The optical properties of semiconductor nanocrystals (SC NCs) are largely controlled by their size and surface chemistry, i.e., the chemical composition and thickness of inorganic passivation shells and the chemical nature and number of surface ligands as well as the strength of their bonds to surface atoms. The latter is particularly important for CdTe NCs, which – together with alloyed CdxHg1−xTe – are the only SC NCs that can be prepared in water in high quality without the need for an additional inorganic passivation shell. Aiming at a better understanding of the role of stabilizing ligands for the control of the application-relevant fluorescence features of SC NCs, we assessed the influence of two of the most commonly used monodentate thiol ligands, thioglycolic acid (TGA) and mercaptopropionic acid (MPA), on the colloidal stability, photoluminescence (PL) quantum yield (QY), and PL decay behavior of a set of CdTe NC colloids. As an indirect measure for the strength of the coordinative bond of the ligands to SC NC surface atoms, the influence of the pH (pD) and the concentration on the PL properties of these colloids was examined in water and D2O and compared to the results from previous dilution studies with a set of thiol-capped Cd1−xHgxTe SC NCs in D2O. As a prerequisite for these studies, the number of surface ligands was determined photometrically at different steps of purification after SC NC synthesis with Ellman's test. Our results demonstrate ligand control of the pH-dependent PL of these SC NCs, with MPA-stabilized CdTe NCs being less prone to luminescence quenching than TGA-capped ones. For both types of CdTe colloids, ligand desorption is more pronounced in H2O compared to D2O, underlining also the role of hydrogen bonding and solvent molecules.
Comparing thermal wave function methods for multi-configuration time-dependent Hartree simulations
(2014)
We compare two methods for creating stochastic temperature wave functions that can be used for Multi-Configuration Time-Dependent Hartree (MCTDH) simulations. In the first method, the MCTDH coefficients are chosen randomly, while the other method uses a single Hartree product of random single-particle functions (SPFs). We find that using random SPFs dramatically improves convergence for a model system for surface sticking.