Investigation of effect of temperature and size on the ionization potential of semiconductor clusters using effective stochastic potential method

Knowledge of the ionization potential (IP) give important chemical insights into electron-attachment and electron-detachment processes. For semiconductor cluster and nanoparticles, the effect of structure on IP is extremely important because of the quantum confinement effect. However, traditional methods for calculating IPs become computationally expensive for the determination of non-zero temperature ensemble-averaged properties which require the calculation of a large number of structures. This presentation will present the ESP-GF method which combines the effective-stochastic potential (ESP) method with 1-particle Green’s function theory for efficient calculation of the ionization potential to obtain ensemble-averaged properties at non-zero temperatures. The ESP method uses random-matrix theory to describe the distribution of structures present in the NVT ensemble which allows an efficient calculation of IPs. The ESP-GF method has been applied to a series of colloidal ZnSe clusters at T=300K and the distributions of IPs will be presented. The results from this project highlight the importance of performing ensemble-averaged calculations for predicting quasiparticle properties in semiconductor clusters.