Computational chemistry is the branch of theoretical chemistry whose major goals are to create efficient computer programs that calculate the properties of molecules (such as total energy, dipole moment, vibrational frequencies) and to apply these programs to concrete chemical objects. It is also sometimes used to cover the areas of overlap between computer science and chemistry.
In theoretical chemistry chemists and physicists together develop algorithms and computer programs to allow precise predictions of atomic and molecular properties and/or reaction paths for chemical reactions. Computational chemists in contrast mostly "simply" use existing computer programs and methodologies and apply these to specific chemical questions.
There are two different approaches in this:
- computational studies can be carried out in order to find a starting point for a laboratory synthesis;
- computational studies can be used to explore the reaction mechanisms and explain observations on laboratory reactions.
There are several major areas within this topic:
- The computational representation of atoms and molecules
- Approaches to storing and searching data on chemical entities (Chemical database)
- approaches to identifying patterns and relationships between chemical structures and their properties (QSPR, QSAR)
- the theoretical elucidation of structure based on simulation of forces
- computational approaches to help in the efficient synthesis of compounds
- computational approaches to design molecules that interact in specific ways with other molecules, especially in drug design
The programs used in computational chemistry are based on many different quantum-chemical methods that solve the molecular Schrödinger equation. The methods that do not include empirical or semi-empirical parameters in their equations are called ab initio methods. The most popular classes of ab initio methods are: Hartree-Fock, Moller-Plesset perturbation theory , configuration interaction , coupled cluster, reduced density matrices and density functional theory. Each class contains several methods that use different variants of the corresponding class, typically geared either to calculating a specific molecular property, or, to application to a special set of molecules. The abundance of these approaches shows that there is no single method suitable for all purposes.
It is, in principle, possible to use one exact method (for example, full configuration interaction ) and apply it to all the molecules, but, although such methods are well-known and available in many programs, the computational cost of their use grows factorially (even faster than exponentially) in the number of electrons that the molecule has. Therefore a great number of approximate methods strive to achieve the best trade-off between accuracy and computational cost. Presently computational chemistry can routinely and very accurately calculate the properties of the molecules that contain no more than, say, 10 electrons. The treatment of molecules that contain a few dozen electrons is practically feasible only by more approximate methods, such as DFT.
There is some dispute within the field on whenether the latter methods are sufficient to accurately describe complex chemical reactions, such as those in biochemistry.
A number of software packages that are self-sufficient and include many quantum-chemical methods are available. Among the most widely used are:
- PLATO (Package for Linear Combination of Atomic Orbitals)
- David C. Young, Computational Chemistry, 2001
- Computational Chemistry List
- Journal of Computational Chemistry
- Center for Computational Chemistry
- NIST Computational Chemistry Comparison and Benchmark DataBase - Contains a database of thousands of computational results for hundreds of molecules
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