Water and oxygen co-induced microstructure relaxation and evolution in CH3NH3PbI3.

Owing to perovskite possessing the outstanding optoelectronic properties, perovskite-based solar cells show prominent performance. The stability of perovskite-based solar cells hampers the progress of commercialization, so it is important to understand the microstructure mechanism of perovskite degradation under the humidity and oxygen environmental conditions. In this study, a meaningful Debye-type dielectric relaxation was observed under water vapor and oxygen co-treatment conditions. Interestingly, the relaxation was not observed under water vapor or oxygen treatment individually. This new dielectric relaxation is identified as a direct result of dipole jump, and its activation energy was measured to be 630 ± 6 meV. According to photoelectron spectroscopy and 13C nuclear magnetic resonance data, we suggest that the dipoles are formed by CH3NH3+ (MA+) and superoxide (O2-), which originate from the distorted crystal lattice and water vapor-weakened hydrogen bonds of Pb-I cages. In addition, the activation energy fitted by dielectric relaxation might be the energy of ion migration. This study contributes to understanding the mechanism of perovskite degradation from the view of microstructure relaxation and evolution, and also provides a method for the analysis of ion migration energy.

Performance Evaluation Of Convolutions And Atrous Convolutions In Deep Networks For Retinal Disease Segmentation On Optical Coherence Tomography Volumes.

The deterioration of the retina center could be the main reason for vision loss. Older people usually ranging from 50 years and above are exposed to age-related macular degeneration (AMD) disease that strikes the retina. The lack of human expertise to interpret the complexity in diagnosing diseases leads to the importance of developing an accurate method to detect and localize the targeted infection. Approaching the performance of ophthalmologists is the consistent main challenge in retinal disease segmentation. Artificial intelligence techniques have shown enormous achievement in various tasks in computer vision. This paper depicts an automated end-to-end deep neural network for retinal disease segmentation on optical coherence tomography (OCT) scans. The work proposed in this study shows the performance difference between convolution operations and atrous convolution operations. Three deep semantic segmentation architectures, namely U-net, Segnet, and Deeplabv3+, have been considered to evaluate the performance of varying convolution operations. Empirical outcomes show a competitive performance to the human level, with an average dice score of 0.73 for retinal diseases.

Anomalous surface diffusion of C60 and anisotropic growth of nano islands on Ni(111).

The migration behavior of C60 on Ni(111) has been inferred from its growth morphology at various substrate temperatures, as observed with scanning tunneling microscopy. The number density of islands increased and their average sizes decreased anomalously in the temperature range of approximately 573 K to approximately 973 K. This trend contradicts the prediction in conventional nucleation theory. At low and high temperatures, C60 commence nucleation on both sides of surface steps in a "bi-directional step flow" mode. However, anisotropy occurs within an intermediate temperature range, in which C60 nucleate predominantly at upper step edges. Surprisingly, in-situ growth measurements at this intermediate temperature range revealed that C60 actually start nucleating from lower step edges, with concomitant formation of Ni terraces underneath. These anomalous thermal dependence of diffusivity and the peculiar growth morphology of C60 on Ni(111) are attributed to C60-induced reconstruction of Ni(111) at higher temperature.