classical PES and typical procedures of optimization.
A.
Classical potentials for the different types of interaction and most common functional forms.
B.
Optimization via energy gradients. Monte Carlo procedures.
C.
Molecular dynamics for the evaluation of minimums, stationary interactions and the evolution of free energies.
4. Introduction to quantum treatments.
A.
Remembrance of the principles and the method of quantum mechanics.
B.
The theorem of the variations. Obtaining eigenvalues and eigenvectors of a system.
5. The theory of molecular orbitals for the description of nanosystems (part I).
A.
Hückel Molecular Orbitals of conjugated systems.
B.
Extended Hückel theory.
6. The theory of molecular orbitals for the description of nanosystems (part II).
A.
The Hartree-Fock method applied to polyatomic systems.
B.
Ab initio procedures.
C.
Basis functions.
D.
Basis set superposition error. Pseudopotentials and the case of heavy atoms. Total energy and zeropoint energy.
7. Methods to correct correlation in Hartree-Fock energy.
A.
Perturbative methods.
B.
Configuration interaction. Multiconfigurational methods. Principles of the coupled cluster method and its application.
8. Semiempirical and approximate Hamiltonians. Best-known semiempirical and approximate Hamiltonians: advantages and limitations. Applications.
9. Application of density functional theory.
A.
The ground concept and theory of density functionals for nanosystems. Simplification of Kohn-Sham.
B.
Working interpretation of results. Most used functionals. Applications.
10. Applications.
A.
Most common programs and their use in different computing environments.
B.
Interpretation of results for molecular geometries, electronic, vibrational and nuclear magnetic resonance spectra.
C.
Some application of electron density calculations. Hybrid quantum mechanics with classical methods.

D.
Molecular modeling of chemical reactions: transition states and reaction pathways by internal coordinates.
E.
Statistic approaches to molecular interactions and the role of entropy.