Preparation of ethyl cellulose bimodal nanofibrous membrane by green electrospinning based on molecular weight regulation for high-performance air filtration.

Preparing bio-based air filtration membrane through green electrospinning strategy is a vital approach to alleviating environmental and energy crises. However, the development of related biomaterials and method for regulating membrane structure are still lacking. In this study, ethyl cellulose (EC) bimodal nanofibrous membrane was prepared by electrospinning using ethanol and water as solvents to achieve high-performance air filtration.

Research on topological effect of natural small molecule and high-performance antibacterial air filtration application by electrospinning.

The application of natural small molecule (NSM) in electrospun fibers is the key to achieving powerful functionality and sustainable development. However, the lack of understanding regarding the mechanism for loading NSM hinders the advancement of high-performance functional fibers. This work clarified the loading mechanism of NSM in polymer solution by comparing the different behaviors of curcumin (Cur), phloretin (PL), and tea polyphenols (TP) blended ethyl cellulose (EC) solutions.

Ethyl cellulose/gelatin/β-cyclodextrin/curcumin nanofibrous membrane with antibacterial and formaldehyde adsorbable capabilities for lightweight and high-performance air filtration.

Functionalization of bio-based nanofibers is the development tendency of high-performance air filter. However, the conventional structural optimization strategy based on high solution conductivity greatly hinders the development of fully bio-based air filter, and not conducive to sustainable development. This work fabricated fully bio-based nanofibrous membrane with formaldehyde-adsorbable and antibacterial capabilities by electrospinning low-conductivity solution for high-performance air filtration and applied to lightweight mask.

Coaxial Electrospun Tai Chi-Inspired Lithium-Ion Battery Separator with High Performance and Fireproofing Capacity.

Organic flame-retardant-loaded battery separator offers a new opportunity for battery safety. However, its poor thermal stability still poses serious safety issues. Inspired by Tai Chi, an "internal-cultivating and external-practicing" core-shell nanofibrous membrane was prepared by coaxial electrospinning, wherein the shell layer was a mixture of polyvinylidene fluoride, silicon dioxide (SiO), and graphene oxide (GO) and the core layer contained triphenyl phosphate (TPP).

Hotspots Reduction for GALS NoC Using a Low-Latency Multistage Packet Reordering Approach.

Traffic splitting enabled by Globally Asynchronous Locally Synchronous (GALS) Network-on-chip (NoC) brings multipath routing capability, which significantly increases link bandwidth at the cost of out-of-order packet delivery. Solving the packet reordering problem is one of the keys to ensure the quality of service (QoS) for NoC. However, traditional packet reordering approaches rely on local reorder buffer, causing on-chip hotspots, which aggravates chip aging and even leads to interconnection failures.

Vessel extraction from non-fluorescein fundus images using orientation-aware detector.

The automatic extraction of blood vessels in non-fluorescein eye fundus images is a tough task in applications such as diabetic retinopathy screening. However, vessel shapes have complex variations, and accurate modeling of retinal vascular structures is challenging. We have therefore developed a new approach to accurately extract blood vessels in non-fluorescein fundus images using an orientation-aware detector (OAD).

A novel self-organizing E-Learner community model with award and exchange mechanisms.

How to share experience and resources among learners is becoming one of the hottest topics in the field of E-Learning collaborative techniques. An intuitive way to achieve this objective is to group learners which can help each other into the same community and help them learn collaboratively. In this paper, we proposed a novel community self-organization model based on multi-agent mechanism, which can automatically group learners with similar preferences and capabilities.