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1.
《International Journal of Hydrogen Energy》2022,47(65):28074-28085
In this paper, a new carbon support with a large number of mesoporous-structures is selected to prepare Pt/C catalysts. Transmission electron microscope (TEM) results show that the Pt/3# catalyst presents a sponge-like morphology, Pt particles are not only evenly distributed on the surface of carbon support, but also the smaller Pt particles are deposited in the mesoporous inside the support. The average diameter of Pt particles is only 2.8 nm. The membrane electrode assembly (MEA) based on Pt/3# catalyst also shows excellent performance. In conclusion, the 3# support is an idea carbon support for PEMFC, which helps to improve the oxygen reduction reaction (ORR) activity of the catalyst. Based on the “internal-Pt” structure of the support mesoporous, the efficient three-phase boundaries (TPBs) are construct to avoid the poisoning effect of ionomer on the nano-metal particles, reduce the activation impedance and oxygen mass transfer impedance, and improve the reaction efficiency. 相似文献
2.
《International Journal of Hydrogen Energy》2022,47(79):33765-33780
This work investigates selective Ni locations over Ni/CeZrOx–Al2O3 catalysts at different Ni loading contents and their influences on reaction pathways in ethanol steam reforming (ESR). Depending on the Ni loading contents, the added Ni selectively interacts with CeZrOx–Al2O3, resulting in the stepwise locations of Ni over CeZrOx–Al2O3. This behavior induces a remarkable difference in hydrogen production and coke formation in ESR. The selective interaction between Ni and CeZrOx for 10-wt.% Ni generates more oxygen vacancies in the CeZrOx lattice. The Ni sites near the oxygen vacancies enhance reforming via steam activation, resulting in the highest hydrogen production rate of 1863.0 μmol/gcat·min. In contrast, for 15 and 20-wt.% Ni, excessive Ni is additionally deposited on Al2O3 after the saturation of Ni–CeZrOx interactions. These Ni sites on Al2O3 accelerate coking from the ethylene produced on the acidic sites, resulting in a high coke amount of 19.1 mgc/gcat·h (20Ni/CZ-Al). 相似文献
3.
Ya Gu Quanmin Zhu Hassan Nouri 《International Journal of Adaptive Control and Signal Processing》2022,36(1):138-154
This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results. 相似文献
4.
《International Journal of Hydrogen Energy》2022,47(47):20494-20506
Proton exchange membrane fuel cells (PEMFCs) durability has been severely hindered by carbon support poor stability in the cathodic Pt-based catalyst. Herein, a high-surface-area nitrogen-doped graphitic nanocarbon (N-G-CA) with mesopores is developed as Pt support to address PEMFCs durability challenge. Resorcinol-formaldehyde aerogel pyrolyzed carbon aerogel is selected as N-G-CA raw material. Nitrogen atoms are introduced into carbon aerogel via NH3 heat treatment. Then, nitrogen-doped carbon aerogel is transferred into N-G-CA via heating together with transition-metal salts (one of FeCl3, FeCl2, CoCl2, or MnCl2, etc.) at 1200 °C. As ORR catalyst, Pt/N-G-CA half-wave potential only lost 10 mV, after 30, 000 cycles accelerated aging test in the rotating-desk-electrode. Only 12 mV voltage loss at 1.5 A/cm2 is observed, after 5, 000 cycles for membrane electrode. Pt/N-G-CA exhibits superior durability and activity than commercial Pt/C. High durability of Pt/N-G-CA is due to N-G-CA high graphitization extent, as well as the interactions between doping nitrogen and Pt. N-G-CA is promising as stable support for durable Pt-based catalysts in PEMFCs, thanks to enhanced carbon corrosion resistance, uniformly dispersed Pt, and strong support-metals interaction. 相似文献
5.
为了解破碎围岩分别采用锚杆支护、锚喷支护以及锚喷+锚索耦合三种支护方式下的支护效果,进而为破碎围岩巷道选择合理的支护方式提供参考。通过借助FLAC3D软件建立数值模型,分析不同支护条件下的破碎围岩巷道位移量、应力分布以及塑性区的时空演化特征。结果表明,采用锚喷+锚索耦合支护时,可以较好的控制巷道围岩的位移量、减小应力集中效应、缩小塑性区的影响范围。 相似文献
6.
Yuelong Ma Le Zhang Tianyuan Zhou Bingheng Sun Chen Hou Shunshun Yang Jin Huang Rui Wang Farida A. Selim Zhongying Wang Ming Li Hao Chen Yun Wang 《Journal of the European Ceramic Society》2021,41(4):2834-2846
Ce:Y3Al5O12 transparent ceramics (TCs) with appropriate emission light proportion and high thermal stability are significant to construct white light emitting diode devices with excellent chromaticity parameters. In this work, strategies of controlling crystal-field splitting around Ce3+ ion and doping orange-red emitting ion, were adopted to fabricate Ce:(Y,Tb)3(Al,Mn)5O12 TCs via vacuum sintering technique. Notably, 85.4 % of the room-temperature luminescence intensity of the TC was retained at 150 °C, and the color rendering index was as high as 79.8. Furthermore, a 12 nm red shift and a 16.2 % increase of full width at half maximum were achieved owing to the synergistic effects of Tb3+ and Mn2+ ions. By combining TCs with a 460 nm blue chip, a warm white light with a low correlated color temperature of 4155 K was acquired. Meanwhile, the action mechanism of Tb3+ ion and the energy transfer between Ce3+ and Mn2+ ions were verified in prepared TCs. 相似文献
7.
《Journal of dairy science》2022,105(4):3176-3191
Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital. 相似文献
8.
Ting Cui Ling Xu Feng Ding Ahmed Alsaedi Tasawar Hayat 《International Journal of Adaptive Control and Signal Processing》2020,34(11):1658-1676
Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms. 相似文献
9.
The complexity and spatial heterogeneity of ecosystem processes driving ecosystem service delivery require spatially explicit models that take into account the different parameters affecting those processes. Current attempts to model ecosystem service delivery on a broad, regional scale often depend on indicator-based approaches that are generally not able to fully capture the complexity of ecosystem processes. Moreover, they do not allow quantification of uncertainty on their predictions. In this paper, we discuss a QGIS plug-in which promotes the use of Bayesian belief networks for regional modelling and mapping of ecosystem service delivery and associated uncertainties. Different types of specific Bayesian belief network output maps, delivered by the plug-in, are discussed and their decision support capacities are evaluated. This plug-in, used in combination with firmly developed Bayesian belief networks, has the potential to add value to current spatial ecosystem service accounting methods. The plug-in can also be used in other research domains dealing with spatial data and uncertainty. 相似文献
10.
Susan Sabra Khalid Mahmood Malik Muhammad Afzal Vian Sabeeh Ahmad Charaf Eddine 《Expert Systems》2020,37(1):e12388
Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE. 相似文献