Statistical Modeling and Analysis for Robust Synthesis of Nanostructures

An effort is made to systematically investigate the best process conditions that ensures synthesis of different types of one dimensional cadmium selenide nanostructures with high yield and reproducibility. Through a designed experiment and rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process robust (i.e., less sensitive) to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. Cadmium Selenide (CdSe) has been found to exhibit one-dimensional morphologies of nanowires, nanobelts and nanosaws, often with the three morphologies being