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Electroreduction of CO2 to C2+ products provides a promising strategy for reaching the goal of carbon neutrality. However, achieving high selectivity of C2+ products at high current density remains a challenge. In this work, we designed and prepared a multi‐sites catalyst, in which Pd was atomically dispersed in Cu (Pd−Cu). It was found that the Pd−Cu catalyst had excellent performance for producing C2+ products from CO2 electroreduction. The Faradaic efficiency (FE) of C2+ products could be maintained at approximately 80.8 %, even at a high current density of 0.8 A cm−2 for at least 20 hours. In addition, the FE of C2+ products was above 70 % at 1.4 A cm−2. Experiments and density functional theory (DFT) calculations revealed that the catalyst had three distinct catalytic sites. These three active sites allowed for efficient conversion of CO2, water dissociation, and CO conversion, ultimately leading to high yields of C2+ products. [ABSTRACT FROM AUTHOR]

Catalytic conversion of CO2 to produce fuels and chemicals is of great importance, and the electrocatalytic CO2 reduction reaction (eCO2RR) is considered one of the most attractive pathways. Multi-carbon (C2+) products are more desirable in many cases. To date, Cu-based catalysts, especially Cu+ sites, have been found to be the most efficient for the production of C2+ products. However, the retention of Cu+ sites at high cathodic potentials in the eCO2RR remains a great challenge. In this study, we designed and synthesized CuAl-oxide-derived (CuxAly-OD, x and y are the mass percentages of Cu and Al) catalysts for the eCO2RR to C2+ products. During the eCO2RR process, the predominant Cu species changed to Cu+, and the resulting electrocatalyst showed a high faradaic efficiency (FE) of 81.6% for C2+ products in alkaline aqueous solutions. Experimental studies showed that the presence of a stable amorphous Al2O3 phase stabilized the Cu+ sites by oxidation state control, leading to high selectivity and activity for the production of C2+ products. This work provides a strategy for improving the stability of Cu+ in the catalyst to enhance the performance of the eCO2RR. [ABSTRACT FROM AUTHOR]

Electroreduction of CO2 into valuable chemicals and fuels is a promising strategy to mitigate energy and environmental problems. However, it usually suffers from unsatisfactory selectivity for a single product and inadequate electrochemical stability. Herein, we report the first work to use cationic Gemini surfactants as modifiers to boost CO2 electroreduction to formate. The selectivity, activity and stability of the catalysts can be all significantly enhanced by Gemini surfactant modification. The Faradaic efficiency (FE) of formate could reach up to 96 %, and the energy efficiency (EE) could achieve 71 % over the Gemini surfactants modified Cu electrode. In addition, the Gemini surfactants modified commercial Bi2O3 nanosheets also showed an excellent catalytic performance, and the FE of formate reached 91 % with a current density of 510 mA cm−2 using the flow cell. Detailed studies demonstrated that the double quaternary ammonium cations and alkyl chains of the Gemini surfactants played a crucial role in boosting electroreduction CO2, which can not only stabilize the key intermediate HCOO* but also provide an easy access for CO2. These observations could shine light on the rational design of organic modifiers for promoted CO2 electroreduction. [ABSTRACT FROM AUTHOR]

Aiming at reducing the effect of time delay on the control performance of magnetorheological (MR) damper semi-active suspension, a control strategy with strong robustness to time delay is investigated in this study, including the force controller of MR damper, the robust controller and the predictive compensator. The force controller of MR damper is built based on the hyperbolic tangent function; the robust controller is built based on the simplified model of car body lateral vibration and is designed by μ-synthesis method considering the effect of time delay; then the Smith predictive model and the lateral velocity predictor are designed, which form the predictive compensator of semi-active controller to reduce the effect of time delay. To validate the effectiveness of the proposed control strategy, several conventional semi-active controllers are designed as comparative objects. The simulation results show that the proposed semi-active control strategy can maintain good performance when time delay is in the range of 0–100 ms and has better robustness to time delay compared with the conventional control strategy. [ABSTRACT FROM AUTHOR]

Modulation of the microenvironment on the electrode surface is one of the effective means to improve the efficiency of electrocatalytic carbon dioxide reduction (eCO2RR). To achieve high conversion rates, the phase boundary at the electrode surface should be finely controlled to overcome the limitation of CO2 solubility in the aqueous electrolyte. Herein, we developed a simple and efficient method to structure electrocatalyst with a superhydrophobic surface microenvironment by one‐step co‐electrodeposition of Cu and polytetrafluoroethylene (PTFE) on carbon paper. The super‐hydrophobic Cu‐based electrode displayed a high ethylene (C2H4) selectivity with a Faraday efficiency (FE) of 67.3 % at −1.25 V vs. reversible hydrogen electrode (RHE) in an H‐type cell, which is 2.5 times higher than a regular Cu electrode without PTFE. By using PTFE as a surface modifier, the activity of eCO2RR is enhanced and water (proton) adsorption is inhibited. This strategy has the potential to be applied to other gas‐conversion electrocatalysts. [ABSTRACT FROM AUTHOR]

The use of semiconductor nanoparticle heterojunctions for photocatalytic activities is a very attractive strategy. TiO2/CdS is widely used in the photocatalytic degradation of pollutants, but there are few reports on photocatalytic hydrogen production and CO2 reduction. In this work, rod and fishbone CdS nanoparticles were prepared by the hydrothermal method, and S-scheme TiO2/CdS nanoparticles with sea urchin morphology were designed. With Na2S and Na2SO3 as sacrifice agents, the H2 yield of TiO2/CdS was 1.07 mmol·h–1·g–1, and with [Ru-(bpy)3]-Cl2·6H2O as the photosensitizer and TEOA as the sacrifice agent, the rate of CO production from CO2 reduction was 47.67 μmol·h–1·g–1. The preparation rates of H2 and CO were 9 times and 13.3 times for TiO2 nanoparticles and 3.1 times and 1.7 times for fishbone CdS/TiO2 composite particles, respectively. The electron transfer path and photocatalytic mechanism were deduced by EPR, TRPL, UPS, etc. The results showed that the construction of the S-scheme heterojunction enhanced the photocatalytic performance of the catalyst. We synthesized the S-scheme TiO2/CdS nanoparticle heterojunction for the first time and applied it to the photocatalytic production of H2 and reduction of CO2. This work provides an effective reference for designing high-performance inorganic S-scheme heterojunction catalysts. [ABSTRACT FROM AUTHOR]

To study the braking performance of linear eddy current brake (LECB) for high-speed maglev trains, experimental studies are usually carried out using a track wheel with a finite radius and a track wheel eddy current brake (TWECB) with a certain radius of curvature. However, the geometrical differences between the two braking methods due to the track radius will lead to differences in their effective excitation air gap during operation. Therefore, the excitation air gap model and eddy current braking force model of TWECB and LECB are developed in this study. Through the excitation air gap model and eddy current braking force model proposed in this paper, the difference in braking performance between TWECB and LECB in the velocity domain and operating air gap domain can be obtained for different track radii. The correctness of the finite element analysis (FEA) method is verified by experimental data, and the eddy current density, braking force and air gap flux density formed by eddy current braking at different track radii are analysed using the finite element method. The results show that an appropriate test track radius can significantly improve the accuracy of TWECB in estimating the braking performance of LECB. [ABSTRACT FROM AUTHOR]

The hunting motion of the vehicle increases the wear of the wheel tracks and affects the lateral stability of the vehicle system and safety, so the hunting motion of the vehicle needs to be recognized. However, the existing recognition methods ignore the small-amplitude hunting motion that precedes the onset of the running motion. In addition, due to the scarcity of real hunting data of high-speed trains, there is a problem of underfitting when training with traditional deep learning methods. In this paper, first, the dynamics model of a high-speed train is established, and the normal, small-amplitude hunting and hunting motions of high-speed trains in the process are simulated. Second, this paper proposes a transfer learning-based method for high-speed train hunting motion recognition. The method uses easily collected normal data samples in the training process, does not use real data samples of small-amplitude hunting and hunting motions, and completes the high-speed train running motions recognition task by transferring from simulation data (source domain) to real data (target domain). Finally, the validation is carried out using the real data, which proves that the method-related approach has some engineering application value in the intelligent monitoring of high-speed trains. [ABSTRACT FROM AUTHOR]

Electrochemical reduction reaction of carbon monoxide (CORR) offers a promising way to manufacture acetic acid directly from gaseous CO and water at mild condition. Herein, we discovered that the graphitic carbon nitride (g‐C3N4) supported Cu nanoparticles (Cu−CN) with the appropriate size showed a high acetate faradaic efficiency of 62.8 % with a partial current density of 188 mA cm−2 in CORR. In situ experimental and density functional theory calculation studies revealed that the Cu/C3N4 interface and metallic Cu surface synergistically promoted CORR into acetic acid. The generation of pivotal intermediate −*CHO is advantage around the Cu/C3N4 interface and migrated *CHO facilitates acetic acid generation on metallic Cu surface with promoted *CHO coverage. Moreover, continuous production of acetic acid aqueous solution was achieved in a porous solid electrolyte reactor, indicating the great potential of Cu−CN catalyst in the industrial application. [ABSTRACT FROM AUTHOR]

Traction motor's rolling element bearings are one of the most critical components for the structural health monitoring of high-speed train vehicles. Most structural health monitoring techniques for railway rolling element bearings are using vibration signal. However, the vibration characteristic of cage defect is difficult to be transmitted to external monitoring point owing to the location of cage in bearing. Hence, the cage defect of Railway Traction Motor Bearing (RTMB) is usually difficult to be recognized with motor housing vibration acceleration signal. Considering Induction Motor (IM) itself a sensor, the mechanical imbalance of bearing cage defect can reflect in stator current through the motor gap magnetic field rather than a solid transmission path. A novel strategy with stator current for monitoring the traction motor bearing cage health status in High-Speed Train (HST) is proposed in this paper. This method requires no additional sensor in the practical application. To prove the strategy is feasible and more effective than vibration-based method for the cage fault diagnosis of RTMB, a comprehensive experiment investigation with a real railway traction motor of a HST is completed. Artificial cage defects are processed on bearings at both ends of the induction motor, respectively. Three high-speed (≥250 km/h) conditions are observed. The data analysis results show that vibration-based method is almost invalid at high-speed condition and the proposed current-based method is feasible and effective for the fault diagnosis of high-speed railway traction motor bearing cage. [ABSTRACT FROM AUTHOR]

Amorphous nano-metal catalysts often exhibit appealing catalytic properties, because the intrinsic linear scaling relationship can be broken. However, accurate control synthesis of amorphous nano-metal catalysts with desired size and morphology is a challenge. In this work, we discover that Cu(0) could be oxidized to amorphous CuxO species by supercritical CO2. The formation process of the amorphous CuxO is elucidated with the aid of machine learning. Based on this finding, a method to prepare Cu nanoparticles with an amorphous shell is proposed by supercritical CO2 treatment followed by electroreduction. The unique feature of this method is that the size of the particles with amorphous shell can be easily controlled because their size depends on that of the original crystal Cu nanoparticles. Moreover, the thickness of the amorphous shell can be easily controlled by CO2 pressure and/or treatment time. The obtained amorphous Cu shell exhibits high selectivity for C2+ products with the Faradaic efficiency of 84% and current density of 320 mA cm−2. Especially, the FE of C2+ oxygenates can reach up to 65.3 %, which is different obviously from the crystalline Cu catalysts. Amorphous metal catalysts often exhibit appealing catalytic properties, however, accurate control synthesis of amorphous nano-metal catalysts is a challenge. Here, the authors report a feasible strategy to prepare the amorphous Cu catalysts by supercritical CO2 treatment followed by electroreduction. The resulted catalyst shows high selectivity towards multi-carbon products for CO2 electroreduction. [ABSTRACT FROM AUTHOR]

Methanol is a highly desirable product of CO2 electroreduction due to its wide array of industrial applications. However, the development of CO2-to-methanol electrocatalysts with high performance is still challenging. Here we report an operationally simple in situ dual doping strategy to construct efficient CO2-to-methanol electrocatalysts. In particular, when using Ag,S-Cu2O/Cu as electrocatalyst, the methanol Faradaic efficiency (FE) could reach 67.4% with a current density as high as 122.7 mA cm−2 in an H-type cell using 1-butyl-3-methylimidazolium tetrafluoroborate/H2O as the electrolyte, while the current density was below 50 mA cm−2 when the FE was greater than 50% over the reported catalysts. Experimental and theoretical studies suggest that the anion S can effectively adjust the electronic structure and morphology of the catalysts in favor of the methanol pathway, whereas the cation Ag suppresses the hydrogen evolution reaction. Their synergistic interactions with host material enhance the selectivity and current density for methanol formation. This work opens a way for designing efficient catalysts for CO2 electroreduction to methanol. Production of methanol from CO2 electroreduction is attractive but achieving high selectivity, current density and stability simultaneously remains a grand challenge. Here, the authors present an in situ dual doping strategy to construct efficient CO2-to-methanol electrocatalysts. [ABSTRACT FROM AUTHOR]

Novel durian-like TiO2@CdS core-shell particles were synthesized through a solvothermal method in ethylenediamine solution and the obtained nanocomposites were characterized by scanning electron microscopy (SEM), powder X-ray diffraction (XRD), and transmission electron microscopic (TEM) techniques. It can be seen from the characterization that the synthesized core-shell structured particles show uniform size. The possible formation mechanism of TiO2@CdS core-shell particles is also presented schematically. CdS grows on the TiO2 surface in the form of nanorods, turning the TiO2@CdS composite particles into durian-like structures. The durian-like TiO2@CdS core-shell particles prepared in the experiment can overcome the disadvantages of TiO2 and CdS, respectively. They not only produce a higher yield of H2 than pure TiO2; the durian-like TiO2@CdS nanostructures formed at 180 °C for 16 h produced 2.5 times as much H2 as did TiO2, also showing enhanced stability as compared with pure CdS. [ABSTRACT FROM AUTHOR]

Developing electrocatalytic reactions with high‐efficiency can make important contributions to carbon neutrality. However, poor long‐term stability of catalysts is a bottleneck for its practical application. Herein, an "in situ periodic regeneration of catalyst (PR‐C)" strategy is proposed to give long‐term high efficiency of CO2 electroreduction to generate C2+ products over Cu catalyst by applying a positive potential pulse for a short time periodically in the halide‐containing electrolyte. The high Faradaic efficiency (81.2 %) and current density (22.6 mA cm−2) could be maintained completely at least 36 h, while the activity and selectivity decreased continuously without using the PR‐C method. Control experiments and operando characterization demonstrated that the surface structure and oxidation state of Cu could be recovered periodically by the PR‐C method, which was beneficial for CO2 activation and C−C coupling. [ABSTRACT FROM AUTHOR]

Traditional control algorithm of shutting down the air ducts for a fixed period is not applicable to take both the riding comfort and the air quality inside high-speed train carriages into account in long tunnels. Inspired by the morphological similarity of the tunnel pressure waves generated by the same train passes through the same tunnel, an upgraded iterative learning control algorithm for suppressing the air pressure variation excited by the quasi-periodic varying-amplitude tunnel pressure wave is developed. Firstly, the mathematical model of the control system is established, in which the air ducts, gaps and random interferences are considered. Then, the methodology of determining the goal in each iteration is formed, and the implementation of the iterative learning control algorithm is discussed. Finally, simulations of the algorithm are carried out. The simulation results show that in the upgraded iterative learning control algorithm, both the goal and the output of the air pressure inside the carriage will converge into a range determined by the amplitude and random interferences. By comparing with the traditional control algorithm, the upgraded iterative learning control algorithm is more adaptable to meet the needs of riding comfort. [ABSTRACT FROM AUTHOR]

Based on the characteristics that the tunnel pressure wave has a fixed-morphologic form when the same train passes through the same tunnel, an applicational approach based on the iterative learning control (ILC) is developed, aiming at overcoming the drawbacks of the traditional strategy for controlling the air pressure variation inside a high-speed train carriage. To achieve the goal, the control system is mathematically modelled. Then, the problem is formulated. The task of suppressing the influence of the tunnel pressure wave on the air pressure inside the carriages is shifted as an ILC problem of tracking the comfort index with varying trial length. The algorithm of refreshing the control signal from trial to trial is determined and the process of ILC control is designed. Next, the convergence of the newly-developed applicational ILC algorithm is discussed and the algorithm is simulated by the simulation signal and field-test signal. Results show that the applicational ILC algorithm be more adaptable in handling the control of the air pressure inside carriage under the excitation of varying-amplitude, varying-scale and varying-initial-states tunnel pressure wave. Meanwhile, the matching with tunnel pressure wave makes the applicational ILC algorithm will take both the riding comfort and fresh air into consideration, which upgrades the performances when the high-speed train passing through long tunnels. [ABSTRACT FROM AUTHOR]

Electroreduction of CO2 into valuable fuels and feedstocks offers a promising way for CO2 utilization. However, the commercialization is limited by the low productivity. Here, we report a strategy to enhance the productivity of CO2 electroreduction by improving diffusion of CO2 to the surface of catalysts using porous organic cages (POCs) as an additive. It was noted that the Faradaic efficiency (FE) of C2+ products could reach 76.1 % with a current density of 1.7 A cm−2 when Cu‐nanorod(nr)/CC3 (one of the POCs) was used, which were much higher than that using Cu‐nr. Detailed studies demonstrated that the hydrophobic pores of CC3 can adsorb a large amount of CO2 for the reaction, and the diffusion of CO2 in the CC3 to the nanocatalyst surface is easier than that in the liquid electrolyte. Thus, more CO2 molecules make contact with the nanocatalysts in the presence of CC3, enhancing CO2 reduction and inhibiting generation of H2. [ABSTRACT FROM AUTHOR]

Electrochemical reduction of CO2 by renewable electricity offers a promising way to settle excessive greenhouse gases and achieve carbon neutrality under a mild environment. Cu-based catalysts have a unique catalytic activity towards multicarbon (C2+) products in the CO2 electroreduction reaction and are widely studied to promote the corresponding selectivity and activity. Here we report a F-doped Cu (F–Cu) catalyst to improve C2+ products in CO2 electroreduction. A high C2+ product (mainly ethylene and ethanol) faradaic efficiency of 70.4% was achieved on the F–Cu catalyst with a high current density (above 400 mA cm−2) in the flow-cell system. The in situ surface enhanced Raman spectroscopy results and electrochemical performance analysis demonstrated that CO2 could be reduced into CO at low potentials and the adsorption of CO could be strengthened on F–Cu, which is beneficial to the subsequent C–C coupling step and formation of the C2+ products. [ABSTRACT FROM AUTHOR]

To break through the limitation of conventional iterative learning control algorithm (ILC) that requires a fixed target, a new ILC algorithm is designed for tracking the varying-amplitude but morphologically similar targets. First, the problem is formulated, in which the tracking target is selected as varying-amplitude and biased-measured. Then, the process of the ILC algorithm based on a variable-gain-proportional-integral scheme is discussed, in which the magnitude coefficient is defined and calculated by orthogonal projection and utilised to redefine the error and build the refreshment algorithm of the input. Next, the convergence of the algorithm is analysed and the applicational simulation is conducted. Results show that the new ILC algorithm has the ability in dealing with the trajectory of the varying but morphologically similar target and the applicational scenario of the ILC algorithm is expanded. [ABSTRACT FROM AUTHOR]