Energy Loss Model Research Articles

Power engineering of the tangential supply device of the microturbine of the thermal control system of a promising spacecraft

This paper presents an overview of the current technical problem related to two-phase spacecraft thermal control systems and possible technical applications of thermal energy recovery in the organic Rankine cycle as an integral part of thermal management systems. The design solution involves the integration of a steam microturbine behind an evaporator radiator. The microturbine is a tangential supply device and a radially centripetal impeller of low speed nst40. In this area, there is no reliable data on the design and energy of both the supply device and the impeller. The energy (loss of enthalpy) of the supply device mainly determines the transport of the swirling flow to the impeller and, as a result, the circumferential operation on the turbine. A prototype of a radial microturbine has been developed and presented in order to evaluate the design of the flow part of both the supply device and the impeller. As a result of the analysis, the main determining hydrodynamic areas necessary for hydrodynamic analysis and mathematical elaboration of the flow calculation algorithm with an assessment of energy losses are identified: the flow of a swirling flow of a radial-annular slit; axial-annular slit and tangential supply device. The first two algorithms assume computational modeling, the model of energy losses in a tangential supply device is not amenable to analytical modeling because it includes a sequence (or compatibility) of flows under boundary conditions defined as “local resistances”: the sudden expansion, reversal of the flow, together with a section of radially circumferential flow, the mutual influence of these boundary conditions assumes only an expe rimental assessment of energy losses in a tangential supply device through the loss coefficient of local resistance in the range of changes in geometric and operating parameters. As a result of experimental studies, a database has been proposed on the loss coefficient of tangential microturbine supply devices in the field of the practical range of the existence of operating and design parameters.

Radiofrequency Induction Heating for Green Chemicals Manufacture: A Systematic Model of Energy Losses and a Scale-Up Case-Study.

Radiofrequency (RF) induction heating has generated much interest for the abatement of carbon emissions from the chemicals sector as a direct electrification technology. Three challenges have held back its deployment at scale: reactors must be built from nonconductive materials which eliminates steel as a design choice; the viability of scale-up is uncertain; and to date the reported energy efficiency has been too low. This paper presents a model that for the first time makes a comprehensive analysis of energy losses that arise from RF induction heating. The maximum energy efficiency for radio frequency induction heating was previously reported to be 23% with a typical frequency range of 200-400 kHz. The results from the model show that an energy efficiency of 65-82% is achieved at a much lower frequency of 10 kHz and a reactor diameter of 0.2 m. Energy efficiency above 90% with reactor diameters above 1 m in diameter are predicted if higher voltage radio frequency sources can be developed. A new location of the work coil inside of the reactor wall is shown to be highly effective. Losses arising from heating a steel reactor wall in this configuration are shown to be insignificant, even when the wall is immediately adjacent to the work coil. This analysis demonstrates that RF induction heating can be a highly efficient and effective industrial technology for coupling high energy demand chemicals manufacture electricity from zero carbon renewables.

Research on proportional valve spool wear diagnostic method hybrid-driven by the valve port energy loss mechanism model and data

High performance proportional valves are commonly utilized for precise control of aircraft actuators to ensure flight safety. Fault diagnosis play a crucial role in maintaining equipment reliability. However, traditional diagnostic methods using vibration signals face challenges such as inability to directly measure failure points, fault characteristics being influenced by sensor position, and large data processing volume, limiting engineering application scope. This paper introduces a valve spool wear fault diagnostic method based on energy loss model and data hybrid drive, leveraging throttling loss characteristics. An energy loss failure mechanism model, incorporating differential pressure and flow rate of valve port, was established, and experimentally verified. This method effectively addresses the limitations of vibration sensors in diagnosing aviation hydraulic systems. By combining particle swarm optimization algorithm with deep extreme learning machine, the number of neurons, weight distribution, and data set ratio are rapidly optimized, reducing data processing complexity and enhancing diagnostic efficiency. Comparative tests demonstrate a significant increase in average diagnostic accuracy rate, with more than 8% improvement after integrating energy loss information and particle swarm optimization, reaching over 98%. The proposed method exhibits superior performance in average diagnostic accuracy rate and stability compared to other methods and can be served as a valuable reference for predicting faults in aviation hydraulic valves.

A strategy to assess the use-phase carbon footprint from energy losses in electric vehicle battery

The electric vehicles are not completely emission-free. The vehicles consume power and the power generation processes involve carbon emissions, resulting in indirect vehicle usage carbon emissions. A use-phase carbon emissions assessment can help electric vehicle designers and manufacturers analyze the onboard carbon footprint and mitigate vehicle-related carbon emissions through energy consumption optimization. In this article, we focus on the use-phase carbon footprint based on the energy losses in electric vehicle battery packs. A battery pack energy loss model is established to examine the carbon footprint of four main subsystems of the battery pack, including the energy storage system, thermal management system, and battery junction box. We use the proposed method to evaluate the battery pack use-phase carbon emissions in four different cities from four main continents. The results show that the highest emissions appear in Tokyo (436.2 kgCO2) due to the relatively high greenhouse gas factor on the grid, the London has the lowest 207.5 kgCO2 emissions due to the massive adoption of sustainable energy during power generation. With a similar high greenhouse gas factor, but Sydney shows lower emissions (347.5 kgCO2) compared to Tokyo, which illustrates the closer the annual average temperature to the battery suitable operation range, the lower energy loss happens inside the battery pack due to the low thermal management load and resistance energy loss in the cells. This electric vehicle has the highest energy loss rate (20.8%) in New York, 343.6 kgCO2 emissions, and the highest thermal management system energy losses show the high seasonal temperature difference causing the high thermal management load to maintain the battery temperature. The proposed method can be used for different battery pack configurations and vehicle uses, providing researchers with a robust and versatile use-phase carbon emissions assessment strategy.

Determination of elastic loss of piezoelectric materials by impedance curve fitting using intelligent algorithms

Understanding the loss parameters of piezoelectric materials is crucial for designing effective piezoelectric sensors. Traditional elastic loss parameter measurement techniques mainly rely on three methods: 3 dB bandwidth, impedance fitting, and ultrasonic attenuation. However, the elastic losses obtained through these methods are constant and frequency-independent, which does not align with the actual vibration characteristics of piezoelectric materials. Therefore, there is a need for a fast, accurate, and frequency-dependent method to obtain the elastic loss of piezoelectric materials. This paper introduces an approach that utilizes intelligent algorithms for fitting impedance curve to calculate elastic loss parameters. A frequency-dependent second-order energy loss model for piezoelectric materials is established. Then, a genetic algorithm is introduced to obtain the optimal elastic loss parameters. The results demonstrate a high consistency between theoretical and experimental impedances, with an error less than 5%. The elastic loss parameters obtained through intelligent algorithm-based impedance curve fitting match well with stress experiment results, with an error less than 6%. This method provides a rapid, accurate, and cost-effective way to obtain frequency-dependent second-order elastic loss parameters for piezoelectric materials.

Renewable microgeneration cooperation with base station sleeping-mode strategy for energy-efficient operation of 5G infrastructures

The energy consumption of the mobile network is becoming a growing concern for mobile network operators and it is expected to rise further with operational costs and carbon footprints due to the massive deployment of small cell base stations in 5G and beyond 5G networks. Renewable energy harvesting has proved its extraordinary potential in green mobile communication to reduce energy costs and carbon footprints. However, the stochastic behavior of renewable energy generation and traffic load makes the reliable operation of mobile networks challenging. Therefore, this paper proposes an energy-sustainable framework of cooperative microgeneration energy power supplies for nearby clusters of small cells to maximize the utilization of sustainable energy by intra-microgrid and inter-microgrid energy cooperation. In addition, a resource-on-demand approach of small cells based on advanced sleep modes is integrated with energy cooperation to optimize energy saving and the techno-economic feasibility of microgrids. The proposed solution of microgeneration energy cooperation framework with a resource-on-demand strategy optimally shares surplus energy between microgrids via physically deployed resistive transmission lines under a practical energy loss model and restrains the mismatch between traffic arrival and energy production. Exhaustive simulation is performed to examine the optimal system performance, carbon emissions performance, energy savings, and cost assessment. Results suggest that the proposed solution performs effectively in terms of cost, emissions, and energy savings.

Experimental and numerical studies of the evaporation and combustion characteristics of large-angle impinging sprays

To achieve a large fuel injection mass per cycle, using one injector will need a large nozzle, which may lead to combustion deterioration in high power density (HPD) engines. Therefore, two-injector method was adopted and then impinging sprays by two injectors were developed to promote the air/fuel mixing and combustion performance. This study investigated the spray, evaporation, ignition and soot emission characteristics of twin injectors at different impinging angles (90°, 120°, 150°, and 180°) using various high-speed imaging techniques in a constant volume chamber. Further, CFD simulations were performed to analyze the impinging sprays under HPD condition. Innovatively, a kinetic energy loss model for impinging sprays was proposed to quantify the effect of spray impingement. The results showed that the turbulent kinetic energy increased with the impinging angle, and the kinetic energy loss at any angle could be predicted by the kinetic energy loss of 180° impinging spray. The kinetic energy loss model better characterized the spray impingement process, and then more accurately predicted the atomization quality and mixing capacity compared with spray volume. Spray impingement changed fuel and soot distributions, the peak soot mass decreased with the impinging angle, which was reduced by 36.8 %, 39.8 %, 44.4 % and 45.9 % at 90 ∼ 180° impinging sprays, respectively, comparing to the single spray. These findings recommended that using a large impinging spray angle in real HPD engines can promote spray atomization and reduce soot formation.

One-dimensional pump geometry prediction modeling for energy loss analysis of pumps working as turbines

Pumps as turbine (PAT) for small-scale hydropower, pressure relief valves, and hydro-pumping applications have recently gained popularity. In contrast to conventional turbines, pumps do not have movable guiding vanes to accommodate changes in flow rate and head. This limits their use to the single best operating point. As a result, the precise estimation of reverse mode operating parameters is critical. One of the most successful techniques in this regard is the energy loss model. However, it necessitates extremely detailed pump geometry and experimental data. Although it is claimed to be more accurate, the lack of data makes it impractical. This calls for the devising of a pump geometrical parameter prediction model from limited manufacturer information. Using 137 sets of commercial pump operating data, geometry redesign was carried out by MATLAB code. Following that, multivariate linear regression analysis was carried out, and a one-dimensional geometrical prediction model was developed. Then the result was validated with computational analysis and measurement. The model results were 99 %, 100 %, and 95 % correlated for pump inlet, volute, and throat inlet diameters, respectively, with the experimental results. Similarly, the model results were also 99 %, 71 %, and 89 % correlated for pump inlet, outlet, and volute blade width, respectively, with experimental results. The model gave a more accurate geometrical result than the analytical and numerical methods.

High-pT suppression in small systems

We present first results for leading hadron suppression in small collision systems, from a convolved radiative and collisional pQCD energy loss model which receives a short path length correction to the radiative energy loss. We find that the short path length correction is exceptionally large for light flavor final states at high-pT , for all system sizes. We numerically investigate the self-consistency of various assumptions underlying the radiative energy loss model, in an effort to understand the size of the short path length correction. This calculation shows that the large formation time assumption, which is utilized by most contemporary energy loss models, is invalid for a large portion of the phenomenologically relevant parameter space.

Diagnosis of bound electron density by measuring energy loss of proton beam in partially ionized plasma target

Partially ionized plasma contains the bound electrons, which have an effect on the instability of the plasma. The evolution process of bound electron density cannot be obtained by using the existing optical method used for diagnosing the free electron density. In this work, we carry out a high-precision experiment: the energy loss of a 100 keV proton beam penetrating through the partially ionized hydrogen plasma target is measured on the platform of ion beam-plasma interaction at the Institute of Modern Physics, Chinese Academy of Sciences. The bound electron density is obtained according to the energy loss model of Bethe theory. The free electron density is measured by laser interferometry and the electron tempercture is obtained from the measured spectrum (<i>T</i><sub>e</sub> = 0.68 eV; <i>n</i><sub>fe</sub> = 2.41×10<sup>17</sup> cm<sup>–2</sup>). It is found that the bound electron density decreases during plasma lifetime. The diagnosis of bound electron density by measuring energy loss of ion beam has the advantages of on-line, in-situ and high resolution, thus providing a new way to solve the problem about measuring the bound electron density in partially ionized plasma. A COMSOL simulation reveals that the high-temperature free electrons will be ejected quickly out of the plasma area through a mechanical diaphragm, thus reducing the total number of free electrons. In order to maintain a relatively high degree of ionization in this plasma, in principle, more and more bound electrons are ionized into free electrons, the density of bound electrons decreases correspondingly. The simulation result accords well with our experimental data. Based on this finding, more detailed plasma target parameter is obtained, which is helpful in deepening the understanding of the interaction process between ion beam and plasma. In future, more researches of low low-energy highly-charged ions-plasma interaction will be conducted.

Flow field characteristics and energy loss model of the effective upstream flow region of orifice in liquid jet

Orifice jets commonly adhere to the thick-walled orifice jet mechanism or the thin-walled one, where the difference between the two orifice jet mechanisms is generally considered to be caused after the fluid enters the orifice. However, ignoring the energy loss before entering the orifice could be inaccurate and even misleading. Therefore, we studied the flow behavior in the upstream flow region of thick-walled orifices (small orifices) and thin-walled ones (large ones). Firstly, the concept of the effective upstream flow region of orifice was proposed based on the film theory. It can be simplified into an approximate hemispherical multi-channel parallel contractive flow field. Then, the experiments of the effective upstream flow region were conducted by the streamlined contractive orifices with equivalent energy loss. The proportion of the energy loss before the fluid enters the orifice to the total energy loss was obtained. In addition, the maximum impact range of the effective upstream flow region was remarked by theoretical derivation, and local resistance coefficient functions were established based on the CFD simulation results. Finally, a semi-theoretical model of energy loss in this region was developed. It can quantitatively measure the proportion of increased energy consumption caused by the sucked air inside orifice, well verifying the eddy energy consumption, which provides a scientific exclusion method for predicting the complex form resistance.

Skin Effect and Losses in Soft Magnetic Sheets: From Low Inductions to Magnetic Saturation

High frequencies are ubiquitous in present-day power applications: most electrical equipment, like rotating machines, are supplied by Pulse Width Modulation (PWM) switching inverters, often working at tens or hundreds of kilohertz. PWM is responsible of minor cycles along the major hysteresis loop of the magnetic core, lasting a few microseconds. Such minor loops can cause deep skin effect, even if the thinnest today available laminations (0.1 - 0.2 mm thick sheets) are used. Common mode currents in the megahertz range, flowing from the electrical machine windings to the machine chassis through capacitive effects, can engender strong electromagnetic disturbances and bearing damages. A correct prediction of high frequency phenomena is necessary, for example, for the accurate calculation of common mode filters, requiring a magnetic model of the laminated cores suited to high frequencies and low induction values and the ensuing dramatic skin effect. For power conversion applications, such as embedded planar transformers, the mandatory reduction of volume and cross-sectional area of the core, often made of high-permeability grain-oriented (HGO) sheets, imposes the increase of the conversion frequency from a few hundred hertz to several kilohertz and high peak induction values. The skin effect in this case is affected by the non-linear saturable magnetic response of the material and its treatment requires non-trivial experimental methods and modeling approaches. In this work, we discuss physically based modeling of magnetization process and energy loss in magnetic sheets at high frequencies. We focus first on the low induction regimes occurring in thin non-oriented (NO) Fe-Si laminations. We consider then the case of high inductions, as encountered in power conversion devices using NO, HGO, and Fe-Co alloys, where non-linear models, possibly validated by magneto-optical observations of the domain wall dynamics, are developed and implemented.

Optimal Design of Motor–Pump Parameters for Direct Load-Sensitive EHA Based on Multi-Objective Optimization Algorithm

The electro-hydrostatic actuator (EHA) is a highly integrated and reliable actuation system which has been widely used in aerospace and construction machinery. In addition, the direct load sensitive EHA (DLS–EHA) has been investigated by introducing load-sensitive techniques which can well match the system output and external loads. More importantly, the matching design of motor–pump parameters is an important stage in the pre-design phase of DLS–EHA. For this reason, a multi-objective optimization design method for DLS–EHA motor–pump parameters is proposed in this paper. Firstly, the motor–pump mass and energy loss models are constructed based on similarity criteria. Secondly, the multi-objective particle swarm optimization algorithm (MOPSO) is used to optimize the design of the motor-pump parameters, and the Pareto frontier solutions of the optimized parameters are obtained. Further, the optimal design parameters are selected on the basis of meeting the actual requirements. Finally, the DLS–EHA prototype is designed based on the optimized design parameters and experimental verification is completed. The results of the study show that the optimized design parameters can meet the design requirements. The design method proposed in this paper provides an important theoretical basis for the optimized design of DLS–EHA.

Quantum Dielectric Model for Energy Loss of Particles in Astrophysical Plasmas

We present the results obtained using a novel quantum approach to describe the interaction of charged particles with the astrophysical type of plasmas, based on the dielectric plasma-wave-packet model (PWPM) together with a full description of statistical effects on energy exchange processes. We use this formulation to calculate the energy loss moments for protons, positrons, and electrons traversing different stellar plasmas on a wide range of projectile velocities and plasma densities and temperatures. We consider special quantum restrictions for the cases of positrons and electrons, including relativistic corrections for high-velocity particles. We analyze and compare the results for different cases of main interest, from dilute solar-corona plasma to cases of increasing densities in the interior of the sun and in the dense regions of giant stars.

CIPSO-Based Decision Support Method for Collision Avoidance of Super-Large Vessel in Port Waters

Effective and timely collision avoidance decision support is essential for super-large vessels navigating in port waters. To guarantee the navigational safety of super-large vessels, this work proposes a collision avoidance decision support method based on the curve increment strategy with adaptive particle swarm optimization (CIPSO). Firstly, the objective function is constructed based on the multi-objective optimization method. Here, a fuzzy comprehensive evaluation (FCE)-based vessel collision hazard model and vessel speed-varying energy-loss model integrating the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) are involved. Furthermore, in response to the limitations of the PSO algorithm, which is prone to falling into local optima in the later stages of iteration, a curve increment strategy is incorporated. To improve the performance of the global optimization, it is optimized using a local followed by global search method. The iterative evolution of CIPSO is used to obtain the optimal decision value in the set domain of feasible solutions. Finally, the effectiveness and feasibility of the proposed method are verified by the numerical simulation and large vessel maneuvering simulator, which can provide collision avoidance decision support for ship pilots.

Research on the Optimal Deployment of Expressway Roadside Units under the Fusion Perception of Intelligent Connected Vehicles

At present, there is still a lack of relevant theoretical guidance on the deployment of roadside RSU on expressways. In the face of the coexistence of V2V and V2I communication in the future, the deployment adjustment after the penetration of intelligent vehicles is not considered. Therefore, this paper proposes a roadside RSU deployment income model in consideration of the influence of V2V and V2I communication. Based on the optimal income of roadside RSU nodes, it achieves the optimization of the RSU deployment range and determines the optimal deployment spacing through the forwarding and relaying role of V2V communication so as to achieve cost savings. In terms of RSU coverage of positive income, it considers the impact of intelligent vehicles and reconstructs the traditional information flow–traffic flow coupling theory to innovatively realize the modeling of income within the information life cycle. In terms of the information transmission deficit, the WSN node energy loss model is reconstructed with permeability. Also, in terms of the construction and maintenance costs, the cost models are constructed for different cluster lengths. In order to provide a basis for expressway sensor network deployment, MATLAB software (version R2016B) is used to analyze the three-dimensional relationship between expressway traffic density, intelligent vehicle permeability, and roadside RSU deployment spacing as well as to determine the optimal roadside RSU deployment spacing with the income model. Finally, the model reliability is validated by the Warshell algorithm and the Kmeans clustering algorithm.

Quick Electrical Drive Selection Method for Bus Retrofitting

The article concerns the issue of retrofitting (i.e., the conversion of worn-out diesel buses into electric buses). As this solution is often cheaper than purchasing new electric buses, it can be attractive for low-population areas with a weaker economic infrastructure. The article aims to present an original method for rapidly selecting components for the electric traction system, such as the electric motor, inverter, and transmission systems, combined with a battery installed in a drawer. The battery swapping solution is dedicated to regions with underdeveloped power infrastructure that does not allow for fast charging of bus batteries using pantographs. A mathematical model in the form of a polynomial was developed to estimate the energy losses for a given route. This model consists of a bus physics model, an energy loss model in the propulsion system, and a battery model. The weight coefficients of the polynomials were determined based on an analytical analysis of the model dependencies. The obtained models were reduced using the Lasso regularization method in linear regression. The input data for the model includes route characteristics (or driving cycle) and technical characteristics of the traction system components. The model output provides a detailed profile of electric energy consumption and peak values of the drive system characteristics (e.g., maximum torque of the motor) which must not be exceeded. Implemented as computer software, the model—combined with a database of motors, inverters, drive transmission systems, and batteries—allows for a quick calculation of the possibilities of applying a selected configuration to cover a given route. The approach proposed in the article enables the rapid composition of electric traction devices based on required driving conditions during the initial vehicle prototyping stage. At the same time, it allows the state of the bus battery to be monitored and estimates the remaining range during the operation of upgraded buses.

Study on the milling performance of ball-end milling cutter under the combined action of micro-texture of rake and flank face

PurposeIt was verified that the micro-texture in the front and back of the tool at the same time had a positive effect on improving the milling behavior and surface quality of the tool. The purpose of this study is to explore the rationality of simultaneous placement of micro-textures on the front and rear surfaces of ball-end milling cutters, analyze the influence of micro-texture parameters on tool milling behavior and workpiece surface quality, reveal its internal mechanism, and obtain the best micro-texture parameters by optimization.Design/methodology/approachFirst, the mechanism of micro-texture is studied based on the energy loss model. Second, the orthogonal experiment is designed to analyze the influence of micro-texture parameters on tool milling behavior and reveal its mechanism by combining simulation technology and cutting experiment. Finally, the parameters are optimized based on the artificial bee colony algorithm.FindingsThe results show that the simultaneous placement of micro-texture on the rake face and flank face of the tool has a positive effect on improving the milling behavior and surface quality of the tool. Taking milling force, tool wear and surface roughness as the evaluation criteria, the optimal parameter combination is obtained: the rake face micro-texture diameter is 50 µm, the distance from the micro-texture is 200 µm and the distance from the cutting edge is 110 µm; the diameter of the micro-textured flank is 40 µm, the distance from the micro-texture is 170 µm and the distance from the cutting edge is 130 µm.Originality/valueTaking milling force, tool wear and surface roughness as the evaluation criteria, the optimal parameter combination is obtained: the rake face micro-texture diameter is 50 µm, the distance from the micro-texture is 200 µm and the distance from the cutting edge is 110 µm; the diameter of the micro-textured flank is 40 µm, the distance from the micro-texture is 170 µm and the distance from the cutting edge is 130 µm, which provides theoretical support for the further study of the micro-textured tool.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2023-0022/

Criteria for the deployment of a heterogeneous linear WSN: Operability vs energy efficiency

Linear Wireless Sensor Networks (LWSN) are typically used for monitoring infrastructure systems extending over several kilometers, where propagation conditions can be inhomogeneous in different sections of the network. Obstacles and reflecting objects contribute to bit errors in data packets, which take extra time and energy to recover. However, the impact of the inhomogeneities across LWSN sections on the time and energy performance of the entire network remains underreported. In addition, conventional methods of building LWSN by distributing relay nodes among inhomogeneous sections have failed to balance operability and energy efficiency criteria. This article examines the models of time and energy loss in LWSN sections showing different signal fading, represented by the Rician K-factor in the expressions for the bit error probability. On the basis of the dependences of time losses on inter-node distances, algorithms for deploying a heterogeneous LWSN are proposed according to the criterion of minimizing end-to-end network delay without restrictions on hardware and energy resources or when distributing a limited number of nodes. As an alternative to the efficiency criterion, we propose algorithms for balancing power consumption in a heterogeneous LWSN at an acceptable level of power loss without limiting the number of nodes or at the lowest level of power loss with a limit on the number of nodes. Experiments were carried out on CC2500 TI node transceivers in five inhomogeneous LWSN sections, where K-factor ranges from 5 to 100, in order to demonstrate the efficiency of the proposed algorithms. Results showed that the end-to-end delay and energy loss can be reduced by 1.36 and 2.4 times, respectively, compared to those in networks with uniformly distributed nodes. To further assess the operability and energy efficiency of the algorithms, a scheme is proposed based on the ratio of normalized concessions in the Pareto region. Additionally, the optimal number of nodes is determined when selecting a rational algorithm for deploying a heterogeneous LWSN.

Influences of Metal Core and Carbon Shell on the Microwave Absorption Performance of Cu-C Core-Shell Nanoparticles.

Metal-C core-shell nanoparticles have been recently demonstrated to be promising candidates for microwave absorption applications. However, the underlying absorption mechanism, such as the contributions of the metal cores and C shells on their absorption performance, remains far from clear due to the complicated interfaces and synergetic effects between metal cores and C shells, as well as the significant challenges in the preparation of samples with well-defined comparability. In this study, Cu-C core-shell nanoparticles and their derivatives, i.e., bare Cu and hollow C nanoparticles, were synthesized for a comparative study on their microwave absorption properties. Electric energy loss models of the three samples were established, and based on these models, the comparative study suggested that the polarization loss could be significantly improved by C shells, and Cu cores had negligible influences on the conduction loss of Cu-C core-shell nanoparticles. The interface between C shells and Cu cores tuned the conduction loss and polarization loss to establish improved impedance matching and achieve optimal microwave absorption performances. A wide effective bandwidth of 5.4 GHz and a low reflection loss of -42.6 dB were achieved for Cu-C core-shell nanoparticles. This work provides new insights into how metal nanocores and C nanoshells affect the microwave absorption of core-shell nanostructures from experimental and theoretical points of view, which has reference values for the construction of highly efficient metal-C-based absorbers.