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Recently, the electronic waste (E-waste) has become the most serious environmental trouble because of the iteration of electronic products. Transparent conductive films (TCFs) are the key component of flexible electronic devices, so the development of devices based on degradable TCFs has become an important way to alleviate the problem of E-waste. Gelatin, one of the most prevalent natural biomacromolecules, has drawn increasing attention due to its good film-forming ability, superior biocompatibility, excellent degradability, and commercial availability at a relatively low cost, but has few applications in flexible electronics. Here, we report a method for preparing flexible TCF based on naturally degradable material-fish gelatin, in which silver nanowires and Ti3C2Tx flakes were used as conductive fillers. The obtained TCF has low roughness (RMS roughness = 5.62 nm), good photoelectric properties (Rs = 25.2 Ω/sq., T = ca.85% at 550 nm), strong interfacial adhesion and good degradability. Moreover, the film showed excellent application in the field of EMI shielding and green light OLED device. We believe that these TCFs will shine in the smart wearable field in the future.

Abstract Graphene oxide (GO), reduced graphene oxide (rGO) and carbon nanotubes (CNTs) have their own advantages in electrical, optical, thermal and mechanical properties. An effective combination of these materials is ideal for preparing transparent conductive films to replace the traditional indium tin oxide films. At present, the preparation conditions of rGO are usually harsh and some of them have toxic effects. In this paper, an SnCl2/ethanol solution was selected as the reductant because it requires mild reaction conditions and no harmful products are produced. The whole process of rGO preparation was convenient, fast and environmentally friendly. Then, SEM, XPS, Raman, and XRD were used to verify the high reduction efficiency. CNTs were introduced to improve the film conductive property. The transmittance and sheet resistance were the criteria used to choose the reduction time and the content ratios of GO/CNT. Thanks to the post-treatment of nitric acid, not only the by-product (SnO2) and dispersant in the film are removed, but also the doping effect occurs, which are all conducive to reducing the sheet resistances of films. Ultimately, by combining rGO, GO and CNTs, transparent conductive films with a bilayer and three-dimensional structure were prepared, and they exhibited high transmittance and low sheet resistance (58.8 Ω/sq. at 83.45 T%, 47.5 Ω/sq. at 79.07 T%), with corresponding $${{\sigma_{dc} } \mathord{\left/ {\vphantom {{\sigma_{dc} } {\sigma_{opt} }}} \right. \kern-\nulldelimiterspace} {\sigma_{opt} }}$$ σ dc / σ opt values of 33.8 and 31.8, respectively. In addition, GO and rGO can modify the surface and reduce the film surface roughness. The transparent conductive films are expected to be used in photoelectric devices.

Here, an approach to produce a hierarchical porous Fe‐N‐C@TABOH catalyst with densely accessible high intrinsic active FeNx sites is proposed. The method involves a single‐step pyrolysis of Zn/Fe‐zeolitic imidazolate framework (Zn/Fe‐ZIF‐H) with tetrabutylammonium hydroxide (TABOH) micelles, which is obtained by utilizing TABOH as a structural template and electronic mediator at room temperature for a brief duration of 16 min. Notably, the yield of Zn/Fe‐ZIF‐H is 3.5 times that of Zn/Fe‐ZIF‐N prepared by conventional method. Results indicate that in addition to expediting synthesis and increasing yield of the Zn/Fe‐ZIF‐H, the TABOH induces a hierarchical porous structure and fosters the formation of more and higher intrinsic active FeNx moieties in Fex‐N‐C@TABOH, showing that TABOH is a multifunctional template. Crucially, the increased mesoporosity/external surface area and optimized microenvironment of Fe‐N‐C@TABOH significantly enhance ORR activity by facilitating the formation of high intrinsic active FeNx sites, increasing accessible FeNx sites, and reducing mass transfer resistance. Through structure tailoring and microenvironment optimization, the resulting Fe‐N‐C@TABOH exhibits superior ORR performance. DFT calculation further validates that the synergistic effect of these two factors leads to low ORR barrier and optimized *OH adsorption energy. This study underscores the importance of structure and electronic engineering in the development of highly active ORR catalysts. [ABSTRACT FROM AUTHOR]

The study aimed to investigate the effects of wear parameters including impact energy, impact frequency, test time, and their interactions on the impact wear characteristics of high chromium white iron (HCWI) and zirconia toughened alumina (ZTA) reinforced HCWI composites fabricated by squeeze casting method using response surface methodology (RSM). The Box-Behnken Design (BBD) method was employed, and a linear model was developed to describe the relationship between wear loss and wear parameters, and to predict the wear behavior of the tested materials. The parameters of energy, frequency, and test time were found to be statistically significant, and positively influencing the wear behavior. Specifically, test time emerged as the most influential factor, followed by energy and frequency. The wear characteristics of HCWI are primarily characterized by shallower plowing and furrows, partial plastic deformation, surface spalling, and inserted abrasives. In contrast, the predominant wear mechanisms for ZTA/HCWI composites include slight breaking of ZTA particles, plowing, and cutting of the metal matrix; breaking and falling of ZTA particles; broken abrasive particles encrusted into the matrix; and the formation of spalling pits. [ABSTRACT FROM AUTHOR]

Hyperspectral image classification is widely applied in several fields. Since existing datasets focus on a single scene, current deep learning-based methods typically divide patches randomly on the same image as training and testing samples. This can result in similar spatial distributions of samples, which may incline the network to learn specific spatial distributions in pursuit of falsely high accuracy. In addition, the large variation between single-scene datasets has led to research in cross-scene hyperspectral classification, focusing on domain adaptation and domain generalization while neglecting the exploration of the generalizability of models to specific variables. This paper proposes two approaches to address these issues. The first approach is to train the model on the original image and then test it on the rotated dataset to simulate cross-scene evaluation. The second approach is constructing a new cross-scene dataset for spatial distribution variations, named GF14-C17&C16, to avoid the problems arising from the existing single-scene datasets. The image conditions in this dataset are basically the same, and only the land cover distribution is different. In response to the spatial distribution variations, this paper proposes a constrained spectral attention mechanism and a constrained spatial attention mechanism to limit the fitting of the model to specific feature distributions. Based on these, this paper also constructs a constrained spectral–spatial attention residual network (CSSARN). Extensive experimental results on two public hyperspectral datasets and the GF14-C17&C16 dataset have demonstrated that CSSARN is more effective than other methods in extracting cross-scene spectral and spatial features. [ABSTRACT FROM AUTHOR]

Introduction: Triptolide (TP), a natural product derived from the herbal medicine Tripterygium wilfordii, exhibits potent immunosuppressive activity. However, the mechanisms underlying its effects in rheumatoid arthritis remain incompletely understood. Methods: Collagen‐induced arthritis (CIA) model was induced in Sprague−Dawley rats by immunization with bovine type II collagen, and TP was administrated as treatment. The therapeutic effect of TP was evaluated based on paw swelling, histopathology, and serum levels of inflammatory factors. Exosomes isolated from rat serum were characterized by transmission electron microscopy, dynamic light scattering, and western blot analysis. Proteomic profiling of exosomes was analyzed by direct DIA quantitative proteomics analysis. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes databases were employed for enrichment analysis related to molecular function, biological processes, and signaling pathways. Western blot analysis was used to analyze differentially expressed proteins. Results: TP treatment ameliorated arthritic phenotypes in CIA rats as evidenced by reduced arthritis score, paw swelling, pathological injury severity scores, and serum levels of inflammatory cytokines. The proteomic analysis revealed that TP treatment significantly inhibited complement and coagulation cascades, interleukin‐17 signaling pathway, and cholesterol metabolism, which were reactivated in CIA rats. Importantly, lipocalin 2 (LCN2) and myeloperoxidase (MPO) levels were markedly upregulated in the CIA group but suppressed upon TP administration. Furthermore, in synovial tissues, LCN2 and MPO expression levels were also elevated in the CIA group but decreased following TP treatment. Conclusion: Our findings demonstrate that TP alleviates CIA, possibly through modulation of exosomal LCN2 and MPO proteins. [ABSTRACT FROM AUTHOR]

The relative neutron flux density distribution is one of the essential physical parameters of the reactor. Measuring the relative neutron flux density distribution of the annular fuel zero-power reactor core has guiding significance for understanding the physical characteristics of the annular fuel core reactor and conducting safety analysis. In this paper, the γ activity of the gold foil at different positions on the outer surface of the fuel cell after irradiation was measured by foil activation method under polygonal loading of annular fuel core. The axial and radial relative neutron flux density distributions of fuel cell at different positions were obtained, and the measured values were compared with the values calculated by Monte Carlo theory. The results show that the maximum relative deviation between experimental measurement and theoretical calculation is within 12%. The measurement results of relative neutron flux density distribution are in line with the measure design expectations. The existing Monte Carlo analysis methods can better analyze the axial flux density distribution of the components in the reactor. This study provides essential data support for the engineering application of annular fuel.