Models computational chemistry

Keywords nanostructure, aquatic ion of hydrogen, proton conduction, computational chemistry, modeling... 

Sauer J (1997) Preprints Symp Adv and Appl Computational Chemistry Modeling, San Francisco, USA,April 13-17,1997,Am Chem Soc, Washington DC, 1997,42 53... 

Recently, there have been a number of studies using computational chemistry techniques to model macromolecules of kerogens (Faulon et al. 1990), coals (Carlson 1992 Nakamura 1993 Murata et al. 1993 Faulon et al. 1994), asphaltenes (Murgich et al. 1996 Kowalewski et al. 1996 Diallo et al. 1998), wood and lignin (Faulon 1994, 1995 Faulon and Hatcher 1994), and biomarkers (Peters et al. 1996 Peters 2000). Computational chemistry models have been used to predict a variety of physical and chemical properties, such as the density of coals (Nakamura et al. 1993 Murata et al. 1993), the microporosity of coals (Faulon 1994, 1995), and the self-association of asphaltenes and resins (Murgich et al. 1996 Subramanian and Sheu 1997 Zajac et al. 1997). Oil companies and petroleum research organizations are interested in compositional and structural chemistry of these macromolecules because of its potential for solving both upstream and downstream problems. 

There is also commercial confidence in the use of computational chemistry models in materials chemistry— modelling is one of the R D core competences of Johnson Matthey [12], for example, a specialty chemicals company that has recently been enjoying considerable commercial success with a +20 % increase in revenue for the year 2011-2012 [13]. 

Both approaches have difficulty with surpassing the grid computing idea. The Fold-ing home project created perhaps the most powerful computational device ever, and attracted many young people to science (Pande et al. 2003). HopefuUy, aU these computational chemistry modeling efforts will bring us a better understanding of nature and a better lives for all people. 

Quack M and Troe J 1998 Statistical adiabatic channel model Encyclopedia of Computational Chemistry vo 4, ed P von Rague Schleyer et a/(New York Wiley) pp 2708-26... 

C.J. Cramer, Essentials of Computational Chemistry - Theories and Models, Wiley, Chichester, 2002. 

There is a lot of confusion over the meaning of the terms theoretical chemistry, computational chemistry and molecular modelling. Indeed, many practitioners use all three labels to describe aspects of their research, as the occasion demands "Theoretical chemistry is often considered synonymous with quantum mechanics, whereas computational chemistry encompasses not only quantum mechanics but also molecular mechaiucs, minimisation, simulations, conformational analysis and other computer-based methods for understanding and predicting the behaviour of molecular systems. Molecular modellers use all of these methods and so we shall not concern ourselves with semantics but rather shall consider any theoretical or computational tecluiique that provides insight into the behaviour of molecular systems to be an example of molecular modelling. If a distinction has to be... 

Frisch M J, G W Trucks and J R Cheeseman 1996. Systematic Model Chemistries Based on Density Functional Theory Comparison with Traditional Models and with Experiment. Theoretical and Computational Chemistry (Recent Developments and Applications of Modem Density Functional Theory) 4 679-707. 

Price S L 2000. Towards More Accurate Model Intermolecular Potentials for Organic Molecules. Ii Lipkowitz K B and D B Boyd (Editors). Reviews in Computational Chemistry Volume 14. Nev York, VCH Publishers, pp. 225-289. 

Cox S R and D E Williams 1981. Representation of the Molecular Electrostatic Potential by a New Atomic Charge Model. Journal of Computational Chemistry 2 304-323. 

Ferguson D M 1995. Parameterisation and Evaluation of a Flexible Water Model. Journal of Computational Chemistry 16 501-511. 

Kurst G R, R A Stephens and R W Phippen 1990. Computer Simulation Studies of Anisotropic iystems XIX. Mesophases Formed by the Gay-Berne Model Mesogen. Liquid Crystals 8 451-464. e F J, F Has and M Orozco 1990. Comparative Study of the Molecular Electrostatic Potential Ibtained from Different Wavefunctions - Reliability of the Semi-Empirical MNDO Wavefunction. oumal of Computational Chemistry 11 416-430. 

Price S L, R J Harrison and M F Guest 1989. An Ab Initio Distributed Multipole Study of the Electrostatic Potential Around an Undecapeptide Cyclosporin Derivative and a Comparison with Point Charge Electrostatic Models. Journal of Computational Chemistry 10 552-567. 

A chemist must realize that theories, models, and approximations are powerful tools for understanding and achieving research goals. The price of having such powerful tools is that not all of them are perfect. This may not be an ideal situation, but it is the best that the scientihc community has to offer. Chemists are advised to develop an understanding of the nature of computational chemistry approximations and what results can be trusted with any given degree of accuracy. 

Computational chemistry is used in a number of different ways. One particularly important way is to model a molecular system prior to synthesizing that molecule in the laboratory. Although computational models may not be perfect, they are often good enough to rule out 90% of possible compounds as being unsuitable for their intended use. This is very useful information because syn-... 

As computational chemistry has become easier to use, professional computational chemists have shifted their attention to more difficult modeling problems. No matter how easy computational chemistry becomes, there will always be problems so difficult that only an expert in the field can tackle them. 

A. R. Leach Molecular Modelling Principles and Applications Longman, Essex (1996). T. Clark, A Handbook of Computational Chemistry John Wiley Sons, New York (1985). 

This section provides a brief discussion of technical issues pertaining to modeling organic molecules. The bibliography focuses on pertinent review literature. Many computational chemistry methods can be applied to organic molecules. However, there are a few caveats to note as discussed here. 

To ensure that computational chemistry develops in an orderly way, researchers must provide certain information so that others can reproduce and analyze their results. Gund et al. proposed guidelines for reporting molecular modeling results. You should consider these guidelines for your publications. 

In computational chemistry it can be very useful to have a generic model that you can apply to any situation. Even if less accurate, such a computational tool is very useful for comparing results between molecules and certainly lowers the level of pain in using a model from one that almost always fails. The MM+ force field is meant to apply to general organic chemistry more than the other force fields of HyperChem, which really focus on proteins and nucleic acids. HyperChem includes a default scheme such that when MM+ fails to find a force constant (more generally, force field parameter), HyperChem substitutes a default value. This occurs universally with the periodic table so all conceivable molecules will allow computations. Whether or not the results of such a calculation are realistic can only be determined by close examination of the default parameters and the particular molecular situation. ... 

A tmism of computational chemistry is that chemists will always want to model ever larger systems, or smaller systems, at ever more accurate levels of approximation. The total miming time of jobs has, in general, not lowered dramatically. Computational chemists still perform calculations that take several days to complete. However, today the molecules can be much larger and the quaUty of the calculations better. 

JM Blaney, JS Dixon. Distance geometry m molecular modeling. In KB Lipkowitz, DB Boyd, eds. Reviews m Computational Chemistry, Vol 5. New York VCFl, pp 299-335. 

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