ABSTRACT
Pd-based electrocatalysts are the most effective catalysts for ethylene glycol oxidation reaction (EGOR), while the disadvantages of poor stability, low resistance to neutrophilic, and low catalytic activity seriously hamper the development of direct ethylene glycol fuel cells (DEGFCs). In this work, defect-riched PdCoZn nanosheets (D-PdCoZn NSs) with ultrathin 2D NSs and porous structures are fabricated through the solvothermal and alkali etching processes. Benefiting from the presence of defects and ultrathin 2D structures, D-PdCoZn NSs demonstrate excellent electrocatalytic activity and good durability against EGOR in alkaline media. The mass activity and specific activity of D-PdCoZn NSs for EGOR are 9.5 A mg-1 and 15.7 mA cm-2 , respectively, which are higher than that of PdCoZn NSs, PdCo NSs, and Pd black. The D-PdCoZn NSs still maintain satisfactory mass activity after long-term durability tests. Meanwhile, in situ IR spectroscopy demonstrates that the presence of defects attenuated the adsorption of intermediates, which improves the selectivity of the C1 pathway with excellent anti-CO poisoning performance. This work not only provides an effective synthetic strategy for the preparation of Pd-based nanomaterials with defective structures but also indicates significant guidance for optimum C1 pathway selectivity of ethylene glycol and other challenging chemical transformations.
ABSTRACT
In order to shorten detection times and improve average precision in embedded devices, a lightweight and high-accuracy model is proposed to detect passion fruit in complex environments (e.g., with backlighting, occlusion, overlap, sun, cloud, or rain). First, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computational complexity while improving the detection speed. Second, a new feature branch is added to the backbone network and the feature fusion layer in the neck network is reconstructed to effectively combine the lower- and higher-level features, which improves the accuracy of the model while maintaining its lightweight nature. Finally, a knowledge distillation method is used to transfer knowledge from the more capable teacher model to the less capable student model, significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than that of the original YOLOv5s model. Furthermore, the model size is 7.14 MB, half that of the original model, and its real-time detection frame rate is 11.25 FPS when implemented on the Jetson Nano. The proposed model is found to outperform state-of-the-art models in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruit in complex orchard scenes, offering valuable technical support for the development of orchard picking robots and greatly improving the intelligence level of orchards.
ABSTRACT
A motor imagery brain-computer interface connects the human brain and computers via electroencephalography (EEG). However, individual differences in the frequency ranges of brain activity during motor imagery tasks pose a challenge, limiting the manual feature extraction for motor imagery classification. To extract features that match specific subjects, we proposed a novel motor imagery classification model using distinctive feature fusion with adaptive structural LASSO. Specifically, we extracted spatial domain features from overlapping and multi-scale sub-bands of EEG signals and mined discriminative features by fusing the task relevance of features with spatial information into the adaptive LASSO-based feature selection. We evaluated the proposed model on public motor imagery EEG datasets, demonstrating that the model has excellent performance. Meanwhile, ablation studies and feature selection visualization of the proposed model further verified the great potential of EEG analysis.
Subject(s)
Brain-Computer Interfaces , Electroencephalography , Signal Processing, Computer-Assisted , Electroencephalography/methods , Humans , Algorithms , Brain/physiology , Brain/diagnostic imaging , Imagination/physiologyABSTRACT
Design high-loading with superior activity and high atomic efficiency has consistently been a new frontier of heterogeneous catalysis while challenging in synthetic technology. In this work, a universal solid-state strategy is proposed for large scalable production of high-loading Ir clusters on porous hollow carbon nanobowls (Ir CSs/PHCNBs). The strong electronic interaction between metallic Ir cluster and C on PHCNBs leads to electron redistribution, which significantly improves the electron transfer rate on the interface. The obtained Ir CSs/PHCNBs only require overpotentials of 35, 34, and 37 mV for the hydrogen evolution reaction (HER) with stable outputting of 10 mA cm-2 under acidic, alkaline, and neutral conditions, respectively, which exceeds the state-of-the-art HER electrocatalysts. Meanwhile, the Tafel slopes of Ir CSs/PHCNBs for the HER process are 23.07, 48.76, and 28.95 mV dec-1 , greatly lower than that of PHCNBs (152.73, 227.96, and 140.29 mV dec-1 ) and commercial Pt/C (20%) (36.33, 66.10, and 36.61 mV dec-1 ). These results provide a new strategy for the universal synthesis of clusters catalysts and insight into understanding the interface effects between clusters and carbon substrate, facilitating the industrial application of hydrogen production.
ABSTRACT
As a technology for emerging environmental applications, water electrolysis is a significant approach for producing clean hydrogen energy. In this work, we used an efficacious piezoelectric method to significantly improve the catalytic water splitting activity without affecting the morphology as well as the components by altering the bulk charge separation state inside the material. The obtained CuCo2O4 nanorods were treated under a corona polarization apparatus, which significantly enhanced ferroelectricity relative to that before the polarization increasing the physical charge separation and piezoelectric potential energy, enhancing the green hydrogen production. The polarized CuCo2O4 nanorods exhibit excellent water electrolysis performance under alkaline conditions, with hydrogen evolution overpotential of 78.7 mV and oxygen evolution overpotential of 299 mV at 10 mA cm-2, which is much better than that of unpolarized CuCo2O4 nanorods. Moreover, the Tafel slopes of polarized CuCo2O4 nanorods are 86.9 mV dec-1 in the HER process and 73.1 mV dec-1 in the OER process, which are much lower than commercial catalysts of Pt/C (88.0 mV dec-1 for HER) or RuO2 (78.5 mV dec-1 for OER), proving faster kinetic on polarized CuCo2O4 nanorods due to their higher electroconductibility and intrinsic activity. In particular, polarized CuCo2O4 nanorods are identified as promising catalysts for water electrolysis with robust stability, offering outstanding catalytic performance and excellent energy efficiency.
ABSTRACT
The electrocatalytic nitrogen reduction reaction (NRR) is emerging as a great promise for ambient and sustainable NH3 production while it still suffers from the high adsorption energy of N2 , the difficulty of *NN protonation, and inevitable hydrogen evolution, leading to a great challenge for efficient NRR. Herein, we synthesized a series of amorphous trimetal Pd-based (PdCoM (M = Cu, Ag, Fe, Mo)) nanosheets (NSs) with an ultrathin 2D structure, which shows high efficiency and robust electrocatalytic nitrogen fixation. Among them, amorphous PdCoCu NSs exhibit excellent NRR activity at low overpotentials with an NH3 yield of 60.68 µg h-1 mgcat -1 and a corresponding Faraday efficiency of 42.93% at -0.05 V versus reversible hydrogen electrode as well as outstanding stability with only 5% decrease after a long test period of 40 h at room temperature. The superior NRR activity and robust stability should be attributed to the large specific surface area, abundant active sites as well as structural engineering and electronic effect that boosts up the Pd 4d band center, which further efficiently restrains the hydrogen evolution. This work offers an opportunity for more energy conversion devices through the novel strategy for designing active and stable catalysts.
Subject(s)
Ammonia , Electronics , Adsorption , Electrodes , Hydrogen , NitrogenABSTRACT
Non-alcoholic fatty liver disease (NAFLD) is characterized by hepatic steatosis, inflammation, and fibrosis, as well as gut dysbiosis. Fibroblast growth factor 21 (FGF21), which regulates glucose and lipid metabolism, has been proven to have a good effect on NAFLD. However, the modulating process between FGF21 and gut microbiota remains unclear in treating NAFLD. Here, the fecal microbiota composition of 30 patients with NAFLD who had undergone liver biopsy and 29 matched healthy participants were studied, together with the fecal bile acid (BA) profile. Treatment with FGF21 was given in methionine-choline-deficient (MCD) diet-induced NAFLD model C57BL/6 mice. An antibiotic cocktail and fecal microbiota transplantation were used to further confirm the benefits of FGF21 that were partially attributable to the change in gut microbiota. Patients with NAFLD had higher serum FGF21 levels and dysregulated fecal microbiota compositions and fecal BA profiles. In NAFLD mice, FGF21 significantly reduced steatohepatitis and collagen deposition in vivo and restored intestinal structure. FGF21 treatment also changed gut microbiota composition and regulated dysbiosis in BA metabolism. After treatment with an antibiotic cocktail, FGF21 partially alleviated hepatic and intestinal damage in NAFLD mice. Furthermore, fecal microbiota transplantation from FGF21-treated mice showed benefits similar to FGF21 therapy. The improvement using FGF21 in MCD diet-induced NAFLD mice is partially mediated via gut microbiota and BA. Gut microbiota-regulated BA metabolism may be a potential target of FGF21 in improving NAFLD.
Subject(s)
Gastrointestinal Microbiome , Non-alcoholic Fatty Liver Disease , Animals , Mice , Bile Acids and Salts/metabolism , Choline/metabolism , Diet , Dysbiosis/drug therapy , Dysbiosis/metabolism , Gastrointestinal Microbiome/physiology , Liver/metabolism , Methionine/metabolism , Mice, Inbred C57BL , Non-alcoholic Fatty Liver Disease/metabolismABSTRACT
BACKGROUND: Fibroblast growth factor 21 (FGF21), primarily secreted by the pancreas, liver, and adipose tissues, plays a pivotal role in regulating glucose and lipid metabolism. Acute pancreatitis (AP) is a common inflammatory disease with specific clinical manifestations. Many patients with diabetes present with concurrent inflammatory symptoms. Diabetes exacerbates intestinal permeability and intestinal inflammation, thus leading to the progression to AP. Our previous study indicated that FGF21 significantly attenuated susceptibility to AP in mice. AIM: To investigate the potential protective role of FGF21 against AP in diabetic mice. METHODS: In the present study, a mouse model of AP was established in diabetic (db)/db diabetic mice through ceruletide injections. Thereafter, the protective effects of recombinant FGF21 protein against AP were evaluated, with an emphasis on examining serum amylase (AMS) levels and pancreatic and intestinal inflammatory cytokines [interleukin (IL)-6, tumor necrosis factor-alpha (TNF-), and intestinal IL-1ß]. Additionally, the impact of this treatment on the histopathologic changes of the pancreas and small intestinal was examined to elucidate the role of FGF21 in diabetic mice with AP. An antibiotic (Abx) cocktail was administered in combination with FGF21 therapy to investigate whether the effect of FGF21 on AP in diabetic mice with AP was mediated through the modulation of the gut microbiota. Subsequently, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt), a bioinformatics software package, was used to predict different pathways between the groups and to explore the potential mechanisms by which the gut microbiota influenced the protective effect of FGF21. RESULTS: The results indicated that FGF21 notably diminished the levels of serum AMS (944.5 ± 15.9 vs 1732 ± 83.9, P < 0.01) and inflammatory factors including IL-6 (0.2400 ± 0.55 vs 1.233 ± 0.053, P < 0.01), TNF- (0.7067 ± 0.22 vs 1.433 ± 0.051, P < 0.01), and IL-1ß (1.377 ± 0.069 vs 0.3328 ± 0.02542, P < 0.01) in diabetic mice with AP. Moreover, notable signs of recovery were observed in the pancreatic structure of the mice. The histologic evidence of inflammation in the small intestine, including edema and villous damage, was significantly alleviated. FGF21 also significantly altered the composition of the gut microbiota, reestablishing the Bacteroidetes/Firmicutes ratio. Upon treatment with an Abx cocktail to deplete the gut microbiota, the FGF21 + Abx group showed lower levels of serum AMS (0.9328 ± 0.075 vs 0.2249 ± 0.023, P < 0.01) and inflammatory factors (1.083 ± 0.12 vs 0.2799 ± 0.032, p < 0.01) than the FGF21 group. Furthermore, the FGF21 + Abx group exhibited diminished injury to the pancreatic and small intestinal tissues, accompanied by a significant decrease in blood glucose levels (17.50 ± 1.1 vs 9.817 ± 0.69 mmol/L, P < 0.001). These findings underscored the superior protective effects of the combination therapy involving an Abx cocktail with FGF21 over the FGF21 treatment alone in diabetic mice with AP. The gut microbiota composition across different groups was further characterized, and a differential expression analysis of gene functions was undertaken using the PICRUSt2 prediction method. These findings suggested that FGF21 could potentially confer therapeutic effects on diabetic mice with AP by modulating the sulfate reduction I pathway and the superpathway of n-acetylceramide degradation in the gut microbiota. CONCLUSION: This study reveals the potential of FGF21 in improving pancreatic and intestinal damage recovery, reducing blood glucose levels, and reshaping gut microbiota composition in diabetic mice with AP. Notably, the protective effects of FGF21 are augmented when combined with the Abx cocktail.
ABSTRACT
The passivation engineering of the hole transport layer in perovskite solar cells (PSCs) has significantly decreased carrier accumulation and open circuit voltage (Voc) loss, as well as energy band mismatching, thus achieving the goal of high-power conversion efficiency. However, most devices incorporating organic/inorganic buffer layers suffer from poor stability and low efficiency. In this article, we have proposed an inorganic buffer layer of Cu2O, which has achieved high efficiency on lower work function metals and various frequently used hole transport layers (HTLs). Once the Cu2O buffer layer was applied to modify the Cu/PTAA interface, the device exhibited a high Voc of 1.20 V, a high FF of 75.92%, and an enhanced PCE of 22.49% versus a Voc of 1.12 V, FF of 69.16%, and PCE of 18.99% from the (PTAA/Cu) n-i-p structure. Our simulation showed that the application of a Cu2O buffer layer improved the interfacial contact and energy alignment, promoting the carrier transportation and reducing the charge accumulation. Furthermore, we optimized the combinations of the thicknesses of the Cu2O, the absorber layer, and PTAA to obtain the best performance for Cu-based perovskite solar cells. Eventually, we explored the effect of the defect density between the HTL/absorber interface and the absorber/ETL interface on the device and recommended the appropriate reference defect density for experimental research. This work provides guidance for improving the experimental efficiency and reducing the cost of perovskite solar cells.