Bioinspired Supramolecular Slippery Organogels for Controlling Pathogen Spread by Respiratory Droplets

Surface-deposited pathogens are sources for the spread of infectious diseases. Protecting public facilities with a replaceable or recyclable antifouling coating is a promising approach to control pathogen transmission. However, most antifouling coatings are less effective in preventing pathogen-contained respiratory droplets because these tiny droplets are difficult to repel, and the deposited pathogens can remain viable from hours to days. Inspired by mucus, an antimicrobial supramolecular organogel for the control of microdroplet-mediated pathogen spread is developed. The developed organogel coating harvests a couple of unique features including localized molecular control-release, readily damage healing, and persistent fouling-release properties, which are preferential for antifouling coating. Microdroplets deposited on the organogel surfaces will be spontaneously wrapped with a thin liquid layer, and will therefore be disinfected rapidly due to a mechanism of spatially enhanced release of bactericidal molecules. Furthermore, the persistent fouling-release and damage-healing properties will significantly extend the life-span of the coating, making it promising for diverse applications.     

Self-healing,elastic and deformable novel composite phase change polymer based on thermoplastic elastomer SEBS for wearable devices

Journal of Materials Science - Form-stable composite phase change materials (C-PCMs) prepared by microencapsulation method and porous matrix adsorption method need for compression molding after...     

离子型稀土矿山淋洗及尾水富集试验研究

对浸矿后离子型稀土原地浸矿场采用清水进行淋洗，在184天的清水淋洗过程中，尾水氨氮值从最开始的507mg/L，降低至140mg/L，淋洗尾水pH4.52~3.10。淋洗尾水采用两级反渗透膜分离，既回收有价资源稀土，又能使出水氨氮达标。结果表明，产水氨氮浓度稳定低于15mg/L，对稀土的截留率高于98.25%，浓水中稀土离子平均浓度313.4mg/L，可进一步回收稀土资源。     

Ultralight and robustly compressible silica aerogel enhanced by AC/C sponge with high oil/water separation

Journal of Porous Materials - In recent years, oil spills and industrial organic pollutants have caused irreparable damage to the environment and biological ecosystems. Therefore, the treatment of...     

A Feature Extraction Method for scRNA-seq Processing and Its Application on COVID-19 Data Analysis

Single-cell RNA-sequencing (scRNA-seq) is a rapidly increasing research area in biomedical signal processing. However, the high complexity of single-cell data makes efficient and accurate analysis difficult. To improve the performance of single-cell RNA data processing, two single-cell features calculation method and corresponding dual-input neural network structures are proposed. In this feature extraction and fusion scheme, the features at the cluster level are extracted by hierarchical clustering and differential gene analysis, and the features at the cell level are extracted by the calculation of gene frequency and cross cell frequency. Our experiments on COVID-19 data demonstrate that the combined use of these two feature achieves great results and high robustness for classification tasks.