(228k) A Novel Computer-Aided Molecular Design Approach to Design New Non-Intuitive Chemical Admixtures for Cement | AIChE

(228k) A Novel Computer-Aided Molecular Design Approach to Design New Non-Intuitive Chemical Admixtures for Cement

Authors 

Kayello, H. - Presenter, The University of Akron
Visco, D. Jr., The University of Akron
Biernacki, J., Tennessee Technological University
Shlonimskaya, N., Tennessee Technological University
Chaudhari, O., Tennessee Technological University

Cementitious materials are among the broad categories that make up the ceramic industry. Portland cement concrete is the literal foundation of our modern society used in the construction of most buildings, foundations, bridge decks, and pavements. However, the desired performance of those structures is not always attained. In order to control and alter the properties of concrete, an array of chemical admixtures are added to improve performance.

            The task of searching for new admixture molecules for concrete can be a daunting, costly, and lengthy process.  Most of the time, the process involves incrementally permuting an existing molecular scaffold that is known to impart a desired property. This incremental approach involves intuition and expert knowledge, more so than scientific formalisms, and limits the likelihood of discovering next-generation highly active substances. Alternatively, a computer-aided molecular design (CAMD) strategy that uses an inverse quantitative structure property relationship (I-QSPR) is proposed for the design of new chemical admixtures for concrete. The CAMD technique is a powerful tool that applies information about how well certain chemicals perform in a given application, encodes their molecular structure using what is referred to as “molecular descriptors,” relates the descriptors to its performance, then uses that information to generate new chemicals with optimal predicted properties of interest. In this work, the CAMD algorithm was used to identify two different types of chemical admixtures for cement with optimal properties, (1) shrinkage-reducing admixtures (SRAs) and (2) water-reducing admixtures (WRAs).

            SRAs reduce the autogenous and the drying shrinkage of cementitious material. SRAs are nonionic surfactants that are effective at reducing the surface tension of the pore solution of concrete. The I-QSPR approach was employed to identify non-intuitive compounds that were predicted by the QSPR model to be effective at reducing the surface tension of water. Five compounds were then tested for their effect at reducing autogenous and drying shrinkage of cement paste and compared to the effect of two commercially available SRAs. Results for both types of shrinkage indicate that the designed compounds perform similar to commercial admixtures, yet have different chemical functionalities.

            WRAs are added to cementitious material in order to increase flowability. However, a negative side-effect of an increased flowability of the material is an increase of setting time, the time required for cementitious material to stiffen. Accordingly, the I-QSPR algorithm was employed to identify structures with high flowability and controlled set time. As a result, over 670 structures with predicted optimal flowability and setting time were identified. Six structures were selected and tested for their effect on the flowability and the setting time of cement paste. Experimental results show the power of the CAMD strategy at identifying novel and non-intuitive structures capable of increasing flowability, but at the time, have controlled setting time of the cement paste.

Topics