Exploration of Crystallization Kinetics in Quasi Two-Dimensional Perovskite and High Performance Solar Cells.

Halide perovskites with reduced-dimensionality (e.g., quasi-2D, Q-2D) have promising stability while retaining their high performance as compared to their three-dimensional counterpart. Generally, they are obtained in (A1)2(A2)n-1PbnI3n+1 thin films by adjusting A site cations, however, the underlying crystallization kinetics mechanism is less explored. In this manuscript, we employed ternary cations halides perovskite (BA)2(MA,FA)3Pb4I13 Q-2D perovskites as an archetypal model, to understand the principles that link the crystal orientation to the carrier behavior in the polycrystalline film. We reveal that appropriate FA+ incorporation can effectively control the perovskite crystallization kinetics, which reduces nonradiative recombination centers to acquire high-quality films with a limited nonorientated phase. We further developed an in situ photoluminescence technique to observe that the Q-2D phase (n = 2, 3, 4) was formed first followed by the generation of n = ∞ perovskite in Q-2D perovskites. These findings substantially benefit the understanding of doping behavior in Q-2D perovskites crystal growth, and ultimately lead to the highest efficiency of 12.81% in (BA)2(MA,FA)3Pb4I13 Q-2D perovskites based photovoltaic devices.

In Situ Studies of Copper-Based CO2 Reduction Electrocatalysts by Scanning Transmission Soft X-ray Microscopy.

A microfluidic-enabled electrochemical device has been developed to investigate electrochemically active nanomaterials under reaction conditions using in situ scanning transmission soft X-ray microscopy (STXM). In situ STXM measurements were conducted on electrodeposited Cu catalysts under electrochemical CO2 reduction (CO2R) conditions. The study provides detailed, quantitative results about the changes in the morphology and chemical structure of the catalytic nanoparticles as a function of applied potentials. The deposited Cu nanoparticles initially contain both Cu(0) and Cu(I). As an increasingly cathodic potential is applied, the Cu(I) species gradually convert to Cu(0) over the potential range of +0.4 to 0 V versus the reversible hydrogen electrode (VRHE). During this process, Cu(I) particles of various sizes are converted to metallic Cu at different reaction rates and at slightly different potentials, indicating a degree of heterogeneity in the electrochemical response of discrete particles. At CO2R relevant potentials, only metallic Cu is observed, and the morphology of the particles is fairly stable within the spatial resolution limits of STXM (∼40 nm). We also report in situ STXM studies of a working electrode with relatively thick Cu-based electrodeposits. The spatially resolved chemical analysis identifies that Cu-oxide species can persist under CO2R conditions, but only when the catalytic nanoparticles are electronically isolated from the working electrode and therefore are catalytically irrelevant. In summary, in situ STXM is presented as a technique to gain advanced morphological and spatially resolved chemical structure insights into electrochemically active nanomaterials, which was used to provide improved understanding regarding Cu nanomaterial catalysts under CO2 reduction conditions.

Statistical model of JPEG noises and its application in quantization step estimation.

In this paper, we present a statistical analysis of JPEG noises, including the quantization noise and the rounding noise during a JPEG compression cycle. The JPEG noises in the first compression cycle have been well studied; however, so far less attention has been paid on the statistical model of JPEG noises in higher compression cycles. Our analysis reveals that the noise distributions in higher compression cycles are different from those in the first compression cycle, and they are dependent on the quantization parameters used between two successive cycles. To demonstrate the benefits from the analysis, we apply the statistical model in JPEG quantization step estimation. We construct a sufficient statistic by exploiting the derived noise distributions, and justify that the statistic has several special properties to reveal the ground-truth quantization step. Experimental results demonstrate that the proposed estimator can uncover JPEG compression history with a satisfactory performance.