Polymer property modelling using grid technology for design of structured products
Chemical Product Design and Engineering (CPD&E)
Chemical Product Design & Engineering - II (CPD&E - 2)
Keywords: polymers, grid, connectivity, groups, properties
To satisfy consumer and regulatory demands, chemical and pharmaceutical industries continuously must focus on developing and producing improved/modified products.
Previous trial-and-error methodologies to produce new products, with specific desired properties, are not feasible as these are capital intensive, time-consuming and difficult to automate. Computer-aided molecular design (CAMD) methods, can partially replace these in determining molecular structures matching specific sets of target properties. Extending CAMD techniques for identifying macromolecular (here polymers) structures having a set of target properties, requires new property models. Developing new property models for predicting polymer properties based on the analysis of polymer structure is the main objective of this paper.
The approach involves inductive learning: Experimental data are collected, a property model is derived from the data set and finally the properties are predicted using the developed model.
Polymer property modeling involves both linear and non-linear models. When modeling several properties, time taken for parameter estimation increases proportionately with the number of properties modeled. Grid technology greatly facilitates this work as different property models (based on either group contributions, connectivity indices or other methods) can be generated in parallel. In this work, we present a suite of new polymer property models based on groups and atomic contributions. These models are more suitable for computer-aided polymer design algorithms than their predecessors. A comparison of the time required for generating the models in series and in parallel, using grid technology is also presented in this paper.
The models in this work are developed for volumetric properties, glass transition temperature, solubility parameter, optical properties and electrical properties. In order to validate these developed models for accuracy, a comparison between predicted properties using these models, experimental results and other literature models such as Van Krevelen’s models and Biceranos models is made.
See the full pdf manuscript of the abstract.
Presented Wednesday 19, 16:20 to 16:40, in session Chemical Product Design & Engineering - II (CPD&E - 2).
