SBIR-STTR Award

Interference of unburned and activated carbon in fly ash with air-entraining admixtures (AEA’s) in fresh concrete mixtures is a major concern in the concrete industry. Therefore, a rapid and accurate measurement of adsorption capacity of fly ash is of great interest to this industry. In this project, a new method is suggested, which can qualitatively and quantitatively measure different surfactants and air-entraining admixtures (AEA’s) adsorbed on fly ash in concrete. Various surfactants (AEA’s) with different fluorescence emission wavelengths and absorbance wavelengths will be demonstrated. By regression analysis of concentrations of various surfactants (AEA’s) to fluorescence and absorbance intensity, new mathematical models of air-entraining admixtures vs. fluorescence intensity or absorbance intensity will be established. Excellent performance of the new method, including large linear range of air-entraining admixture concentration, high sensitivity and selectivity, good repeatability and accuracy, will be confirmed.

Interference of unburned and activated carbon in fly ash with air-entraining admixtures (AEAs) in fresh concrete mixtures is a major concern in the concrete industry. Therefore, a rapid and accurate measurement of adsorption capacity of fly ash is of great interest to this industry. In Phase I, a new method was developed and shown to have the ability to qualitatively and quantitatively measure different surfactants and air-entraining admixtures (AEAs) adsorbed on fly ash in concrete. Various surfactants with different fluorescence emission wavelengths and absorbance wavelengths were evaluated and characterized. By regression analysis of concentrations of various AEAs to fluorescence and/or absorbance intensity, new mathematical models of air-entraining admixtures vs. fluorescence intensity or absorbance intensity were established. Excellent performance of the new method, including large linear range of air-entraining admixture concentration, good sensitivity and selectivity, good repeatability and accuracy, were confirmed. Phase II will further improve this method in terms of sensitivity and overall performance by building a semi-automated instrument with programmable liquid handling capabilities to remove human error and improve data accuracy. The instrument will then be used to establish a database of various AEAs and will be used to identify unknown AEAs and predict their fly ash adsorption capacity.