Quantitative Structure-Activity Relationships (QSARs) for Materials Science
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Quantitative Structure-Activity Relationships (QSARs ) for Materials Science Krishna Rajan, Changwon Suh, Arun Rajagopalan and Xiang Li Combinatorial Materials Science and Informatics Laboratory Department of Materials Science & Eng. and Information Technology Program Rensselaer Polytechnic Institute, Troy NY 12180-3590 USA [email protected]
ABSTRACT The field of combinatorial synthesis and “artificial intelligence” in materials science is still in its infancy. In order to develop and accelerated strategy in the discovery of new materials and processes, requires the need to integrate both the experimental aspects of combinatorial synthesis with the computational aspects of information based design of materials. In biology and organic chemistry, this has been accomplished by developing descriptors which help to specify “quantitative structure- activity relationships’ at the molecular level. If materials science is to adopt these strategies as well, a similar framework of “QSARs” is required. In this paper, we outline some approaches that can lay the foundations for QSARs in materials science. INTRODUCTION The concept of structure-property relationships in materials science is usually taken for granted as the foundation on which materials design is based on. Yet it is interesting to note that other disciplines, especially in the biological / pharmacology and drug design areas, have established a formalism which they term as “Quantitative Structure- Activity Relationships “ – QSARs or “Quantitative Structure-Property Relationships” – QSPRs. The exact context of when the terms QSAR and QSPR are to be used can vary among the organic based sciences community but for the purposes of our discussion here, we shall view the two terms as equivalent. The basic functional form for QSARs may be of the form Φ = f (ξ1 ξ2, ξ3.....) where Φ represents the “property” of interest and ξ represents the numerous parameters or “descriptors” associated with that material that appear to have an influence on that property. The QSAR may in fact involve a number of such functions which collectively describe a set of structure –activity relationships. For instance an examples of such a QSAR includes: Estimation of flash points in organic systems [1]
where TFP is the temperature of a flash, TBP is experimental temperature of boiling, RNCG is relative negative [surface] charge and characterizes the dispersion of partial charges in the molecule, HDCA is H-donors charged surface area and represents the sum of solvent-accessible surface area of H-bonding donor atoms. S7.5.1
MATERIALS DESCRIPTORS AND MATERIALS FUNCTIONALITY Many approaches in the engineering design of materials of course take into account the numerous variables that influence the process….resulting in some type of equation very similar to those used in the bioinformatics / organic chemistry field. Such equations are some sort of continuous function which maps the variability of the functionality in terms of parameters such as composition. Some classical examples where the materials s
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