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Water pollution has emerged as a formidable issue of utmost concern in the world, and the design of three-dimensional porous, high adsorption performance, and sustainable adsorbent materials is of great significance for wastewater purification. Naturally abundant sodium alginate was used to prepare oxidized sodium alginate (OSA), a biomass macromolecule containing an aldehyde group. A double network interpenetrating structure based on carboxymethyl chitosan (CMS) and OSA was constructed without any small molecule cross-linking agent throughout, and a Schiff base reaction occurred at room temperature to prepare chemically stable CMS@OSA aerogels, which contain a continuous and dense porous structure inside the aerogel. CMS and OSA both contain an anionic reactive group, carboxyl, which makes them both matrix and functional materials, enabling selective adsorption of malachite green (MG) dyes. The prepared aerogel adsorbent showed a high adsorption capacity (302 mg/g) for MG at room temperature. The adsorption mechanism between the aerogel adsorbent and the adsorbent mass was investigated, and the effect of different factors on the adsorption performance was analyzed. The fitting coefficients of both the adsorption kinetic model and the isotherm model reached 0.99. The ingenious preparation method and excellent adsorption performance offer great prospects for chitosan biomass aerogels to play a role in environmental protection and economy. Highlights * An interpenetrating structure based on the Schiff base reaction. * Construction of three-dimensional porous structures. * Pure ecological raw materials without toxic crosslinkers. * High adsorption capacity at 302 mg/g for malachite green. KEYWORDS adsorption, aerogel, chitosan, malachite green, sodium alginate, 1 | INTRODUCTION Water is considered to be the most important natural resource for human survival. A healthy and adequate water supply is the basis for human well-being and an [...]

Abstract Biodegradable poly(butylene adipate-co-terephthalate) (PBAT) has excellent processing and mechanical properties. However, PBAT is expensive and its relatively slow biodegradation rate limits its wide application. In this paper, PBAT/thermoplastic starch [...]

Most of data contain only a few labels because of high cost of obtaining them in reality. Compared with supervised learning and unsupervised learning, semi-supervised learning can obtain higher learning performance with less labeling cost by making full use of large amount of unlabeled data and small amount of labeled data in datasets.Self-Training algorithm is a classical semi-supervised learning algorithm. In the process of iteratively optimizing classi-fier, high-confidence samples are continuously selected from unlabeled samples and labeled by the base classifier.Then, these samples and pseudo-labels will be added into the training sets. Selecting high-confidence samples is a critical step in the Self-Training algorithm. Inspired by the density peaks clustering (DPC) algorithm, this paper pro-poses semi-supervised Self-Training algorithm for density peak membership optimization (STDPM), which uses den-sity peak to select high-confidence samples. Firstly, STDPM takes density peak to discover the potential spatial structure information of the samples and constructs a prototype tree. Secondly, STDPM searches the unlabeled direct relatives of the labeled samples in the prototype tree, and defines the density peak of the unlabeled direct relatives that belong to different clusters as the clusters-peak. Then, clusters-peak is turned into the density peak membership after normalized. Finally, STDPM regards samples with membership greater than the set threshold as high-confidence samples that are labeled by the base classifier and added to the training set. STDPM makes full use of the density and distance information implied by the peak, which improves the selection quality of high-confi-dence samples and further improves the classification performance. Comparative experiments are conducted on 8 bench-mark datasets, which verify the effectiveness of STDPM.

Flexible wearable devices based on conductive hydrogels have received widespread attention. However, the poor mechanical properties, weak adhesion and low sensitivity of traditional hydrogels greatly limit their practical applications. In this study, a polyacrylamide/gelatin/tannic acid-modified carbon nanotube (PAM/gelatin/TA-CNT) double network conductive hydrogel with skin temperature-triggered adhesion and low-temperature-triggered detachment was constructed via a simple one-pot method using polyacrylamide (PAM) and gelatin as the main components, and tannic acid (TA)-modified carbon nanotubes (CNTs) as the conductive filler. The resulting hydrogel has various functions such as excellent mechanical properties, high sensitivity (GF value was 5.50), wide strain detection range and excellent fatigue resistance. Flexible strain sensors based on this hydrogel can provide real-time and stable monitoring of human physiological activities over a wide strain range. In addition, its assembly into a pressure sensor can also realize information encryption and transmission. [ABSTRACT FROM AUTHOR]

Bio-based polyamide 56 (PA56) is an environmentally friendly polymer but has not been widely used due to its inherent disadvantages of low impact strength and brittleness. In this paper, polyethylene and maleic anhydride grafted EPDM were used to co-modify PA56. The core-shell structure of PP and EPDM-g-MAH could increase the impact strength of the composites by a factor of 4.5 without significant loss of toughness. The toughness and rigidity of PA56 were balanced while the thermal stability and crystalline properties were maintained in a betterstate. This gives PA56 great potential for the automotive and construction machinery industries. [ABSTRACT FROM AUTHOR]

Membrane separation technology, as an important means of treating oily wastewater, is considered to be one of the most promising oil/water separation technologies. However, problems such as membrane contamination and single separation performance have also hindered its wider application. In this study, polydopamine (PDA)-Ag nanospheres were prepared by oxidant-induced dopamine polymerization and in situ reduction with silver ions, and assembled onto silanized poly(vinylidene fluoride) (PVDF) filtration membranes by a vacuum-assisted operation. The separation efficiency of the PDA–Ag@PVDF filter membrane for the dichloroethane oil-in-water emulsion was 98.8%, and the removal rate of malachite green dye in the emulsion was as high as 98%. After multiple separation/UV irradiation cycles, the flux recovery rate was greater than 98.7%. The PDA–Ag@PVDF filter membrane is a multifunctional and self-cleaning separation membrane, whose excellent properties make it promising in the field of oil/water separation. [ABSTRACT FROM AUTHOR]

Hydrogels have been widely used for adsorbing heavy metal ions in wastewater treatment. Herein, a calcium alginate/poly‐N‐isopropylacrylamide double‐network hydrogel with photothermal responsiveness was prepared for adsorbing heavy metal ions in aqueous solution. The chemical composition, micromorphology, swelling properties, photothermal responsiveness, adsorption properties, and adsorption mechanism of gel microspheres were studied, respectively. The gel microspheres had an interpenetrating three‐dimensional porous structure, and their high porosity morphology and high specific surface area could ensure the adequate exposure of active adsorption sites. The gel microspheres showed excellent selective adsorption of Cr(III), and the theoretical maximum adsorption capacity of 146.16 mg/g was calculated according to the Langmuir model. Besides, its excellent photothermal conversion ability enhanced the resistance to external interference after the adsorption. Our work has provided an innovative approach to solar water purification while optimizing the preparation process. [ABSTRACT FROM AUTHOR]

Conductive hydrogel-based flexible sensors have garnered significant interest in the realm of smart wearable electronics. Nevertheless, the development of multifunctional hydrogels continues to be an essential challenge, given that conventional hydrogels typically exhibit singular functionality and frail mechanical properties. In this study, inspired by mussels, a multifunctional conductive hydrogel with superior stretchability, adhesion, pH sensitivity, and antibacterial activation was prepared with polydopamine (PDA)-coated carbon nanotubes (CNTs) doped. Particularly, a semi-interpenetrating network structure with multiple cross-linking sites was constructed, resulting in the hydrogel with a super-stretching ability (1904%) and fatigue resistance. The PDA-CNTs in the system not only imparted self-adhesive properties to the hydrogel but also facilitated efficient ion and electron transfer with the synergistic effect of Al3+, thereby enhancing the sensitivity (GF = 3.81) and cycling stability. The flexible sensor based on this hydrogel could be applicable to detect various human activities and also exhibited huge potential in the field of information sensing and transmission. [ABSTRACT FROM AUTHOR]

Biodegradable poly(butylene adipate‐co‐terephthalate) (PBAT) has excellent processing and mechanical properties. However, PBAT is expensive and its relatively slow biodegradation rate limits its wide application. In this paper, PBAT/thermoplastic starch (TPS) complexes were prepared by a two‐step process using epoxidized soybean oil (ESO) as a reactive compatibilizer. The compatibilizing ability of ESO was investigated by FT‐IR and GPC. Results showed ESO could form a chemical bonding interface with PBAT and TPS. Compared to PBAT/TPS, tensile strength, elongation at break and tear strength of PBAT/TPS/5%ESO composites increased by 84%, 53%, and 68%, respectively. The optical transparency of the PBAT/TPS/5%ESO film improved by 6% compared to the PABT/TPS film. This research offers a viable solution for the preparation of high performance, green PBAT/TPS complexes. [ABSTRACT FROM AUTHOR]