Expert system chemicals

In chemistry and chemical engineering, expert systems are used for various tasks ranging from laboratory automation or reaction kinetics to the design of syntheses or the simulations of processes [24]. The application of expert systems in chemistry is described in more detail in Chapter IX, Section 2 of the Handbook,... 

G. Schembecker, Chemical Engineering Expert Systems, in Encyclopedia cf Computational Chemistry, P.v.R. Schleyer, N. L. AlUnger, T. Clark,... 

Another step in laboratory automation to be achieved is the conversion of standard chemical procedures such as titrations or thermal gravimetric analysis, into unit laboratory operations. A procedure could then be selected from these laboratory operations by an expert system and translated by the system to produce a set of iastmctions for a robot. The robot should be able to obey specific iastmctions, such as taking a specified sample aliquot and titrating it using a specified reagent. 

Evidence of the appHcation of computers and expert systems to instmmental data interpretation is found in the new discipline of chemometrics (qv) where the relationship between data and information sought is explored as a problem of mathematics and statistics (7—10). One of the most useful insights provided by chemometrics is the realization that a cluster of measurements of quantities only remotely related to the actual information sought can be used in combination to determine the information desired by inference. Thus, for example, a combination of viscosity, boiling point, and specific gravity data can be used to a characterize the chemical composition of a mixture of solvents (11). The complexity of such a procedure is accommodated by performing a multivariate data analysis. 

As computing capabiUty has improved, the need for automated methods of determining connectivity indexes, as well as group compositions and other stmctural parameters, for existing databases of chemical species has increased in importance. New naming techniques, such as SMILES, have been proposed which can be easily translated to these indexes and parameters by computer algorithms. Discussions of the more recent work in this area are available (281,282). SMILES has been used to input Contaminant stmctures into an expert system for aquatic toxicity prediction by generating LSER parameter values (243,258). 

J. P. Hickey, A. Aldridge, D. R. May Passino, A. M. Frank, Expert System Predicts Aquatic Toxicityfrom Contaminant Chemical Structure,NMoa-A Fisheries Research Center-Great Lakes, U.S. Fish and Wildlife Service, Ann Arbor, Mich., 1991 Ibid., Drug Information Journal 26, 487 (1992). 

Ramanathan, P, S. Kannan, and J.F. Davis, Use Knowledge-Based-System Programming Toolkits to Improve Plant Trouhleshooting, Chemical Engineeiing Piogiess, June 1993, 75-84. (Expert system approach)... 

In the first stages of the development of an Action plan all control options are considered. In the case of lakes, this process is aided by a PC-based expert system , PACGAP, which looks at the physical and chemical characteristics of the lake to determine the most likely option for control. Once further, more detailed information has been collected on the lake s nutrient inputs and other controlling factors, amore complex interactive model can be used (Phytoplankton Response To Environmental CHange, PROTECH-2) to define the efficacy of proposed control options more accurately. This model is able to predict the development of phytoplankton species populations under different nutrient and stratification regimes. 

CCPS G-36. Expert Systems in Process Safety. American Institute of Chemical Engineers, Center for Chemical Process Safety, New York. 

Timberlake, D. L., and R. Govind (1994). Expert System for Solvent Substitution. Preprints of Papers Presented at the ZOSth ACS National Meeting, August 21-25,1994, Washington, DC, 215-217. Center for Great Lakes Studies, University of Wis-consin-Milwaukee, Milwaukee, WL Division of Environmental Chemistry, American Chemical Society. 

An expert system, named "GlovES+," has been written to provide reliable selections of chemical protective clothing for a wide variety of chemicals. The system conducts "intelligent searches" which emulate a human expert s decision path in evaluating a large database from an electronic publication by Forsberg. 

Nevertheless, professional industrial hygienists are called upon routinely to select protective clothing that will provide an adequate, if not absolute, level of protection, even when permeation data are not available for a specific chemical/polymer combination. Their task is formidable. It is also a task that can be performed more easily with the assistance of an expert system. 

KEITH ET AL. Expert System for Selecting Chemical Protective Clothing... 

For convenience of searching for information on similar compounds, chemicals are grouped under 80 chemical classes. These same classes are used with the expert system. Synonyms for many of the compounds are also included where it is likely that the synonym might simplify searching. These same synonyms are also used in the expert system. 

The need for rapidly accessible estimation of toxicity has led to the development of software and other algorithms that will generate estimations of toxicity, usually for organic compounds [79] such methodology is termed an expert system, which has been defined [34] as any formalised system, not necessarily computer-based, which enables a user to obtain rational predictions about the toxicity of chemicals. Essentially, expert systems fall into two classes— those relying on statistical approaches and those based on explicit rules derived from human knowledge. 

Smithing MP, Darvas F. Hazardexpert an expert system for predicting chemical toxicity. In Finlay JW, Robinson SF, Armstrong DJ, editors, Food safety assessment. Washington DC American Chemical Society, 1992. p. 191-200. 

As an example, consider the automation efforts for chemical laboratories in the last decades. Chemical laboratories of today are equipped with instruments that, in principle, can run automatically for 24 hours a day. This results in a higher productivity, since more samples can be analysed with an equal technical effort. Decisions about the analysis itself, how many and which samples must be analysed with what method or technique, etc., are still the responsibility of the laboratory personnel. Since experience can be incorporated into expert systems, they can provide significant benefits as decision-supporting tools. Therefore, the main ideas of expert systems and their development are explained in this chapter. More detailed information can be found in the numerous textbooks on expert systems [7-10]. 

A designer should consult with experts to interpret data from chemical compatibility tests. To meet this need, U.S. EPA developed a software system called Flexible Membrane Liner Advisory Expert System (FLEX) to assist in evaluating test data. FLEX is an expert system that is based on data from many chemical compatibility tests and contains interpretations from experts in the field. 

Wehrens R (1994) Hybridisation of expert systems in chemometrics. In LMC Buydens, WJ Meissen (eds) Chemometrics. Exploring and exploiting chemical information. Katholieke Universiteit Nijmegen, p 113... 

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