Electrocatalytic synthesis of C–N coupling compounds from CO2 and nitrogenous species

The authors gratefully acknowledge financial support from the National Natural Science Foundation of China (Nos. 42277485, 21976141, 22272197, 22102184, 22102136, andU22A20392), the Natural Science Foundation of Hubei Province (2022CFB1001 and 2021CFA034), the Department of Education of Hubei Province (Q20221701 and Q20221704), and the Joint Fund of Yulin University and Dalian National Laboratory for Clean Energy (YLU-DNL Fund 2022008).The electrocatalytic synthesis of C–N coupling compounds from CO2 and nitrogenous species not only offers an effective avenue to achieve carbon neutrality and reduce environmental pollution, but also establishes a route to synthesize valuable chemicals, such as urea, amide, and amine. This innovative approach expands the application range and product categories beyond simple carbonaceous species in electrocatalytic CO2 reduction, which is becoming a rapidly advancing field. This review summarizes the research progress in electrocatalytic urea synthesis, using N2, NO2−, and NO3− as nitrogenous species, and explores emerging trends in the electrosynthesis of amide and amine from CO2 and nitrogen species. Additionally, the future opportunities in this field are highlighted, including electrosynthesis of amino acids and other compounds containing C–N bonds, anodic C–N coupling reactions beyond water oxidation, and the catalytic mechanism of corresponding reactions. This critical review also captures the insights aimed at accelerating the development of electrochemical C–N coupling reactions, confirming the superiority of this electrochemical method over the traditional techniques.publishersversionpublishe

Review on Dimensionless Numbers Relevant for Polymer Electrolyte Fuel Cells

With the concern about global warming, air pollution and energy security, the prospect of using polymer electrolyte fuel cells (PEFCs) in future sustainable and renewable energy conversion systems has achieved substantial momentum. Dimensionless numbers can be determined before construction of a model is started, to make simple estimations on the transport processes, for example, within the porous PEFC GDL. Microstructural parameters, such as tortuosities and contact angles, are frequently treated as fitting parameters used in the respective governing equations, such that unrealistic values could be assumed or properties could not be representative of the corresponding microstructure. This treatment can be avoided if the origin of the expression is clearly clarified and if geometric properties are not used for fitting. Instead, it is recommended to, when needed, introduce parameters, without a geometrical meaning used only for fitting the model to experimental data, such as the pre-exponential factor in the advanced microstructural approach

SOFC Cathode Design Optimization using the Finite Element Method

Solid oxide fuel cells (SOFCs) are promising as an energy producing device, which at this stage of development will require extensive analysis and benefit from numerical modeling at different time- and length scales. A 3D model is developed based on the finite element method (FEM), using COMSOL Multiphysics, of a single SOFC operating at an intermediate temperature range. Ion, electron, heat, gas-phase species and momentum, transport equations are implemented and coupled to the kinetics of the electrochemical and internal reforming reactions. High current density spots were identified in our previous work, at positions where the electron transport distance is short and the oxygen concentration is high. The electron transport especially within the cathode is found to be limiting for the electrochemical reactions at positions far from the channel walls (interconnect). New cathode designs are proposed, for the cathode/air channel interface, to be able to reduce the maximum electron current density (decreasing the ohmic polarization due to electron transport), i.e., to increase the fuel utilization, with constant inlet conditions, compared to a standard approach. The two cases with a modified cathode structure presents 1 % higher average ion current density as well as 1 % higher fuel utilization, keeping the inlet conditions similar

Parametric study for electrode microstructure influence on SOFC performance

A solid oxide fuel cell (SOFC) is a clean and high-efficiency energy conversion device, which undergoes improvement of performance continuously. The transport of gas species and charges proceed in the porous electrodes. The porous electrodes are also responsible for the removal of exhaust gases. In this paper, a fully coupled 3D single-channel multiphysics computational fluid dynamics (CFD) model was developed based on the finite element method (FEM). The governing equations for momentum, species, charges, and heat transport were solved by a segregated solver. The impact of decreased ionic, electronic, and pore phase tortuosity on the SOFC performance such as fuel utilization, current density, activation overpotential and temperature distribution are analyzed and compared with the base case. In addition to the tortuosity investigation, the volume fraction of the electronic phase in the active layer and the support layer is also investigated using a parametric sweep study. Of all the decreased tortuosity cases, there is an increase in ionic current density and temperature compared with the base case. Except for a decreased pore tortuosity, all other cases led to an increase of electronic current density compared with the base case. The consumption of hydrogen increased for all cases compared with the base case. The activation overpotential increased with decreased electronic phase and pore phase tortuosity, while a decrease of ionic phase tortuosity caused a decrease. Finally, when decreasing all phase tortuosity, both current density, temperature, activation overpotential, and hydrogen consumption increased. For the parametric sweep, there is an optimum electronic phase volume fraction value. This work allows for a better understanding of the relationship between the microstructure and performance of SOFCs. Meanwhile, it provides theoretical guidance for a better porous electrode design

Solid Oxide Fuel Cell Interconnect Design Optimization considering the Thermal Stresses

The mechanical failure of solid oxide fuel cell (SOFC) components may cause cracks with consequences such as gas leakage, structure instability and reduction of cell lifetime. A comprehensive 3D model of the thermal stresses of an anode-supported planar SOFC is presented in this work. The main objective of this paper is to get an interconnect optimized design by evaluating the thermal stresses of an anode-supported SOFC for different designs, which would be a new criterion for interconnect design. The model incorporates the momentum, mass, heat, ion and electron transport, as well as steady-state mechanics. Heat from methane steam reforming and water–gas shift reaction were considered in our model. The results examine the relationship between the interconnect structures and thermal stresses in SOFC at certain mechanical properties. A wider interconnect of the anode side lowers the stress obviously. The simulation results also indicate that thermal stress of coflow design is smaller than that of counterflow, corresponding to the temperature distribution. This study shows that it is possible to design interconnects for an optimum thermal stress performance of the cell

Impact of water drop presence on diffusion parameters of PEFC gas diffusion layers

A polymer electrolyte fuel cell (PEFC) produces electrical energy thanks to the electrochemical reaction carried out inside the cell. During the energy conversion, water molecules are also produced in the cathode side and this can affect the diffusion parameters of the gas diffusion layers (GDLs). The generated water-drops due to the reaction may block the reactant gases and produce material oxidation. The mentioned phenomena influence the performance of the PEFCs. This paper aims to describe and quantify the impact on diffusion parameters of GDLs when the presence of formed water-drops inside the layer is considered. This study considers digitally generated GDLs, and the parameters considered are porosity, gas-phase tortuosity and diffusibility. The fluid flow behavior through the three-dimensional porous domain representing the GDL is obtained by using the lattice Boltzmann method (LBM). Depending on the water-drop size, the impact over the mentioned parameters can be computed. For the current study, a single water-drop has been placed into the GDL domain and its impact has been analyzed

Performance experimental data of a polymer electrolyte fuel cell considering the variation of the relative humidity of reactants gases

The data collected in this article is based on a performance test of a polymer electrolyte fuel cell (PEFC). The behavior the different parameters of a PEFC is analyzed considering different aspects relative to the inlet gases temperatures. The fuel cell was evaluated by means of a current sweep at different percentages of relative humidity between the feed gas and the cell. The relative humidity values were established by means of the temperature setting. The data presented show the experimental response of the cell in real time, which can be used to perform a depth analysis or they can be a starting point for material and performance investigation. In addition, charts presenting the voltage and power density behavior as a function of the volumetric flows of the anode (H2) as well as cathode (O2). The data presented in this article are originally from our research performed in [1]

Performance of a polymer electrolyte fuel cell considering the variation of the relative humidity of reactants gases (dataset)

The data shows the real-time performance of a Polymer Electrolyte Fuel Cell considering the variation in the relative humidity of the reactive gases

Research on the Construction of a Knowledge Graph and Knowledge Reasoning Model in the Field of Urban Traffic

The integration of multi-source transportation data is complex and insufficient in most of the big cities, which made it difficult for researchers to conduct in-depth data mining to improve the policy or the management. In order to solve this problem, a top-down approach is used to construct a knowledge graph of urban traffic system in this paper. First, the model layer of the knowledge graph was used to realize the reuse and sharing of knowledge. Furthermore, the model layer then was stored in the graph database Neo4j. Second, the representation learning based knowledge reasoning model was adopted to implement knowledge completion and improve the knowledge graph. Finally, the proposed method was validated with an urban traffic data set and the results showed that the model could be used to mine the implicit relationship between traffic entities and discover traffic knowledge effectively