A Time-Interval Strategy to Prepare Porous SiO2 Spheres with Adjustable Core-Shell Ratio for Multiple Guest Loading.

Porous microspheres with desired pore size and distribution are in high demand for loading various guest materials, especially various pollutants that are several nanometers in size or stably suspended in liquid. Herein, multilevel porous SiO2 microspheres with arbitrarily adjustable core-shell ratios are prepared by solely regulating the time interval between the start of the hydrolysis reaction and the addition of organic solvent. The core-shell ratio of the SiO2 microspheres increases gradually with prolongation of the addition time interval; meanwhile, the specific surface area can be adjusted from 543.2 m2 g-1 to 992.9 m2 g-1, and the average pore diameter varies from 2.3 to 5.7 nm together with a high pore volume reaching 0.91 cm3 g-1. Moreover, the hierarchical core-shell SiO2 microspheres with an adjustable core-shell ratio, a large specific surface area, and a multilevel pore size could be obtained on a large scale. These SiO2 microspheres demonstrate excellent performance in coloading platinum nanoparticles and various dye molecules, suggesting their great potential in treating various pollutants in printing and dyeing wastewater.

Remote Sensing Retrieval of Cloud Top Height Using Neural Networks and Data from Cloud-Aerosol Lidar with Orthogonal Polarization.

In order to enhance the retrieval accuracy of cloud top height (CTH) from MODIS data, neural network models were employed based on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. Three types of methods were established using MODIS inputs: cloud parameters, calibrated radiance, and a combination of both. From a statistical standpoint, models with combination inputs demonstrated the best performance, followed by models with calibrated radiance inputs, while models relying solely on calibrated radiance had poorer applicability. This work found that cloud top pressure (CTP) and cloud top temperature played a crucial role in CTH retrieval from MODIS data. However, within the same type of models, there were slight differences in the retrieved results, and these differences were not dependent on the quantity of input parameters. Therefore, the model with fewer inputs using cloud parameters and calibrated radiance was recommended and employed for individual case studies. This model produced results closest to the actual cloud top structure of the typhoon and exhibited similar cloud distribution patterns when compared with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) CTHs from a climatic statistical perspective. This suggests that the recommended model has good applicability and credibility in CTH retrieval from MODIS images. This work provides a method to improve accurate CTHs from MODIS data for better utilization.