2015 AIChE Annual Meeting Proceedings

(450e) Experiment and Theory to Detect and Predict Ligand Phase Separation on Metallic Nanoparticles

Authors

Steven Merz - Presenter, University of Virginia
Zachary Farrell - Presenter, University of Virginia
Sergei Egorov - Presenter, University of Virginia
David Green - Presenter, University of Virginia

In this work we seek to quantify phase separation in two-ligand monolayers on nanoparticle surfaces through experimental and computational methods.  Nanoparticles are synthesized, using the Farrell-Green Synthesis(Farrell, Shelton, Dunn, & Green, 2013), with a two ligand system consisting of a homologous series of alkanethiols.  Experimentally Matrix Assisted Laser Desorption Ionization (MALDI) is used to determine the ordering of the nanoparticle monolayers.  Computationally, self-consistent mean-field theory (SCF) and molecular simulation are used to predict the expected ligand phase separation of these systems, which can be directly compared to the experimental MALDI spectra. The experimental spectra show a trend of increasing order as the chain length mismatch is increased.  In addition each two-ligand system shows maximum order at or near a concentration of 80% dodecanethiol on the surface.  The computational data agrees well with this trend both quantitatively and qualitatively.  Based on the agreement between experimental and computational results it is expected that the monolayer patterning indicated by the simulations is representative of the experimental monolayer patterning. The computation results allow for a more complete understanding of the type of phase separation that a monolayer experiences and may allow for a way to predict the type and degree of phase separation experienced by other nanoparticle monolayer systems.