The electrocatalytic oxidation of small organic compounds such as methanol or formic acid has been the subject of numerous investigations in the last decades. The motivation for these studies is ...often their use as fuel in so-called direct methanol or direct formic acid fuel cells, promising alternatives to hydrogen-fueled proton exchange membrane fuel cells. The fundamental research spans from screening studies to identify the best performing catalyst materials to detailed mechanistic investigations of the reaction pathway. These investigations are commonly performed at conditions quite different to fuel cell devices, where no liquid electrolyte will be present. We previously developed a gas diffusion electrode setup to mimic “real-life” reaction conditions and study electrocatalysts for oxygen gas reduction or water splitting. It is here demonstrated that the setup is also suitable to investigate the properties of catalysts for the electro-oxidation of small organic molecules simulating conditions of low temperature proton exchange membrane fuel cells.
•GDE measurements for oxidation of small organic molecules mimicking PEM conditions.•Comparison of RDE and GDE results.•Applying realistic catalyst films without ECSA loss.•Benchmark study for GDE measurements.
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Path planning is a challenging, computationally complex optimization task in high-dimensional scenarios. The metaheuristic algorithm provides an excellent solution to this problem. The dung beetle ...optimizer (DBO) is a recently developed metaheuristic algorithm inspired by the biological behavior of dung beetles. However, it still has the drawbacks of poor global search ability and being prone to falling into local optima. This paper presents a multi-strategy enhanced dung beetle optimizer (MDBO) for the three-dimensional path planning of an unmanned aerial vehicle (UAV). First, we used the Beta distribution to dynamically generate reflection solutions to explore more search space and allow particles to jump out of the local optima. Second, the Levy distribution was introduced to handle out-of-bounds particles. Third, two different cross operators were used to improve the updating stage of thief beetles. This strategy accelerates convergence and balances exploration and development capabilities. Furthermore, the MDBO was proven to be effective by comparing seven state-of-the-art algorithms on 12 benchmark functions, the Wilcoxon rank sum test, and the CEC 2021 test suite. In addition, the time complexity of the algorithm was also analyzed. Finally, the performance of the MDBO in path planning was verified in the three-dimensional path planning of UAVs in oil and gas plants. In the most challenging task scenario, the MDBO successfully searched for feasible paths with the mean and standard deviation of the objective function as low as 97.3 and 32.8, which were reduced by 39.7 and 14, respectively, compared to the original DBO. The results demonstrate that the proposed MDBO had improved optimization accuracy and stability and could better find a safe and optimal path in most scenarios than the other metaheuristics.
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•Formic acid: an alternative hydrogen source for bio-oil upgrading.•Pd/AC: highly active and selective in transfer hydrogenation.•Hydrogenation activity decreases on supports with strong ...metal-support interaction in presence of HCOOH.
Palladium nanoparticles with size smaller than 10nm were loaded on several supports including activated carbon (AC), MIL-101, TiO2, Al2O3, and TiO2-activated carbon composites (TiO2-AC). These catalysts showed high activity in liquid phase hydrogenation of phenol. Their catalytic performances in transfer hydrogenation of phenol with formic acid under mild conditions (T=50°C and P<5bar) were also tested for the purpose of in situ upgrading of bio-oil. The activity followed the trend of Pd/AC>Pd/TiO2-AC>Pd/MIL-101>Pd/TiO2>Pd/Al2O3. When 400μL of formic acid was introduced into 10mL of 0.25M aqueous phenol solution, phenol can be fully hydrogenated on 200mg of Pd/AC catalyst at 50°C within 4h, with 80% selectivity to cyclohexanone. The high activity of Pd/AC catalyst in hydrogen transfer makes it possible for in situ upgrading of bio-oil under mild conditions by converting unstable components (such as HCOOH and phenol) to stable ones (mainly cyclohexanone) which can then be potentially introduced into current refinery. In addition, the effect of formic acid on the hydrogenation activity of supported Pd catalysts was also reported. Presence of formic acid significantly decreased the hydrogenation activity of Pd supported on MIL-101 and oxides (TiO2 and Al2O3), probably due to the competitive adsorption of molecular formic acid with phenol on a single Pd site.
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Aiming at the problems of low resource utilization and high distribution cost of urban logistics enterprises, this paper introduces the threshold setting of large parcels, comprehensively considers ...the processing links of large parcels and standard parcels in loading, unloading, sorting, and other processing links, and constructs a logistics planning model with the type of multi-functional transit center as the variable and the total cost of the logistics system as the goal. Aiming at the shortcomings of the honey badger algorithm, three optimization strategies are used to improve the logistics model, and the effectiveness of the improved algorithm is verified by comparing with the CPLEX operation results. Based on the operation data of SF Jinzhou, this paper obtains the optimization results of large parcel threshold, multi-function transit center location layout, and terminal demand point allocation. From the results, the introduction of the threshold setting for large parcels has played a significant role in the joint optimization of multi-functional center location selection and terminal demand point allocation under multi-parcel distribution and provides theoretical data support for the existing urban logistics location problem.
Aspect Sentiment Triplet Extraction (ASTE) is a challenging task in natural language processing (NLP) that aims to extract triplets from comments. Each triplet comprises an aspect term, an opinion ...term, and the sentiment polarity of the aspect term. The neural network model developed for this task can enable robots to effectively identify and extract the most meaningful and relevant information from comment sentences, ultimately leading to better products and services for consumers. Most existing end-to-end models focus solely on learning the interactions between the three elements in a triplet and contextual words, ignoring the rich affective knowledge information contained in each word and paying insufficient attention to the relationships between multiple triplets in the same sentence. To address this gap, this study proposes a novel end-to-end model called the Dual Graph Convolutional Networks Integrating Affective Knowledge and Position Information (DGCNAP). This model jointly considers both the contextual features and the affective knowledge information by introducing the affective knowledge from SenticNet into the dependency graph construction of two parallel channels. In addition, a novel multi-target position-aware function is added to the graph convolutional network (GCN) to reduce the impact of noise information and capture the relationships between potential triplets in the same sentence by assigning greater positional weights to words that are in proximity to aspect or opinion terms. The experiment results on the ASTE-Data-V2 datasets demonstrate that our model outperforms other state-of-the-art models significantly, where the F1 scores on 14res, 14lap, 15res, and 16res are 70.72, 57.57, 61.19, and 69.58.
A novel approach called the nonlinear convex decreasing weights golden eagle optimization technique based on a global optimization strategy is proposed to overcome the limitations of the original ...golden eagle algorithm, which include slow convergence and low search accuracy. To enhance the diversity of the golden eagle, the algorithm is initialized with the Arnold chaotic map. Furthermore, nonlinear convex weight reduction is incorporated into the position update formula of the golden eagle, improving the algorithm’s ability to perform both local and global searches. Additionally, a final global optimization strategy is introduced, allowing the golden eagle to position itself in the best possible location. The effectiveness of the enhanced algorithm is evaluated through simulations using 12 benchmark test functions, demonstrating improved optimization performance. The algorithm is also tested using the CEC2021 test set to assess its performance against other algorithms. Several statistical tests are conducted to compare the efficacy of each method, with the enhanced algorithm consistently outperforming the others. To further validate the algorithm, it is applied to the cognitive radio spectrum allocation problem after discretization, and the results are compared to those obtained using traditional methods. The results indicate the successful operation of the updated algorithm. The effectiveness of the algorithm is further evaluated through five engineering design tasks, which provide additional evidence of its efficacy.
In recent years, scholars have paid increasing attention to the joint entity and relation extraction. However, the most difficult aspect of joint extraction is extracting overlapping triples. To ...address this problem, we propose a joint extraction model based on Soft Pruning and GlobalPointer, short for SGNet. In the first place, the BERT pretraining model is used to obtain the text word vector representation with contextual information, and then the local and non-local information of the word vector is obtained through graph operations. Specifically, to address the lack of information caused by the rule-based pruning strategies, we utilize the Gaussian Graph Generator and the attention-guiding layer to construct a fully connected graph. This process is called soft pruning for short. Then, to achieve node message passing and information integration, we employ GCNs and a thick connection layer. Next, we use the GlobalPointer decoder to convert triple extraction into quintuple extraction to tackle the problem of problematic overlapping triples extraction. The GlobalPointer decoder, unlike the typical feedforward neural network (FNN), can perform joint decoding. In the end, to evaluate the model performance, the experiment was carried out on two public datasets: the NYT and WebNLG. The experiments show that SGNet performs substantially better on overlapping extraction and achieves good results on two publicly available datasets.
The introduction of structural defects in metal–organic frameworks (MOFs), often achieved through the fractional use of defective linkers, is emerging as a means to refine the properties of existing ...MOFs. These linkers, missing coordination fragments, create unsaturated framework nodes that may alter the properties of the MOF. A property‐targeted utilization of this approach demands an understanding of the structure of the defect‐engineered MOF. We demonstrate that full‐field X‐ray absorption near‐edge structure computed tomography can help to improve our understanding. This was demonstrated by visualizing the chemical heterogeneity found in defect‐engineered HKUST‐1 MOF crystals. A non‐uniform incorporation and zonation of the defective linker was discovered, leading to the presence of clusters of a second coordination polymer within HKUST‐1. The former is suggested to be responsible, in part, for altered MOF properties; thereby, advocating for a spatio‐chemically resolved characterization of MOFs.
A three‐dimensional view of chemical heterogeneities in defect‐engineered HKUST‐1 metal–organic framework (MOF) crystals is presented. Cryo‐full‐field XANES computed tomography was used to visualize the presence and distribution of a second coordination polymer of reduced copper coordination within defect‐engineered HKUST‐1 crystals. Observations encourage a revisitation of the structure‐property relationships of defect‐engineered MOFs.
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Path planning is one of the key issues in the research of unmanned aerial vehicle technology. Its purpose is to find the best path between the starting point and the destination. Although there are ...many research recommendations on UAV path planning in the literature, there is a lack of path optimization methods that consider both the complex flight environment and the performance constraints of the UAV itself. We propose an enhanced version of the Chimp Optimization Algorithm (TRS-ChOA) to solve the UAV path planning problem in a 3D environment. Firstly, we combine the differential mutation operator to enhance the search capability of the algorithm and prevent premature convergence. Secondly, we use improved reverse learning to expand the search range of the algorithm, effectively preventing the algorithm from missing high-quality solutions. Finally, we propose a similarity preference weight to prevent individuals from over-assimilation and enhance the algorithm’s ability to escape local optima. Through testing on 13 benchmark functions and 29 CEC2017 complex functions, TRS-ChOA demonstrates superior optimization capability and robustness compared to other algorithms. We apply TRS-ChOA along with five well-known algorithms to solve path planning problems in three 3D environments. The experimental results reveal that TRS-ChOA reduces the average path length/fitness value by 23.4%/65.0%, 8.6%/81.0%, and 16.3%/41.7% compared to other algorithms in the three environments, respectively. This indicates that the flight paths planned by TRS-ChOA are more cost-effective, smoother, and safer.
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Two metal organic frameworks (MOFs), chromium benzenedicarboxylates MIL-101 and MIL-53, have been synthesized and used as the support of palladium catalysts. The palladium catalysts were ...characterized by XRD, TEM, and CO chemisorption. MIL-101 is highly hydrophilic and beneficial as support for fine Pd nanoparticles with an average size of 2.3nm. Microporous MIL-53 is relatively hydrophobic and larger Pd particles with an average size of 4.3nm were formed on the external surface. Pd/MIL-101 showed better phenol selective hydrogenation activity to cyclohexanone (>98%) under mild reaction conditions because of its smaller particle size.
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•Hydrophilic MIL-101 benefits the support of Pd nanoparticles.•MIL-53: hydrophobic and adsorbing phenolic compounds strongly.•Pd/MILs: highly active catalyst for selective hydrogenation of phenol.
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