Relaxation Matching Research Articles

Facile Recycling of Waste Biomass for Preparation of Hierarchical Porous Carbon with High-Performance Electromagnetic Wave Absorption.

Hierarchical-porous-structured materials have been widely used in the field of electromagnetic wave (EMW) absorption, playing a critical role in minimizing EMW interference and pollution. High-quality EMW absorbers, characterized by a lower thickness, lighter weight, wider absorption band, and stronger absorption capacity, have been instrumental in reducing damage and preventing malfunctions in the automotive and aviation industries. The utilization of discarded nut shells through recycling can not only alleviate environmental problems but relieve resource constraints. Herein, a facile method for the preparation of hierarchical porous biomass carbon derived from abandoned Xanthoceras Sorbifolium Bunge Shell (XSS) biomass was developed for high-performance EMW absorption. The porous structures of XSS biochar were studied by using different levels of the K2CO3 activator and simple carbonization. The effect of K2CO3 on the EMW parameters, including the complex permittivity, complex permeability, polarization relaxation, and impedance matching, was analyzed. The best EMW absorption performance of the XSS biochar was observed at a mass ratio of activator-to-biomass of 2:1. A minimum reflection loss (RLmin) of -38.9 dB was achieved at 9.12 GHz, and a maximum effective absorption bandwidth (EABmax) of up to 3.28 GHz (14.72~18.0 GHz) could be obtained at a 1.8 mm thickness. These results demonstrated that hierarchical porous XSS carbon was prepared successfully. Simultaneously, the prepared XSS biochar was confirmed as a potential and powerfully attractive EMW-absorbing material. The proposal also provided a simple strategy for the development of a green, low-cost, and sustainable biochar as a lightweight high-performance absorbing material.

Matching the building footprints of different vector spatial datasets at a similar scale based on one-class support vector machines

Automatic matching of multisource data is an important technique for achieving change detection, fusion and updating spatial data. However, most current learning methods for building footprint matching require a large number of samples, and labeling these samples is costly in terms of labor and time. Moreover, multisource building footprint data are complex and diverse leading to recognizing the different matching relationships is a hard task. Thus, this study proposes a learning-based method for recognizing multisource building footprints matching relationships by using a one-class support vector machine (OCSVM). The OCSVM was trained using only positive samples. First, a set of geometric indicators was designed to train a model and realize initial matching recognition. Then, a contextual metric was calculated based on the rough matching results, and geometric and contextual metrics were combined to train the model and realize relaxed matching recognition. Relaxed matching is an optimization process implemented after initial matching to recognize more relaxed matching relationships. In relaxed matching, a convex hull is used to recognize matching relationships besides 1:1, such as 1:n, m:1 and m:n. The experimental results showed that the proposed method outperformed indicator-weighted (weighted average) and learning-based matching methods, such as traditional SVMs and decision trees (DTs). The precision scores of the proposed model were 97.1%, 95% and 97.2% for the Wuhan (China), Beijing (China) and Richmond Hill (Canada) datasets, respectively. Furthermore, the proposed model identified the matching relationships of buildings with complex geometric features and high-density spatial distributions.

MnFe2O4/polyaniline/diatomite composite with multiple loss mechanisms towards broadband absorption.

The research and development of absorbing materials with high absorbing capacity, wide effective absorption bandwidth, and lightweight has always been interesting. In this research, a facile hydrothermal method was used to prepare MnFe2O4, and the grain size of MnFe2O4 decreased with increasing hydrothermal temperature. When the size of MnFe2O4 nanoparticles is less than 10nm, its quantum size effect and surface effect make its electromagnetic microwave absorption performance greatly optimized. When the thickness of MnFe2O4-110 °C is 2.57mm, the minimum reflection loss (RLmin) is -35.28 dB. Based on this, light porous diatomite and a three-dimensional polyaniline network are introduced. Diatomite is used as the base material to effectively reduce the agglomeration of MnFe2O4 quantum dots. The relatively high surface area introduced by a three-dimensional network of polyaniline promotes the orientation, interfacial polarization, multiple relaxation, and impedance matching, thereby generating further dielectric loss. Additionally, the magnetic properties of manganese ferrite and the strong electrical conductivity of polyaniline play an appropriate complementary role in electromagnetic wave absorption. The RLmin of MnFe2O4/PANI/diatomite is -56.70 dB at 11.12GHz with an absorber layer thickness of 2.57mm. The effective frequency bandwidth (RL < -10 dB) ranges from 9.21 to 18.00GHz. The absorption mechanism indicates that the high absorption intensity is the result of the synergistic effect of impedance matching, conduction losses, polarization losses, and magnetic losses.

Dense, 11 V-Tolerant, Balanced Stimulator IC with Digital Time-Domain Calibration for 100 nA Error.

This article presents a multichannel neurostimulator implementing a novel charge balancing technique to achieve maximal integration. Safe neurostimulation demands accurate charge balancing of the stimulation waveforms to prevent charge build-up on the electrode-tissue interface. We propose digital time-domain calibration (DTDC), which adjusts the second phase of the biphasic stimulation pulses digitally, based on a one-time characterization of all stimulator channels with an on-chip ADC. Accurate control of the stimulation current amplitude is loosened in exchange for time-domain corrections, relieving circuit matching constraints and consequentially saving channel area. A theoretical analysis of DTDC is presented, establishing expressions for the required time resolution and the new, relaxed circuit matching constraints. To validate the DTDC principle, a 16-channel stimulator was implemented in 65 nm CMOS, requiring only 0.0141 mm 2 area/channel. Despite being implemented in a standard CMOS technology, 10.4 V compliance is achieved for compatibility with high-impedance microelectrode arrays typical for high-resolution neural prostheses. To the authors' knowledge, this is the first stimulator in a 65 nm low-voltage process achieving over 10 V output swing. Measurements after calibration show the DC error is successfully reduced below 96 nA on all channels. Static power consumption is 20.3 µW/channel.

Ultrafine Vacancy-Rich Nb2O5 Semiconductors Confined in Carbon Nanosheets Boost Dielectric Polarization for High-Attenuation Microwave Absorption

The integration of nano-semiconductors into electromagnetic wave absorption materials is a highly desirable strategy for intensifying dielectric polarization loss; achieving high-attenuation microwave absorption and realizing in-depth comprehension of dielectric loss mechanisms remain challenges. Herein, ultrafine oxygen vacancy-rich Nb2O5 semiconductors are confined in carbon nanosheets (ov-Nb2O5/CNS) to boost dielectric polarization and achieve high attenuation. The polarization relaxation, electromagnetic response, and impedance matching of the ov-Nb2O5/CNS are significantly facilitated by the Nb2O5 semiconductors with rich oxygen vacancies, which consequently realizes an extremely high attenuation performance of − 80.8 dB (> 99.999999% wave absorption) at 2.76 mm. As a dielectric polarization center, abundant Nb2O5–carbon heterointerfaces can intensify interfacial polarization loss to strengthen dielectric polarization, and the presence of oxygen vacancies endows Nb2O5 semiconductors with abundant charge separation sites to reinforce electric dipole polarization. Moreover, the three-dimensional reconstruction of the absorber using microcomputer tomography technology provides insight into the intensification of the unique lamellar morphology regarding multiple reflection and scattering dissipation characteristics. Additionally, ov-Nb2O5/CNS demonstrates excellent application potential by curing into a microwave-absorbing, machinable, and heat-dissipating plate. This work provides insight into the dielectric polarization loss mechanisms of nano-semiconductor/carbon composites and inspires the design of high-performance microwave absorption materials.

Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching

Offline imitation learning (IL) promises the ability to learn performant policies from pre-collected demonstrations without interactions with the environment. However, imitating behaviors fully offline typically requires numerous expert data. To tackle this issue, we study the setting where we have limited expert data and supplementary suboptimal data. In this case, a well-known issue is the distribution shift between the learned policy and the behavior policy that collects the offline data. Prior works mitigate this issue by regularizing the KL divergence between the stationary state-action distributions of the learned policy and the behavior policy. We argue that such constraints based on exact distribution matching can be overly conservative and hamper policy learning, especially when the imperfect offline data is highly suboptimal. To resolve this issue, we present RelaxDICE, which employs an asymmetrically-relaxed f-divergence for explicit support regularization. Specifically, instead of driving the learned policy to exactly match the behavior policy, we impose little penalty whenever the density ratio between their stationary state-action distributions is upper bounded by a constant. Note that such formulation leads to a nested min-max optimization problem, which causes instability in practice. RelaxDICE addresses this challenge by supporting a closed-form solution for the inner maximization problem. Extensive empirical study shows that our method significantly outperforms the best prior offline IL method in six standard continuous control environments with over 30% performance gain on average, across 22 settings where the imperfect dataset is highly suboptimal.

Hydrangea-like N-doped Carbon/MoO2@SnS2 microspheres with Schottky contact: A multi-interface heterostructure for high-performance microwave absorption

Heterointerface engineering is now recognized as a powerful strategy to optimize the microwave absorption performance of dielectric materials through composition adjustment and structural design. Herein, a hydrangea-like N-doped Carbon/MoO2@SnS2 (NC/MoO2@SnS2) composite was successfully prepared by high-temperature pyrolysis and oil bath treatment. The surface of each NC/MoO2 microsphere was vertically covered with interconnected SnS2 nanosheets, forming a porous core-shell morphology. We found that the number of heterojunctions and the proportion of high-lossy phases played a decisive role in optimizing the electromagnetic parameters. By regulating the content of dielectric phases, the optimized NC/MoO2@SnS2 (S3 sample) displayed a minimum reflection loss (RLmin) of −75.0 dB at an ultrathin thickness of 1.41 mm and a wide EAB of 4.2 GHz at 1.53 mm. The enhanced microwave absorption was mainly ascribed to multiple polarization relaxation, multi-interface reflection and good impedance matching characteristics produced by this semiconductor/carbon heterostructure with dual Schottky barriers. Therefore, this work provided a feasible strategy for making full use of heterointerface engineering to design ternary semiconductor/carbon heterostructures as high-performance dielectric MAMs.

Minimizing emissions from grid-based hydrogen production in the United States

Low-carbon hydrogen could be an important component of a net-zero carbon economy, helping to mitigate emissions in a number of hard-to-abate sectors. The United States recently introduced an escalating production tax credit (PTC) to incentivize production of hydrogen meeting increasingly stringent embodied emissions thresholds. Hydrogen produced via electrolysis can qualify for the full subsidy under current federal accounting standards if the input electricity is generated by carbon-free resources, but may fail to do so if emitting resources are present in the generation mix. While use of behind-the-meter carbon-free electricity inputs can guarantee compliance with this standard, the PTC could also be structured to allow producers using grid-supplied electricity to qualify subject to certain clean energy procurement requirements. Herein we use electricity system capacity expansion modeling to quantitatively assess the impact of grid-connected electrolysis on the evolution of the power sector in the western United States through 2030 under multiple possible implementations of the clean hydrogen PTC. We find that subsidized grid-connected hydrogen production has the potential to induce additional emissions at effective rates worse than those of conventional, fossil-based hydrogen production pathways. Emissions can be minimized by requiring grid-based hydrogen producers to match 100% of their electricity consumption on an hourly basis with physically deliverable, ‘additional’ clean generation, which ensures effective emissions rates equivalent to electrolysis exclusively supplied by behind-the-meter carbon-free generation. While these requirements cannot eliminate indirect emissions caused by competition for limited clean resources, which we find to be a persistent result of large hydrogen production subsidies, they consistently outperform alternative approaches relying on relaxed time matching or marginal emissions accounting. Added hydrogen production costs from enforcing an hourly matching requirement rather than no requirements are less than $1 kg−1, and can be near zero if clean, firm electricity resources are available for procurement.

Digital surface model generation from aerial imagery using bridge probability relaxation matching

Optical image dense matching is a crucial step in the process of generating digital surface models (DSMs). Many existing dense matching methods have adopted pixelwise matching strategy and have achieved precise matching results; however, the methods are time consuming and have limited efficiency in high surveying and mapping production. We introduce a bridge probability relaxation matching method for automatic DSM generation. The method adopts a coarse-to-fine hierarchical strategy and achieves high matching accuracy and fast processing speed simultaneously. This method builds a self-adaptive disparity surface model in a local area and constrains the disparity surface using the spatial relationship between feature points and adjacent pixels. Finally, the disparity is optimized by calculating the increment of the relaxation iteration probability. Experiments are based on different areas with different textures and terrain types. Compared with the DSMs derived from semi-global matching, our proposed approach achieves high levels of accuracy and efficiency in automatic DSM generation.

Constructing 3D Tent-Like frameworks in melamine hybrid foam for superior microwave absorption and thermal insulation

Taking serious electromagnetic pollution and practical application requirements into consideration, it’s imperative to develop multifunctional microwave absorption materials. In this work, the phenol–formaldehyde resin (PF) successfully adheres to melamine–formaldehyde foam (MF) as three-dimensional (3D) porous frameworks, and subsequently the substrate anchors few-layered MXene nanosheets by dripping-squeeze-drying procedures. According to the results, the hollow tent-like structure of MXene/PF@MF (MPM) shows a significant effect on microwave absorption capability, including extending heterogeneous interfaces for polarization relaxation and prolonging microwave propagation paths for energy dissipation. Based on the synergy of multiple components and rational structure, MPM exhibits a minimum reflection loss (RLmin) value of −58.8 dB at 2.2 mm and achieves an effective absorption bandwidth (EAB) of 6.74 GHz covering the entire Ku band. The microwave absorption mechanism reveals that the superior microwave absorption capability results from high conduction loss, polarization relaxation, multiple attenuations, and appropriate impedance matching. Furthermore, the MPMs possess lightweight features (32.7–48.7 g cm−3) and low thermal conductivity (0.0309–0.0318 W m−1 K−1) benefitting the unique 3D porous structure. Meanwhile, the low thermal conductivity endows MPMs with infrared stealth, which broadens the application in military fields. This work proposes a facile strategy for constructing highly efficient microwave absorbers with multiple functions.

A Compact Single-Ended Inverter-Based Transceiver With Swing Improvement for Short-Reach Links

This paper presents a compact single-ended inverter-based transceiver with swing improvement for short-reach links. The low output impedance of the transmitter enlarges the output swing and the eye size to overcome large single-ended noise while relaxed impedance matching provides good signal integrity. For good area efficiency, the proposed transmitter utilizes an inverter driver which is much smaller than the conventional source-series termination driver and thus occupies only <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$42.5 ~\mu \text{m}^{2}$ </tex-math></inline-formula> . By taking the advantage of a large signal swing, the receiver consists of only four slicers and latches to minimize area overhead and to simplify the design. The transceiver was fabricated in 28-nm CMOS technology and tested at supply voltage of 1.13 V. The transmitter achieved a large output swing of 850 mV, which is 50.4 % larger than the conventional source-series termination transmitter. At the far-end of a channel consisting of a 1 m SMA cable and a 17 mm printed circuit board trace, the transmitter achieved eye openings of 440 mV and 234 mV at 16 Gb/s (−2.7 dB) and 20 Gb/s (−8 dB), respectively. Even with a large switching noise of 100 mV, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-situ</i> eye at the receiver was measured 114 mV with 7.4 dB loss.

Flat-optics generation of broadband photon pairs with tunable polarization entanglement.

The concept of "flat optics" is quickly conquering different fields of photonics, but its implementation in quantum optics is still in its infancy. In particular, polarization entanglement, strongly required in quantum photonics, is so far not realized on "flat" platforms. Meanwhile, relaxed phase matching of "flat" nonlinear optical sources enables enormous freedom in tailoring their polarization properties. Here we use this freedom to generate photon pairs with tunable polarization entanglement via spontaneous parametric downconversion (SPDC) in a 400-nm GaP film. By changing the pump polarization, we tune the polarization state of photon pairs from maximally entangled to almost disentangled, which is impossible in a single bulk SPDC source. Polarization entanglement, together with the broadband frequency spectrum, results in an ultranarrow (12 fs) Hong-Ou-Mandel effect and promises extensions to hyperentanglement.

Efficient parallel edge-centric approach for relaxed graph pattern matching

Prior algorithms on graph simulation for distributed graphs are not scalable enough as they exhibit heavy message passing. Moreover, they are dependent on the graph partitioning quality that can be a bottleneck due to the natural skew present in real-world data. As a result, their degree of parallelism becomes limited. In this paper, we propose an efficient parallel edge-centric approach for distributed graph pattern matching. We design a novel distributed data structure called ST that allows a fine-grain parallelism, and hence guarantees linear scalability. Based on ST, we develop a parallel graph simulation algorithm called PGSim. Furthermore, we propose PDSim, an edge-centric algorithm that efficiently evaluates dual simulation in parallel. PDSim combines ST and PGSim in a Split-and-Combine approach to accelerate the computation stages. We prove the effectiveness and efficiency of these propositions through theoretical guarantees and extensive experiments on massive graphs. The achieved results confirm that our approach outperforms existing algorithms by more than an order of magnitude.

Gene Regulatory Network Inference as Relaxed Graph Matching

Bipartite network inference is a ubiquitous problem across disciplines. One important example in the field molecular biology is gene regulatory network inference. Gene regulatory networks are an instrumental tool aiding in the discovery of the molecular mechanisms driving diverse diseases, including cancer. However, only noisy observations of the projections of these regulatory networks are typically assayed. In an effort to better estimate regulatory networks from their noisy projections, we formulate a non-convex but analytically tractable optimization problem called OTTER. This problem can be interpreted as relaxed graph matching between the two projections of the bipartite network. OTTER's solutions can be derived explicitly and inspire a spectral algorithm, for which we provide network recovery guarantees. We also provide an alternative approach based on gradient descent that is more robust to noise compared to the spectral algorithm. Interestingly, this gradient descent approach resembles the message passing equations of an established gene regulatory network inference method, PANDA. Using three cancer-related data sets, we show that OTTER outperforms state-of-the-art inference methods in predicting transcription factor binding to gene regulatory regions. To encourage new graph matching applications to this problem, we have made all networks and validation data publicly available.

Relaxed Current Matching Requirements in Highly Luminescent Perovskite Tandem Solar Cells and Their Fundamental Efficiency Limits.

Perovskite-based tandem solar cells are of increasing interest as they approach commercialization. Here we use experimental parameters from optical spectroscopy measurements to calculate the limiting efficiency of perovskite–silicon and all-perovskite two-terminal tandems, employing currently available bandgap materials, as 42.0% and 40.8%, respectively. We show luminescence coupling between subcells (the optical transfer of photons from the high-bandgap to low-bandgap subcell) relaxes current matching when the high-bandgap subcell is a luminescent perovskite. We calculate that luminescence coupling becomes important at charge trapping rates (≤106 s–1) already being achieved in relevant halide perovskites. Luminescence coupling increases flexibility in subcell thicknesses and tolerance to different spectral conditions. For maximal benefit, the high-bandgap subcell should have the higher short-circuit current under average spectral conditions. This can be achieved by reducing the bandgap of the high-bandgap subcell, allowing wider, unstable bandgap compositions to be avoided. Lastly, we visualize luminescence coupling in an all-perovskite tandem through cross-section luminescence imaging.

Excellent microwave absorbing properties of ZnO/ZnFe2O4/Fe core-shell microrods prepared by a rapid microwave-assisted hydrothermal-chemical vapor decomposition method

To enhance the poor microwave absorption capabilities (MACs) of pure ZnO since its impedance mismatching and lack of magnetic loss ability, ZnO/ZnFe2O4/Fe core-shell microrods (CSMRs) and microflowers (CSMFs) were respectively fabricated by microwave hydrothermal-chemical vapor deposition and hydrothermal-chemical vapor deposition. The morphology, composition and resulting properties of as-prepared samples were affected by different deposition temperatures (Td) and Fe(CO)5 volumes. Due to the synergy of Fe(CO)5 adsorption and decomposition, the Fe/Zn ratio was controlled by varying Td from 300 °C to 500 °C, which conveniently modulated the static magnetic properties and MACs of ZnO/ZnFe2O4/Fe CSMRs and CSMFs. Results showed that the optimal reflection loss (RL) value was −46.88 dB at 6.88 GHz with absorber thickness as thin as 2.2 mm. When the RL was below −20 dB, 15.15 GHz was covered. The rod shaped heterostructure could be formed due to the presence of magnetic particles with Fe core/ZnFe2O4 shell embedding, promoting the orientation and interfacial polarizations, multiple relaxation and proper impedance matching. Our findings suggest that ZnO/ZnFe2O4/Fe CSMRs are a type of promising absorber material with high-performance MACs, broad bandwidths and thin thicknesses.

Preparation and Microwave Absorption Properties of NixSy/PVDF Nanocomposites

Octahedral NixSy nanoparticles and NixSy/PVDF nanocomposites are successfully prepared by solvothermal method. The electromagnetic absorption performance of NixSy/PVDF with different filling concentrations is investigated in the range of 2-18 GHz. An optimal reflection loss value of −32.75 dB at 10.48 GHz is achieved for the filled with concentration of 20 wt%, and the bandwidth less than −10 dB can reach up to 4.48 GHz with a thickness of 3 mm. Furthermore, fundamental mechanisms for absorbing is discussed, it is found that the interface polarization, electric dipole polarization, Debye relaxation and impedance matching are the main factors affecting the absorption performance of NixSy/PVDF.

ORTHOPHOTO SHADOW DETECTION METHOD UNDER ARTIFICIAL SHADOW

Abstract. Shadows are ubiquitous in high-resolution images, especially in urban regions where there are more serious shadow occlusions. In order to improve the detection effect of shadows, this paper analyzes the characteristics and properties of shadows in orthophotos, and proposes an orthophoto shadow detection method under artificial shadow. Firstly, the shadow modeling tool is used to calculate the shadow regions (i.e. artificial shadow) caused by the building obstructing the sun's rays. Secondly, the relaxation matching algorithm is extended by the position and the shape of the shadow polygon as characteristic constraints. The relaxation matching algorithm is extended by the position and shape as shadow polygon’s characteristic constraints. Thirdly, the feature constraint value is calculated which between the shadow polygons of the two images. The correlation coefficient is used to obtain the initial probability value of each shadow polygon in the orthophoto. Finally, the optimal solution is obtained by continuous correction and iteration of the initial probability value. The method performs an overall matching of the two images and obtains the position of the shadow regions of the buildings in the orthophoto image. Experiment shows that this method reduces the mismatch rate and improves the matching accuracy. This method can detect shadow regions of buildings in orthophoto quickly and efficiently.

Spectroscopic Comparison of Thermal Transport at Organic-Inorganic and Organic-Hybrid Interfaces Using CsPbBr3 and FAPbBr3 (FA = Formamidinium) Perovskite Nanocrystals.

Thermal transport across interfaces depends on the matching of vibrational structure at the interface. This work examines the transfer of thermal excitation from an organic ligand coating to either all-inorganic cesium lead tribromide (CsPbBr3) nanocrystals or hybrid organic-inorganic formamidinium lead tribromide (FAPbBr3) nanocrystals using selective infrared optical excitation. These two semiconductors are directly compared because they (or similar semiconductors) are currently envisioned as strong candidates in many optoelectronic technologies and they differ due to the presence of an organic or inorganic cation, which introduces substantial differences in the phonon density of states in otherwise quite similar semiconductors. Infrared excitation of C-H vibrations of surface-bound ligands generates a temperature gradient between the organic ligand shell and nanocrystal core, which results in heat flow, measured by probing changes of the semiconductor band gap. Heat transfer to both perovskite compositions of comparable sizes is similar (25-30 ps), due to fast intramolecular vibrational relaxation and similar matching of low-energy phonons with the organic ligand, but FAPbBr3 samples show a slow bleaching kinetic on the order of 1 ns. This slow, heat-induced change in the semiconductor band gap is attributed not to interfacial heat transfer but instead to thermal equilibration between the organic and inorganic sublattices of FAPbBr3. Ab initio molecular dynamics simulations support the hypothesis that low-energy inorganic sublattice phonon modes are populated initially in the heat transfer process, with a slow thermal population of the higher-energy phonon modes associated primarily with the organic cation. Slow thermal equilibration of FAPbBr3 is likely to substantially impact the time-dependent response of optoelectronic devices that heat the semiconductor active layer and provide further evidence that the poor bulk thermal transport of hybrid perovskite materials extends to microscopic thermal processes.

Plasmon resonance strategy to enhance permittivity and microwave absorbing performance of Cu/C core-shell nanowires

Single crystalline ultralong Cu/C core-shell nanowires (CSNWs) with a diameter of 70–190 nm, a shell thickness of 5–40 nm and a length of up to 100 μm have been synthesized in a high yield via a hydrothermal-carbonthermal reduction method. The phase structure, C shell thickness and core diameter of Cu/C CSNWs can handily be tuned via changing sintering temperate (Ts), acetone volume (V) and the molar ratios of Cu(Ac)2 to pyrrole (δ). The microwave absorption performance (MAP) was used to optimize the synthetic process and structure of Cu/C CSNWs. The optimal MAP was exhibited by Cu/C CSNWs with the diameter of 110 ± 20 nm, C shell thickness of 5–8 nm and C/Cu mass ratio of 0.051 to 0.61 produced at Ts = 600 °C, δ = 6 and V = 0–1 mL. The effective bandwidth (RL ≤ –10 dB) showed the maximal value of 6.28 GHz, corresponding to a sample thickness of 2.4 mm. The minimum RL value of −46.6 dB was reached at 17.3 GHz with a sample thickness of 2.0 mm. The superior MAP is ascribed to the synergy of Plasmon resonance enhanced permittivity, dual dielectric relaxation, high attenuation and good impedance matching. In this way, the new strategy for Plasmon resonance enhance permittivity and microwave absorbing performance to solve electromagnetic (EM) pollution problems are undoubtedly opened up.