This study aims at demonstrating the application of a microreactor combinatorial system for multiple parameter synthesis of nanoparticles. In order to meet this aim, an automatic system for combinatorial synthesis of CdSe nanoparticles was developed, and more than 3300 datasets were obtained to optimize and understand the effect of reaction parameters on nanoparticle properties. A microreactor was used and programmable equipments were employed for additional speed up. Six reaction condition parameters were systematically combined to produce sets of CdSe nanoparticle synthesis conditions. The 3387 datasets under different reaction conditions, with an average time of 7.5. min were generated and characterized. The total experimental time including data handling analyses is approximately one month. The absorbance, absorption peak wavelength, photoluminescence (PL) peak, and PL full width of half maximum (FWHM) were calculated from each spectrum by using computer-aided processing. Based on the results of several multivariate analyses using the numerous and complicated data, we were able to conclude the following (1) nanoparticle characterization is necessary to establish understanding and control of nanoparticle synthesis and limitations of the reaction system, (2) weighting evaluation method is an efficient way to find the condition for balanced nanoparticle properties, and (3) neural network is an effective tool to analyze data generated from combinatorial synthesis.
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Industrial and Manufacturing Engineering