Understanding size dependence of phase stability and band gap in CsPbI3 perovskite nanocrystals.

Inorganic halide perovskites CsPbX3 (X = Cl, Br, I) have been widely studied as colloidal quantum dots for their excellent optoelectronic properties. Not only is the long-term stability of these materials improved via nanostructuring, their optical bandgaps are also tunable by the nanocrystal (NC) size. However, theoretical understanding of the impact of the NC size on the phase stability and bandgap is still lacking. In this work, the relative phase stability of CsPbI3 as a function of the crystal size and the chemical potential is investigated by density functional theory. The optically active phases (α- and γ-phase) are found to be thermodynamically stabilized against the yellow δ-phase by reducing the size of the NC below 5.6 nm in a CsI-rich environment. We developed a more accurate quantum confinement model to predict the change in bandgaps at the sub-10 nm regime by including a finite-well effect. These predictions have important implications for synthesizing ever more stable perovskite NCs and bandgap engineering

Atmospheric Circulation of Brown Dwarfs and Jupiter and Saturn-like Planets: Zonal Jets, Long-term Variability, and QBO-type Oscillations

Brown dwarfs and directly imaged giant planets exhibit significant evidence for active atmospheric circulation, which induces a large-scale patchiness in the cloud structure that evolves significantly over time, as evidenced by infrared light curves and Doppler maps. These observations raise critical questions about the fundamental nature of the circulation, its time variability, and the overall relationship to the circulation on Jupiter and Saturn. Jupiter and Saturn themselves exhibit numerous robust zonal (east-west) jet streams at the cloud level; moreover, both planets exhibit long-term stratospheric oscillations involving perturbations of zonal wind and temperature that propagate downward over time on timescales of ~4 years (Jupiter) and ~15 years (Saturn). These oscillations, dubbed the Quasi Quadrennial Oscillation (QQO) for Jupiter and the Semi-Annual Oscillation (SAO) on Saturn, are thought to be analogous to the Quasi-Biennial Oscillation (QBO) on Earth, which is driven by upward propagation of equatorial waves from the troposphere. To investigate these issues, we here present global, three-dimensional, high-resolution numerical simulations of the flow in the stratified atmosphere--overlying the convective interior--of brown dwarfs and Jupiter-like planets. The effect of interior convection is parameterized by inducing small-scale, randomly varying perturbations in the radiative-convective boundary at the base of the model. In the simulations, the convective perturbations generate atmospheric waves and turbulence that interact with the rotation to produce numerous zonal jets. Moreover, the equatorial stratosphere exhibits stacked eastward and westward jets that migrate downward over time, exactly as occurs in the terrestrial QBO, Jovian QQO, and Saturnian SAO. This is the first demonstration of a QBO-like phenomenon in 3D numerical simulations of a giant planet.Comment: 27 pages, 15 figures, in press at ApJ; this is the revised (accepted) version, which includes a major new section providing detailed analysis of the types of wave modes present in the model, and characterizing the wave-mean-flow interactions by which they generate the QBO-like oscillation

Bayesian Nonparametrics to Model Content, User, and Latent Structure in Hawkes Processes

Communication in social networks tends to exhibit complex dynamics both in terms of the users involved and the contents exchanged. For example, email exchanges or activities on social media may exhibit reinforcing dynamics, where earlier events trigger follow-up activity through multiple structured latent factors. Such dynamics have been previously represented using models of reinforcement and reciprocation, a canonical example being the Hawkes process (HP). However, previous HP models do not fully capture the rich dynamics of real-world activity. For example, reciprocation may be impacted by the significance and receptivity of the content being communicated, and modeling the content accurately at the individual level may require identification and exploitation of the latent hierarchical structure present among users. Additionally, real-world activity may be driven by multiple latent triggering factors shared by past and future events, with the latent features themselves exhibiting temporal dependency structures. These important characteristics have been largely ignored in previous work. In this dissertation, we address these limitations via three novel Bayesian nonparametric Hawkes process models, where the synergy between Bayesian nonparametric models and Hawkes processes captures the structural and the temporal dynamics of communication in a unified framework. Empirical results demonstrate that our models outperform competing state-of-the-art methods, by more accurately capturing the rich dynamics of the interactions and influences among users and events, and by improving predictions about future event times, user clusters, and latent features in various types of communication activities