Microstructure design to improve the efficiency of thermal barrier coatings

The insulation effect of ceramic coating in a turbine blade is of great importance for the service of engine in the field of aviation industry. Fabricating microstructure in the thermal barrier coatings(TBCs) is considered to be able to enhance the thermal insulation effect. In this study, the traditional three-layer structure, containing ceramic top coat, bonding coat and substrate, is firstly simplified into a double-layer structure, where only ceramic layer and substrate are left, for analyzing the thermal insulation. Afterwards, the thermal insulation effect of the designed microstructure in the bonding coat of the three-layer structure is further studied. Column-like microstructures, filled with hollow ceramic microspheres in the interspace, are designed to improve the thermal insulation effect. The size parameters of the designed microstructure were optimized. The existence of the designed microstructure can significantly prolong the efficiency of thermal barrier coatings. The insulation temperature between the heating surface and lower surface of the substrate can exceed 300℃ and the thermal balance time has a big improvement of 240 s, more than 50%, than the traditional TBCs structure. Compared with the TBCs structure without microstructure, the designed microstructure can significantly improve the insulation temperature of more than 110℃.

A superconducting wireless energiser based on electromechanical energy conversion

A superconducting magnet(SM)can produce high magnetic fields up to a dozen times stronger than those generated by an electromagnet made of normal conductors or a permanent magnet(PM),and thus has attracted increasing research efforts in many domains including medical devices,large scientific equipment,transport,energy storage,power systems,and electric machines.Wireless energisers,e.g.,high temperature superconducting(HTS)flux pumps,can eliminate the thermal load from current leads and arc erosion of slip rings,and are thus considered a promising energisation tool for SMs.However,the time‐averaged DC output voltage in existing HTS flux pumps is generated by dynamic resistance:the dynamic loss is unavoidable,and the total AC loss will become significant at high frequencies.This study introduces a highly efficient superconducting wireless energizer(SWE)designed specifically for SMs.The SWE takes advantage of the inherent properties of a superconducting loop,including flux conservation and zero DC resistivity.Extensive theoretical analysis,numerical modelling exploiting the H‐ϕformulation,and experimental measurements were conducted to demonstrate the efficiency and efficacy of the novel SWE design.The electromechanical performance and loss characteristics of the SWE system have also been investigated.Compared to conventional HTS flux pumps,the proposed SWE has lower excitation loss,in the order of 10−1 mW,and thus can achieve a high system efficiency of no less than 95%.Furthermore,it has a simpler structure with higher reliability,considered ready for further industrial development.In addition to deepening the understating of the intricate electromechanical dynamics between magnetic dipoles and superconducting circuits,this article provides a novel wireless energisation technique for SMs and opens the way to step changes in future electric transport and energy sectors.

AC loss mitigation for high temperature superconducting coils in wireless power transfer

With the rapid development of high temperature superconducting(HTS)technology,second generation(2G)HTS materials have become a promising alternative to traditional conductive materials in the power transmission industry.Recently,the topic of using HTS materials in wireless power transfer(WPT)systems for electric vehicles(EVs)has attracted widespread attention in the background of net zero transport.With virtually zero DC resistance and superior current‐carrying capacity,HTS materials can achieve high quality factor and power density in the WPT resonant circuits compared to conventional metals,e.g.,copper.However,the optimal working frequency for the conventional WPT system is relatively high in the order of kilohertz level.Superconducting coils working at high frequencies could generate high AC losses,reducing the overall power transfer efficiency(PTE)and increasing the cooling burden.In order to improve the PTE of HTS‐WPT systems,the AC loss mitigation methods for different HTS coil topologies have been investigated in this paper by varying the inter‐turn gap and tape width.Three HTS coil structures,namely the spiral coil,the solenoid coil and the double pancake(DP)coil,have been studied with a 2D axisymmetric multi‐layer numerical model based on the H‐formulation,and the simulation results have been validated by the published experimental data.The general loss characteristics,loss distributions in each turn,as well as magnetic flux densities have been analysed in detail for three types of HTS coils.Moreover,the impact of these two loss reduction methods on the WPT performance has also been evaluated.Findings have shown that increasing the inter‐turn gap and tape width can effectively reduce the AC power losses and increase the PTE of the HTS‐WPT system.The spiral coil demonstrates the highest AC power loss reduction effect and PTE while maintaining a stable level of magnetic fields.This paper is believed to deepen the understanding of superconducting WPT and provide a useful reference for more efficient wireless energisation applications.

N-doped carbon supported Pd catalysts for N-formylation of amines with CO2/H2

Using mesoporous N-doped carbons(NCs)derived from glucose and melamine as the supports,a series of Pd/NC catalysts were prepared,in which Pd nanoparticles with average size<2.0 nm were uniformly distributed on the supports.It was indicated that the resultant Pd/NC catalysts were effective for N-formylation of amines with CO_2and H_2in ethanol without any additives.Especially,the catalyst Pd/NC-800-6.9%containing quaternary N showed the best performance,affording a series of formylamides in good or even excellent yields.Further investigation reveals that the interaction between the Pd nanoparticles and quaternary nitrogen in the NC support was responsible for the good performance of the catalyst.

Sequential protocol for C(sp)-H carboxylation with CO_2:KO^tBu-catalyzed C(sp)-H silylation and KO^tBu-mediated carboxylation

CO_2 incorporation into C-H bonds is an important and interesting topic. Herein a sequential protocol for C(sp)-H carboxylation by employing a metal-free C-H activation/catalytic silylation reaction in conjunction with KO^tBu-mediated carboxylation with CO_2 was established, in which KO^t Bu catalyzes silylation of terminal alkynes to form alkynylsilanes at low temperature, and simultaneously mediates carboxylation of the alkynesilanes with atmospheric CO_2. Importantly, the carboxylation further promotes the silylation, which makes the whole reaction proceed very rapidly. Moreover, this methodology is simple and scalable, which is characterized by short reaction time, wide substrate scope, excellent functional-group tolerance and mild reaction conditions,affording a range of corresponding propiolic acid products in excellent yields in most cases. In addition, it also allows for a convenient ^(13)C-labeling through the use of ^(13)CO_2.

A statistical model for the design of rotary HTS flux pumps based on deep-learning neuron network

Rotory high temperature superconducting(HTS)flux pumps can consistently generate a DC voltage by rotating magnets over superconducting tapes,and thus energize the circuit if a closed loop is formed.The voltage output is a crucial factor to reflect the performance of such an HTS flux pump,which is determined by a set of design specifications,and some of them have been investigated extensively in the current literature.However,no work has been done yet to study the HTS dynamo output voltage by efficiently integrating all the design parameters together.In this paper,a well‐trained deep‐learning neuron network(DNN)with back‐propagation algorithms has been put forward and validated.The proposed DNN is capable of quantifying the output voltage of an HTS dynamo instantly with an overall accuracy of approximately 98%with respect to the simulated values with all design parameters explicitly specified.The model possesses a powerful ability to characterize the output behavior of HTS dynamos by considering multiple design parameters,e.g.,airgap,superconductor tape width,operating frequency,remanent flux density,rotor radius,and permanent magnet width,which have covered all the typical design considerations.The output characteristics of an HTS dynamo against each of the design parameters have been successfully demonstrated using this model.Compared to conventional time‐consuming finite element method(FEM)based numerical models,the proposed DNN model has the advantages of automatic learning,fast computation,as well as strong programmability.Therefore the DNN model can greatly facilitate the design and optimization process for HTS dynamos.An executable application has been developed accordingly based on the DNN model,which is believed to provide a useful tool for learners and designers of HTS dynamos.