Cost management and toxic waste generation are two key issues that must be addressed before the commercialization of perovskite optoelectronic devices. We report a groundbreaking strategy for eco-friendly and cost-effective fabrication of highly efficient perovskite solar cells. This strategy involves the usage of a high volatility co-solvent, which dilutes perovskite precursors to a lower concentration (<0.5 M) while retaining similar film quality and device performance as a high concentration (>1.4 M) solution. More than 70% of toxic waste and material cost can be reduced. Mechanistic insights reveal ultra-rapid evaporation of the co-solvent together with beneficial alteration of the precursor colloidal chemistry upon dilution with co-solvent, which in-situ studies and theoretical simulations confirm. The co-solvent tuned precursor colloidal properties also contribute to the enhancement of the stability of precursor solution, which extends its processing window thus minimizing the waste. This strategy is universally successful across different perovskite compositions, and scales from small devices to large-scale modules using industrial spin-coating, potentially easing the lab-to-fab translation of perovskite technologies.
We utilize an array method called the frequency‐Bessel transformation method to extract the multimodal dispersion curves of Rayleigh waves from ambient seismic noise data recorded by the USArray Transportable Array. We observe as many as five overtones' dispersion curves of Rayleigh waves in the Midwestern United States, and four and three overtones' dispersion curves, respectively, in the U.S. Great Plain area and Northeastern United States. We employ a quasi‐Newton method to invert the multimodal dispersion curves for the shear velocity. We find that the sensitivity of overtones to deeper structures is higher than that of fundamental mode in the same frequency range. The utilization of overtones significantly improved the non‐uniqueness and convergence of the inversions, which make the final inversion results robust and reliable. Our inversion results for S wave velocity (Vs) model in the studied areas exhibit some differences compared with Shen and Ritzwoller's model (2016, https://doi.org/10.1002/2016JB012887). The Vs falls abruptly in the lower crust (21–33 km) in the U.S. Great Plain area and Northeastern U.S. areas. A high‐velocity zone is observable in depth of 50–60 km in the U.S. Great Plain area and Midwestern United States, and all three models show larger Vs values below 50 km than those of Shen and Ritzwoller (2016).
In the past two decades, seismic ambient-noise cross correlation (CC) has been one of the most important technologies in seismology. Usually, only the fundamental-mode surface-wave dispersion was extracted from the ambient noise. Recently, with the frequency–Bessel transform (F-J) method, overtone dispersion can also be extracted from the ambient noise and it adds significant value in inversion. This method has also been verified to be effective for array seismic records of earthquake events. In this article, we describe our algorithm and a Python package called CC-FJpy. For the F-J method, we use the Nvidia’s graphics processing unit to accelerate the computation, which can achieve a 100-fold computational efficiency. We have encapsulated our experiences and technologies into CC-FJpy and tested the CC-FJpy by ambient-noise and earthquake data to ensure its speed and ease of use. Our open-source package CC-FJpy can benefit the development of surface-wave studies using ambient noise and make it easier to start with high-mode surface waves.
A depth-dependent dispersion compensation algorithm for enhancing the image quality of the Fourier-domain optical coherence tomography (OCT) is presented. The dispersion related with depth in the sample is considered. Using the iterative method, an analytical formula for compensating the depth-dependent dispersion in the sample is obtained. We apply depth-dependent dispersion compensation algorithm to process the phantom images and in vivo images. Using sharpness metric based on variation coefficient to compare the results processed with different dispersion compensation algorithms, we find that the depth-dependent dispersion compensation algorithm can improve image quality at full depth.
In this paper, a photo-modulated transistor based on the thin-film transistor structure was fabricated on the flexible substrate by spin-coating and magnetron sputtering. A novel hybrid material that composed of CdSe quantum dots and reduced graphene oxide (RGO) fragment-decorated ZnO nanowires was synthesized to overcome the narrow optical sensitive waveband and enhance the photo-responsivity. Due to the enrichment of the interface and heterostructure by RGO fragments being utilized, the photo-responsivity of the transistor was improved to 2000 A W−1 and the photo-sensitive wavelength was extended from ultraviolet to visible. In addition, a positive back-gate voltage was employed to reduce the Schottky barrier width of RGO fragments and ZnO nanowires. As a result, the amount of carriers was increased by 10 folds via the modulation of back-gate voltage. With these inherent properties, such as integrated circuit capability and wide optical sensitive waveband, the transistor will manifest great potential in the future applications in photodetectors.
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