Computer software prediction

The choice of variables remaining with the operator, as stated before, is restricted and is usually confined to the selection of the phase system. Preliminary experiments must be carried out to identify the best phase system to be used for the particular analysis under consideration. The best phase system will be that which provides the greatest separation ratio for the critical pair of solutes and, at the same time, ensures a minimum value for the capacity factor of the last eluted solute. Unfortunately, at this time, theories that predict the optimum solvent system that will effect a particular separation are largely empirical and those that are available can be very approximate, to say the least. Nevertheless, there are commercially available experimental routines that help in the selection of the best phase system for LC analyses, the results from which can be evaluated by supporting computer software. The program may then suggest further routines based on the initial results and, by an iterative procedure, eventually provides an optimum phase system as defined by the computer software. 

Predictive human error analysis can be performed manually or by means of a computer software package. Three types of analysis are possible within PHEA. 

The use of the electrostatic potential in analyzing and predicting molecular interactive behavior and properties has increased remarkably over the past 25 years. In 1980, it was still reasonable to hope to at least mention, in one lengthy review chapter (Politzer and Daiker 1981), all of the papers that had been published in this area. In 1996, such an objective would be ridiculous. This popularity can be attributed to (a) the insight that V(r) can provide, especially into noncovalent interactions, and (b) the widespread availability of computational software packages of which it has become a standard feature. 

Within the past few years the advances made in hydrocarbon thermodynamics combined wtih increased sophistication in computer software and hardware have made it quite simple for engineers to predict phase equilibria or simulate complex fractionation towers to a high degree of accuracy through software systems such as SSI s PROCESS, Monsanto s FLOWTRAN, and Chemshare s DISTILL among others. This has not beem the case for electrolyte systems. 

In developing the thermodynamic framework for ECES, we attempted to synthesize computer software that would correctly predict the vapor-liquid-solid equilibria over a wide range of conditions for multicomponent systems. To do this we needed a good basis which would make evident to the user the chemical and ionic equilibria present in aqueous systems. We chose as our cornerstone the law of mass action which simply stated says "The product of the activities of the reaction products, each raised to the power indicated by its numerical coefficient, divided by the product of the activities of the reactants, each raised to a corresponding power, is a constant at a given temperature. ... 

Expert systems represent a branch of artificial intelligence that has received enormous publicity in the last two to three years. Many companies have been formed to produce computer software for what is predicted to be a substantial market. This paper describes what is meant by the term expert system and the kinds of problems that currently appear amenable to solution by such systems. The physical sciences and engineering disciplines are areas for application that are receiving considerable attention. The reasons for this and several examples of recent applications are discussed. The synergism of scientists and engineers with machines supporting expert systems has important implications for the conduct of chemical research in the future some of these implications are described. 

Increasing attention is being given to developing methods to predict failure rate data for process equipment and systems. Such methods are beginning to appear in published literature. These methods include correlations, factored estimation procedures, and analogies to predict equipment failure rates. They are desirable because they offer efficient means of providing equipment failure rate data for risk assessments, and they can be conveniently incorporated into computer software. 

One author (Reinhardt, Chapter 2) predicts that, over the next several decades, pharmaceutical research will increasingly shift from Europe and the United States to Asia, where many of these newly industrialized countries are located, as has manufacturing in many other industries, ranging from motor vehicles to electronics to computer software. 

Therefore, similar to the attempts made to estimate vapor pressure (Section 4.4) there have been a series of quite promising approaches to derive topological, geometric, and electronic molecular descriptors for prediction of aqueous activity coefficients from chemical structure (e.g., Mitchell and Jurs, 1998 Huibers and Katritzky, 1998). The advantage of such quantitative structure property relationships (QSPRs) is, of course, that they can be applied to any compound for which the structure is known. The disadvantages are that these methods require sophisticated computer software, and that they are not very transparent for the user. Furthermore, at the present stage, it remains to be seen how good the actual predictive capabilities of these QSPRs are. 

INFORMATION SOURCES FOR SOFTWARE FOR COMPUTER-AIDED PREDICTION OF TOXICITY METHODS... 

For optimising two parameters at a time, one of the simplest, and easy to use computer software packages is DryLab, produced and marketed by LC Resources. Data from just two runs is used to predict both isocratic and gradient conditions. Usually the two runs are gradients in which the % organic component in the mobile phase is varied with time. The peak... 

In silico models (or expert systems ) have also been developed. These are computer software-based structure-activity relationship and quantitative structure-activity relationship analyses of data libraries of acute toxicity data developed for use in evaluating and predicting the acute oral and inhalation toxicity potential of a chemical or drug. 

Kostka, T., Selzer, P., and Gasteiger, J., Computer-Assisted Prediction of the Degradation Prodncts and Infrared Spectra of s-Triazine Herbicides, in Software-Entwicklung in der Chemie 11, Eels, G. and Schubert, V., Eds., Gesellschaft Deutscher Chemiker, Frankfnrt/Main, 1997, 227. 

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