Construction of Covalent Organic Framework Nanofiber Membranes for Efficient Adsorption of Antibiotics.

Techniques beyond crystal engineering are critical for manufacturing covalent organic frameworks (COFs) and to explore them for advanced applications. However, COFs are normally obtained as insoluble, unmeltable, and thus nonprocessible microcrystalline powders. Therefore, it is a significant challenge to implement COFs into larger architectures and structural control on different length scales. Herein, a facile strategy is presented to prepare flexible COF nanofiber membranes by in-situ growth of COFs on polyacrylonitrile (PAN) nanofiber substrates via a reversible polycondensation-termination approach. The obtained PAN@COF nanofiber membranes with vertically aligned COF nanoplates combine a large functional surface with efficient mass transport, thus making it a promising adsorbent, for example, for water purification. The antibiotic pollutant ofloxacin (OFX) is removed from water with a superior absorption capacity of ≈236 mg g-1 and removal efficiency as high as 98%. The here presented in-situ growth of COFs on nanofiber membranes can be extended to various Schiff base-derived COF materials with different compositions, providing a highly efficient way to construct flexible COF-based membranes for several applications.

ECGAN-Assisted ResT-Net Based on Fuzziness for OSA Detection.

OBJECTIVE: Growing attention has been paid recently to electrocardiogram (ECG) based obstructive sleep apnea (OSA) detection, with some progresses been made on this topic. However, the lack of data, low data quality, and incomplete data labeling hinder the application of deep learning to OSA detection, which in turn affects the overall generalization capacity of the network. METHODS: To address these issues, we propose the ResT-ECGAN framework. It uses a one-dimensional generative adversarial network (ECGAN) for sample generation, and integrates it into ResTNet for OSA detection. ECGAN filters the generated ECG signals by incorporating the concept of fuzziness, effectively increasing the amount of high-quality data. ResT-Net not only alleviates the problems caused by deepening the network but also utilizes multihead attention mechanisms to parallelize sequence processing and extract more valuable OSA detection features by leveraging contextual information. RESULTS: Through extensive experiments, we verify that ECGAN can effectively improve the OSA detection performance of ResT-Net. Using only ResT-Net for detection, the accuracy on the Apnea-ECG and private databases is 0.885 and 0.837, respectively. By adding ECGAN-generated data augmentation, the accuracy is increased to 0.893 and 0.848, respectively. CONCLUSION AND SIGNIFICANCE: Comparing with the state-of-the-art deep learning methods, our method outperforms them in terms of accuracy. This study provides a new approach and solution to improve OSA detection in situations with limited labeled samples.

A ratiometric fluorescence sensor based on gold silver nanoclusters and tungsten disulfide quantum dots with simple fabrication for the detection of copper ions in river water.

Copper plays a key role in the human body; meanwhile, excess Cu2+ ions can result in various diseases. Nanoclusters (NCs) are often used to measure Cu2+ ions, but there are two difficulties. On the one hand, a single probe of NCs is easily affected by environmental factors. On the other hand, it is difficult to mask the interference of Pb2+ ions and Cd2+ ions in the process of detecting Cu2+ ions. As a new type of quantum dots (QDs), tungsten disulfide quantum dots (WS2-QDs) have some advantages of simple synthesis and stable luminescence properties. Stable WS2-QDs with blue fluorescence are used as a reference probe, while gold silver nanoclusters (AuAgNCs) with red fluorescence are used as a response probe. A ratiometric fluorescent sensor was constructed by mixing the two styles of fluorescent probes, which is abbreviated as NCs/QDs. This nano-sensor can be used to detect the concentration of Cu2+ ions, in which the fluorescence of QDs does not change significantly, while the fluorescence of NCs can be quenched by Cu2+ ions. The concentration of Cu2+ ions can be determined as low as 0.12 µM with a linear range from 0.3 to 3 µM. The common interference caused by Pb2+ and Cd2+ ions can be eliminated by the phosphate buffer solution (PBS). This sensor was used to detect the concentration of Cu2+ in river water with satisfactory results.

A covalent organic framework/graphene aerogel electrocatalyst for enhanced overall water splitting.

The rational design of covalent organic framework (COF) based hybrid materials is of paramount importance to address the fundamental challenges of COFs with respect to their poor electron mobilization and the limited number of accessible active sites. Herein, we propose a new strategy for the fabrication of covalently bonded COF grafted graphene aerogel hybrid materials for electrocatalytic application. An in situ step-growth polymerization approach was developed to achieve the hybridization of COFs along the surface of amino-functionalized graphene nanosheets. By taking advantage of the three-dimensional conductive networks and highly accessible active sites, the cobalt-incorporated COF/graphene hybrid aerogel shows high oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) performances with an overpotential of 300 and 275 mV at 10 mA cm-2, respectively, under alkaline conditions. When applied to an electrochemical water-splitting electrolyzer, it is able to produce hydrogen and oxygen at competitive rates of 1.14 and 0.58 µL s-1, respectively, under ambient conditions, demonstrating its potential for practical applications.