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It is a challenge to grow perovskite films with large crystalline grains and a full coverage on the surface of an organic compound film by a solution process. Herein, we for the first time introduce environmental‐friendly urea into PbI2 precursor to mediate the perovskite film growth and crystallization on the top of PEODT:PSS for efficient inverted solar cells. This method attains high‐quality perovskite films with large‐size grains of over 2 μm and a full coverage. This enables us to fabricate the inverted perovskite solar cells showing a maximum efficiency of 18.01% with a fill factor of 82.29% and a stabilized efficiency of 17.56%. Infrared spectroscopy and scanning electron microscopy images demonstrate that urea is coordinated with PbI2 to form PbI2 · OC(NH2)2 complex, resulting in large PbI2 flakes by a slow crystallization. The large PbI2 flake with fewer nucleation sites is conducive to forming monolithic perovskite grains. Further investigation indicates that CH3NH3I · PbI2 · OC(NH2)2 complex is formed as an intermediate phase, which retards the crystallization process of the perovskite films. These factors lead to a high‐quality perovskite film with large grain size and excellent crystallinity.

A microlens array has become an important micro-optics device in various applications. Compared with traditional manufacturing approaches, digital light processing (DLP)-based printing enables fabrication of complex three-dimensional (3D) geometries and is a possible manufacturing approach for microlens arrays. However, the nature of 3D printing objects by stacking successive 2D patterns formed by discrete pixels leads to coarse surface roughness and makes DLP-based printing unsuccessful in fabricating optical components. Here, we report an oscillation-assisted DLP-based printing approach for fabrication of microlens arrays. An optically smooth surface (about 1 nm surface roughness) is achieved by mechanical oscillation that eliminates the jagged surface formed by discrete pixels, and a 1–3 s single grayscale ultraviolet (UV) exposure that removes the staircase effect. Moreover, computationally designed grayscale UV patterns allow us to fabricate microlenses with various profiles. The proposed approach paves a way to 3D print optical components with high quality, fast speed, and vast flexibility.

Objective This study aimed to observe the clinical characteristics of patients with coronavirus disease 2019 (COVID‐19) with overweight and obesity. Methods Consecutive patients with COVID‐19 from 10 hospitals of Jiangsu province, China, were enrolled. Results A total of 297 patients with COVID‐19 were included, and 39.39% and 13.47% of patients had overweight and obesity, respectively. The proportions of bilateral pneumonia (92.50% vs. 73.57%, P = 0.033) and type 2 diabetes (17.50% vs. 3.57%, P = 0.006) were higher in patients with obesity than lean patients. The proportions of severe illness in patients with overweight (12.82% vs. 2.86%, P = 0.006) and obesity (25.00% vs. 2.86%, P < 0.001) were significantly higher than lean patients. More patients with obesity developed respiratory failure (20.00% vs. 2.86%, P < 0.001) and acute respiratory distress syndrome (5.00% vs. 0%, P = 0.024) than lean patients. The median days of hospitalization were longer in patients with obesity than lean patients (17.00 days vs. 14.00 days, P = 0.029). Overweight (OR, 4.222; 95% CI: 1.322‐13.476; P = 0.015) and obesity (OR, 9.216; 95% CI: 2.581‐32.903; P = 0.001) were independent risk factors of severe illness. Obesity (HR, 6.607; 95% CI: 1.955‐22.329; P = 0.002) was an independent risk factor of respiratory failure. Conclusions Overweight and obesity were independent risk factors of severe illness in COVID‐19 patients. More attention should be paid to these patients.

Compared with conventional camera, the light field camera takes the advantage of being capable of recording the direction and intensity information of each ray projected onto the CCD (charge couple device) sensor simultaneously. In this paper, a novel method is proposed for reconstructing three-dimensional (3-D) temperature field of a flame based on a single light field camera. A radiative imaging of a single light field camera is also modeled for the flame. In this model, the principal ray represents the beam projected onto the pixel of the CCD sensor. The radiation direction of the ray from the flame outside the camera is obtained according to thin lens equation based on geometrical optics. The intensities of the principal rays recorded by the pixels on the CCD sensor are mathematically modeled based on radiative transfer equation. The temperature distribution of the flame is then reconstructed by solving the mathematical model through the use of least square QR-factorization algorithm (LSQR). The numerical simulations and experiments are carried out to investigate the validity of the proposed method. The results presented in this study show that the proposed method is capable of reconstructing the 3-D temperature field of a flame.