It is still a challenge to realize the dream of a hydrogen-based economy using a robust catalyst for overall water splitting. Here, we introduce two-dimensional MoN/MoO2 heterostructure nanosheets using nickel foam as a substrate for water splitting. The heterojunction formation was achieved through the partial nitriding of a Mo-based precursor to MoN in the annealing process under NH3 environment. The heterogeneous interface between MoN and MoO2 as active sites is supposed to improve the surface reaction kinetics and electronic conductivity. Therefore, an excellent performance is achieved when MoN/MoO2 is employed as both cathode and anode electrocatalysts; the corresponding cell voltages are 1.57 and 1.84 V at 10 and 100 mA cm-2 in 1 M KOH, respectively. The promising bifunctional catalytic performance of our catalyst opens up a new way for efficient electrochemical water splitting.
Fine tuning the structure of bimetallic nanoparticles is critical toward understanding structure–activity relationships and further improving the catalytic performance in propane dehydrogenation (PDH). Excessive Fe species in the PtFe bimetallic catalysts promote carbon deposition leading to low propylene selectivity, and it remains challenging to synthesize well-defined PtFe catalysts while selectively eliminating the excessive Fe. Herein, we show that the formation of coke can be significantly inhibited by introducing CO2 into the PDH over PtFe catalysts, where CO2 effectively eliminates the active Fe(0) coking sites without changing the catalytic surface structure of the PtFe alloy. With a CO2/C3H8 feeding ratio of 0.20, the Pt1Fe7/S-1 catalyst shows the highest propylene production rate and decreased amount of coke from 18.8 to 1.0 wt % compared with dehydrogenation without CO2. X-ray absorption spectroscopy, X-ray photoelectron spectroscopy, and 57Fe Mössbauer results indicate that it is the oxidation of excessive unalloyed Fe species during the CO2-PDH reaction, instead of the reverse Boudouard reaction (CO2 + C = 2CO), that significantly inhibits the carbon deposition. This work provides a promising strategy for tuning the structure of PtFe bimetallic catalysts under reaction conditions and improving the performance of the PDH reaction.
Particle size is an important parameter of supported catalysts, but understanding the size-performance relationship is a challenge, especially in some complicated process. In this contribution, the particle size effect on CO2 hydrogenation to hydrocarbons over iron-based catalysts was deconvoluted into the effects on primary and secondary reactions. With a particle size range of 2.5–12.9 nm, the overall selectivity of C2+ hydrocarbons increases continuously, while that of CO decreases with the increasing size. The reverse water gas shift (RWGS) reaction and methanation are the main primary reactions and they are more sensitive within a particle size range of 6.1–12.9 nm. The formation of formate species is more favored, and thereby more CH4 is produced as a primary product on larger particles. The secondary process, the further hydrogenation of primary CO to hydrocarbons, is more sensitive within the particle size range of 2.5–9.8 nm, where the geometric effect or ensemble effect on larger particles leads to a higher chain-growth probability. More terrace sites may be conducive for C–C coupling, and the enhanced CO adsorption also benefits the secondary process. These findings highlight the deconvoluted particle size effect on CO2 hydrogenation and provide a dimension for understanding the catalysts in complicated reaction networks.
The hydrogenation of CO 2 to CH 4 can realize the utilization of CO 2 , which has an important implications to both the energy and environment. As a result of the low catalytic activity of the supported Ni/SiO 2 catalyst, the ZrO 2 is added to improve its catalytic performance by the impregnation method. The experimental results show that ZrO 2 is an effective promoter to enhance the low-temperature catalytic activity of Ni/SiO 2 catalyst.
Aiming at some shortcomings of the genetic algorithm to solve the path planning in a global static environment, such as a low efficiency of population initialization, slow convergence speed, and easy-to-fall-into the local optimum, an improved genetic algorithm is proposed to solve the path planning problem. Firstly, the environment model is established by using the grid method; secondly, in order to overcome the difficulty of a low efficiency of population initialization, a population initialization method with directional guidance is proposed; finally, in order to balance the global and local optimization searching and to speed up the solution speed, the proposed non-common point crossover operator, range mutation operator, and simplification operator are used in combination with the one-point crossover operator and one-point mutation operator in the traditional genetic algorithm to obtain an improved genetic algorithm. In the simulation experiment, Experiment 1 verifies the effectiveness of the population initialization method proposed in this paper. The success rates in Map 1, Map 2, Map 3, and Map 4 were 56.3854%, 55.851%, 34.1%, and 24.1514%, respectively, which were higher than the two initialization methods compared. Experiment 2 verifies the effectiveness of the genetic algorithm (IGA) improved in this paper for path planning. In four maps, the path planning is compared with the five algorithms and the shortest distance is achieved in all of them. The two experiments show that the improved genetic algorithm in this paper has advantages in path planning.
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