Conductance Fluctuations Research Articles

Decreases in Sympathetic Activity Due to Low-Intensity Extremely Low-Frequency Electric Field Treatment Revealed by Measurement of Spontaneous Fluctuations in Skin Conductance in Healthy Subjects

Decreases in Sympathetic Activity Due to Low-Intensity Extremely Low-Frequency Electric Field Treatment Revealed by Measurement of Spontaneous Fluctuations in Skin Conductance in Healthy Subjects

Measurements of fluctuation-induced in-plane magneto-conductivity of granular aluminum film

The phenomenon of Berezinskii–Kosterlitz–Thouless (BKT) phase fluctuations and the superconducting fluctuations is investigated in a 40 nm thick granular aluminum film using magneto-transport measurements. The transport measurements suggest the possibility of strong electron–phonon (el–ph) interactions in contrast to a Bardeen–Cooper–Schrieffer superconductor. It shows a BKT transition of 2.304 K and a superconducting mean-field transition at 2.32 K. The presence of the resistive tail even before the BKT transition reflects the abundance of thermally activated free vortices. By analyzing the excess conductivity, Gaussian–Ginzburg–Landau superconducting fluctuations are observed above the superconducting transition, which causes rounding of the transition region even before the superconducting transition. The temperature dependence of the fluctuation conductivity in zero magnetic field exhibits distinct signatures of the two-dimensional direct Aslamazov–Larkin theory, with a significant contribution from the Maki–Thompson (MT) model. Furthermore, the anomalous behavior of the fluctuation conductivity at higher temperatures and perpendicular magnetic fields (up to 700 mT) is explained in terms of the total-energy cutoff (=0.72) in the low-wavelength region of the superconducting fluctuations and a pair-breaking parameter (∼0.031). Further studies on the pair-breaking parameter indicate the presence of the el–ph scattering, which diminishes the MT contribution. Our study carries important bearings on how the BKT phase fluctuations and superconducting amplitude fluctuations control the conductivity of granular superconductor near and above the transition region as non-equilibrium properties of weakly disordered granular superconductors. This research is of significance, offering insights into the fundamental properties of granular superconductivity and aiding in the comprehension of nano-structured thin film devices.

Antimony-mediated few-layer metallic MoSe2 with rich selenium vacancies for ultrafast sodium/potassium storage

Transition metal dichalcogenides with sandwich structure possess high theoretical capacity, while face the challenge of inferior inherent electronic conductivity and dramatic volume fluctuation during cycling, lessening their fascination for electrochemical energy storage material applications. Herein, we report a crystal phase modulation strategy to modulate the electronic structure by doping cation (Sb) into the few-layer 2H-phase MoSe2 lattice, thereby implants abundant selenium vacancies and expands the layer spacing, which transforms it into a 1T-phase (T-MoSe2/C-1). The few-layer 1T-MoSe2 nanosheets are confined within chlorella-derived N, P-doped bio-carbon, endowing T-MoSe2/C-1 with a rock-solid structure, rapid Na+/K+ transport kinetics, and high reversibility. Density functional theory calculations confirm that the antimony atoms in T-MoSe2/C-1 system significantly increase the electronic conductivity, decrease the Na+/K+ diffusion barrier and reinforce the adsorbed capability for Na+/K+. Consequently, the T-MoSe2/C-1 achieves a reversible capacity of 540 mAh/g at 0.5 A/g and delivers as high as 333 mAh/g even at a high rate of 25 A/g for SIBs. As the anode of PIBs, it maintains a stable capacity of 210 mAh/g after 1,000 cycles at 5 A/g. This study provides a new horizon on the phase regulation of transition metal dichalcogenides (TMDs) to improve sodium/potassium-ions storage.

Cost-effective production of Titania nanoparticles for the modification of transformer insulating oil

Nanofluids are prospective solutions for improving the transformer dielectric strengthby adding nanoparticles to the standard oils used in transformers.Oil-based titania nanofluids are becoming increasingly popular due to their superior insulating qualities and distinctive thermal performance, and they areconsideredas possible replacements in the domains of transformer insulating oils.This paper describes the industrial synthesis of titania nanoparticles for improving the insulating characteristics of virgin oil used in transformers.The titania nanoparticles were analyzed using an X-ray diffractogram (XRD), which revealed a prominent peak at Bragg angle 25O, indicating that the titania nanoparticles were generated in the anatase phase. Fourier transform infrared (FTIR) spectroscopy study endorsed the formation of Ti-O-Ti, Ti-OH, C-H and O-H stretching vibrations at 760 cm−1, 1345 cm−1, 2475 cm−1, and 3646 cm−1 wavenumbers respectively. Field emission scanning electron microscopy (FESEM) and Atomic Force Microscopy (AFM) examinations on the produced titania nanoparticles revealed that the particles had a circular shape with a diameter of 55 nm and an average roughness value of roughly 3.6 nm respectively.The viscosity of the host virgin oil and the nanoparticles-filled nanofluid were examined, and higher viscosity values were found as particle concentration increased.The effective conductivity study with the zeta potential and thermal conductivity fluctuation with temperature variation also revealed that at higher temperatures, conductivity with the zeta potential increased and thermal conductivity dropped. Furthermore, the breakdown strength of the titania nanoparticles-based virgin oil was observed to be effectively increased with the particle concentration.

Electrical conductivity fluctuations as a tracer to determine time-dependent transport characteristics in hyporheic sediments

Assessing solute transport in riverbed sediments is important for quantifying the effective reactivity of hyporheic sediments and the magnitude of exchange flows between rivers and their river beds. A typical approach of estimating transport in riverbed sediments is by measuring natural tracers such as fluctuations of temperature or electrical conductivity (EC) and fitting models to them that assume time-independent travel time distributions, implying steady-state flow. Here, we use a transport parameterization that is based on the advection–dispersion equation (ADE) with coefficients that continuously vary in time. The ADE is solved numerically and its solution is fitted to measured EC time series using Bayesian parameter inference. A continuous function of model parameters is constructed by smoothly interpolating between point values with different temporal resolution, and Tikhonov regularization is used to avoid spurious parameter fluctuations. The approach is tested using EC time series synchronously measured in river water and hyporheic porewater of two urban rivers in Germany and one urban river in South Australia. For all datasets the goodness of fit was improved by introducing a time-dependent EC offset. Estimated porewater velocities were highly transient in three out of the four datasets with values increasing by up to a factor of six over the course of a day. Flux transients were likely related to both variations of hydraulic gradients along and spatial shifting of flow paths. Comparison to stationary, non-parametric deconvolution indicated that transient flow may induce multimodality in stationary travel time distributions. Given the high temporal dynamics of transport in the streambed sediments of the three investigated urban rivers, we envision that the presented model is also a valuable tool to improve the assessment of reactive transport in riverbed sediments.

General Relations between Stress Fluctuations and Viscoelasticity in Amorphous Polymer and Glass-Forming Systems.

Mechanical stress governs the dynamics of viscoelastic polymer systems and supercooled glass-forming fluids. It was recently established that liquids with long terminal relaxation times are characterized by transiently frozen stress fields, which, moreover, exhibit long-range correlations contributing to the dynamically heterogeneous nature of such systems. Recent studies show that stress correlations and relaxation elastic moduli are intimately related in isotropic viscoelastic systems. However, the origin of these relations (involving spatially resolved material relaxation functions) is non-trivial: some relations are based on the fluctuation-dissipation theorem (FDT), while others involve approximations. Generalizing our recent results on 2D systems, we here rigorously derive three exact FDT relations (already established in our recent investigations and, partially, in classical studies) between spatio-temporal stress correlations and generalized relaxation moduli, and a couple of new exact relations. We also derive several new approximate relations valid in the hydrodynamic regime, taking into account the effects of thermal conductivity and composition fluctuations for arbitrary space dimension. One approximate relation was heuristically obtained in our previous studies and verified using our extended simulation data on two-dimensional (2D) glass-forming systems. As a result, we provide the means to obtain, in any spatial dimension, all stress-correlation functions in terms of relaxation moduli and vice versa. The new approximate relations are tested using simulation data on 2D systems of polydisperse Lennard-Jones particles.

Electrodermal lability and sensorimotor preparation: effects on reaction time, contingent negative variation, and heart rate

Electrodermal lability is a trait-like measure of spontaneous sympathetic resting activity. In the present study, we addressed whether interindividual differences in this lability have an impact on the reaction time (RT) and on two physiological indicators of a goal-oriented sensorimotor preparation in a long-running, forewarned RT task (S1-S2 paradigm). The two indicators were the brain’s contingent negative variation (CNV) and a heart rate deceleration (HRD). The interindividual differences were determined by counting spontaneous skin conductance fluctuations during a 5-min resting phase and dividing the subjects into two groups: individuals below (stable) and above (labile) the median of these fluctuations. In the task, labile individuals had a shorter RT compared with stable individuals and showed in the final phase of preparation in both physiological indicators the stronger response. Thus, lability-dependent effects in forewarned RT tasks cannot be explained by differences in stimulus-driven or passively controlled processes alone. Rather, goal-oriented, deliberately controlled processes that serve to adequately prepare for an imperative stimulus—the S2 in our paradigm—also must be considered to explain them. Labile individuals not only react faster than stable ones but also intentionally prepare themselves more appropriately for the imperative stimulus. A norepinephrine hypothesis focusing on the tonic activity of the locus coeruleus (LC) is proposed as an explanation for these and other lability-dependent effects. The frequency of spontaneous electrodermal fluctuations at rest may represent a peripheral, noninvasive, and easily measurable indicator of the baseline LC activity during wakefulness.

“Stick–slip” fluctuations in local electrical conductivity maps on graphite surfaces: A revisit

Electrical conductivity images of graphite surfaces are routinely obtained using scanning probe microscopy. Although the acquired conductivity maps often display a trigonal pattern with smooth variations, a “stick–slip” type of fluctuation has also been reported, where the local conductivity inversely correlates with the friction force during probe scanning. In this work, we revisit the lattice-resolved variations in local conductivity on graphite surfaces and reveal a new series of behaviors. Unlike previous observations, we demonstrate that local conductivity can exhibit in-phase, out-of-phase, or mixed-mode correlations with “stick–slip” lateral force signals. These behaviors are attributed to the cross-talk effect between interface contact conductivity and lateral force, induced by the inhomogeneous conductivity of the tip apex. This mechanism is experimentally validated, showing that local conductivity variations can switch within a single scan due to spontaneous changes in the conductivity of the tip. Our findings enhance the understanding of lattice-resolved electrical conductivity data on graphite surfaces and suggest a novel approach to amplify small lateral forces using inhomogeneous probe tips.

Fluctuation induces conductivity and microstructural studies in Y-123: Effect of CaO inclusion

This study explored the impact of CaO as effective fine pinning centres on the interactions among thermodynamic fluctuations of superconducting parameters during the superconducting transitions in the Y-123 (YBa2Cu3O7-δ) matrix system. The investigation involved introducing varying concentrations (0.0100 wt% ≤ × ≤ 0.6000 wt%) of CaO into the Y-123 matrix through a green approach thermal treatment method annealed in an oxygen flow. TGA-DTA analysis revealed that the thermal stability of CaO exceeded that of the Y-123 matrix system. In XRD results, all specimens crystallized into orthorhombic Y-123 as the main phase, accompanied by non-superconducting phases such as Y-211 and BaCuO2, contributing to the enhancement of superconducting parameters. These inclusions of CaO induced distinct trends in grain degradation, spiral grain growth, and the appearance of homogeneous Y-123 nano-entities within the Y-123 matrix system. DC resistivity measurements investigating thermal fluctuation conductivity showed reductions in transition temperature widths (ΔTc and ΔTcMF1-offset) reaching an optimal concentration of CaO inclusion at 0.0375 wt%. Additionally, intra-granular current density at 0 K (Jc(0)) experienced significant improvements at lower concentrations, peaking at 0.0375 wt% at 11.0 ×106 A/m2. The incorporation of CaO at 0.0375 wt% proved optimal for achieving finely scaled lattice defects in intergranular and intragranular coupling, serving as effective pinning centres. This dominance in the 3D regime of thermal fluctuation reduced flux motion and improved Jc(0). The study concluded that the deficient inclusion of CaO led to the well-dispersed formation of nano-sized Y-123 particles, enhancing the superconducting parameters.

Comparative Analysis of the Irradiation with Medium Fluences of High-Energy Electrons and Pr Doping on the Fluctuation Conductivity of YBa2Cu3O7–δ Single Crystals

Medium-fluence fast electron irradiation (1019 e/cm2 to 1020 e/cm2) or the changes in the praseodymium concentration in the range of 0.0 ≤ z ≤ 0.5 on the excess conductivity of YBa2Cu3O7–δ single crystals ware investigated. These can lead to a wider range of the temperature interval of excess conductivity which narrows the interval of linearity in the ab plane. At fluences 0 ≤ Φ ≤ 6.5 × 1019 e/cm2, there was a threefold increase in the transverse coherence length ξc(0) with an increase in Φ of more than four times as the praseodymium concentration increased to z ≈ 0.42. The two-dimensional–three-dimensional (2D–3D) crossover point shifted upward in temperature. Conversely, to irradiation with low fluences (Φ ≤ 1019 e/cm2) or low praseodymium doping (z ≤ 0.39), irradiation with medium fluences or high praseodymium doping led to a non-monotonic dependence of ξc(0) on the irradiation fluence, with characteristic maxima at Φ~(7–8) × 1019 e/cm2 and z ≈ 0.42, likely due to the suppression of the superconducting characteristics.

Research on the Control System for the Use of Biogas Slurry as Fertilizer

Due to its rich nutritional composition, biogas slurry can serve as a special liquid fertilizer. However, the application of slurry in agricultural fields currently faces challenges such as reliance on skilled famers’ experience, low precision, and difficulty in accurately controlling the irrigation dosage. To address these issues, an agricultural biogas slurry mixing agricultural machinery and its system has been designed and developed with the aim of enhancing the precision and safety of slurry application. The structure of the device has been designed, filter components have been selected, and improvements have been made to the structure of traditional connectors. Taking into account factors such as soil and humidity, an algorithm based on biogas slurry conductivity for slurry mixing decisions and the feedback control mechanism has been designed. After assembling the prototype, experiments were conducted, and the results showed that after processing by the system, compared to the calculated theoretical optimum, the concentration error of each component in the mixed fertilizer was controlled within 10%, and the conductivity fluctuation range was within 5%. This indicates that the overall ratio accuracy and stability of the biogas slurry mixing system are high. The biogas slurry mixing agricultural machinery and its system provide a novel intelligent equipment solution for the precise application of slurry, effectively enhancing the accuracy and safety of slurry application, reducing the use of chemical fertilizers during agricultural irrigation, and minimizing pollution to the environment and soil.

Tailoring local chemical fluctuation of high-entropy structures in thermoelectric materials.

In high-entropy materials, local chemical fluctuation from multiple elements inhabiting the same crystallographic site plays a crucial role in their unique properties. Using atomic-resolution chemical mapping, we identified the respective contributions of different element characteristics on the local chemical fluctuation of high-entropy structures in thermoelectric materials. Electronegativity and mass had a comparable influence on the fluctuations of constituent elements, while the radius made a slight contribution. The local chemical fluctuation was further tailored by selecting specific elements to induce large lattice distortion and strong strain fluctuation to lower lattice thermal conductivity independent of increased entropy. The chemical bond fluctuation induced by the electronegativity difference had a noticeable contribution to the composition-dependent lattice thermal conductivity in addition to the known fluctuations of mass and strain field. Our findings provide a fundamental principle for tuning local chemical fluctuation and lattice thermal conductivity in high-entropy thermoelectric materials.

Hydrophobic Modification of Pectin Aerogels via Chemical Vapor Deposition.

Pectin aerogels, with very low density (around 0.1 g cm-3) and high specific surface area (up to 600 m2 g-1), are excellent thermal insulation materials since their thermal conductivity is below that of air at ambient conditions (0.025 W m-1 K-1). However, due to their intrinsic hydrophilicity, pectin aerogels collapse when in contact with water vapor, losing superinsulating properties. In this work, first, pectin aerogels were made, and the influence of the different process parameters on the materials' structure and properties were studied. All neat pectin aerogels had a low density (0.04-0.11 g cm-1), high specific surface area (308-567 m2 g-1), and very low thermal conductivity (0.015-0.023 W m-1 K-1). Then, pectin aerogels were hydrophobized via the chemical vapor deposition of methyltrimethoxysilane using different reaction durations (2 to 24 h). The influence of hydrophobization on material properties, especially on thermal conductivity, was recorded by conditioning in a climate chamber (25 °C, 80% relative humidity). Hydrophobization resulted in the increase in thermal conductivity compared to that of neat pectin aerogels. MTMS deposition for 16 h was efficient for hydrophobizing pectin aerogels in moist environment (contact angle 115°) and stabilizing material properties with no fluctuation in thermal conductivity (0.030 W m-1 K-1) and density for the testing period of 8 months.

Light Emission and Conductance Fluctuations in Electrically Driven and Plasmonically Enhanced Molecular Junctions.

Electrically connected and plasmonically enhanced molecular junctions combine the optical functionalities of high field confinement and enhancement (cavity function), and of high radiative efficiency (antenna function) with the electrical functionalities of molecular transport. Such combined optical and electrical probes have proven useful for the fundamental understanding of metal-molecule contacts and contribute to the development of nanoscale optoelectronic devices including ultrafast electronics and nanosensors. Here, we employ a self-assembled metal-molecule-metal junction with a nanoparticle bridge to investigate correlated fluctuations in conductance and tunneling-induced light emission at room temperature. Despite the presence of hundreds of molecules in the junction, the electrical conductance and light emission are both highly sensitive to atomic-scale fluctuations-a phenomenology reminiscent of picocavities observed in Raman scattering and of luminescence blinking from photoexcited plasmonic junctions. Discrete steps in conductance associated with fluctuating emission intensities through the multiple plasmonic modes of the junction are consistent with a finite number of randomly localized, point-like sources dominating the optoelectronic response. Contrasting with these microscopic fluctuations, the overall plasmonic and electronic functionalities of our devices feature long-term survival at room temperature and under an electrical bias of a few volts, allowing for measurements over several months.

Conductance and thermopower fluctuations in interacting quantum dots

Conductance and thermopower fluctuations in interacting quantum dots

Interfacial modulation of hollow ZnS-SnS2 microboxs by Ti3C2Tx MXene to construct three-dimensional hybrid anodes for lithium-ion batteries with ultra high stability at low temperature

Metal sulfides exhibit obvious volume expansion due to the inherent poor conductivity and large temperature fluctuations, leading to reduced storage capacity. Herein, an electrostatic self-assembly strategy was proposed to fabricate a three-dimensional (3D) polyaniline (PANI) encapsulated hollow ZnS-SnS2 (H-ZSS) heterojunction confined on Ti3C2Tx MXene nanosheets (H-ZnS-SnS2@MXene@PANI, denoted as H-ZSSMP), which exhibits remarkable reversible capacity and cyclic stability (520.3 mAh/g at 2 A/g after 1000 cycles) at room temperature. Additionally, specific capacity can stabilized at 362.5 mAh/g for 250 cycles at −20 °C. A full cell with the configuration of H-ZSSMP//lithium iron phosphate (LiFePO4) can retain a satisfactory reversible capacity of 424.7 mAh/g after 100 cycles at 0.1 C. Theory calculations confirm heterogeneous interface can accelerate the transfer of ions through the interfacial regulation effect of MXene on H-ZSS. Our work provides a simple strategy to improve the capacity and stability of lithium-ion batteries (LIBs), as well as the new applications of MXene and bimetallic sulfides as anode materials, which will facilitate the development of MXene based composites for energy storage.

Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary

In this research, a multi-step modeling approach is followed using unsupervised and deep learning algorithms to interpret the geophysical well-logging data for improved characterization of the Quaternary aquifer system in the Debrecen area, Hungary. The Most Frequent Value-Assisted Cluster Analysis (MFV-CA) is used to map lithological variations within the aquifer system. Additionally, the Csókás method is used to discern both vertical and horizontal fluctuations in hydraulic conductivity. MFV-CA is introduced to cope with the limitation of the conventional Euclidean distance-based k-means clustering known for its low resistance to outlying values, resulting in deformed cluster formation. However, the computational time and demands of MFV-CA are evident, making them costly and time-consuming. As a result, Deep Learning (DL) methods are suggested to provide fast characterization of the groundwater aquifers. These methods include Multi-Layer Perceptron Neural Networks (MLPNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM), which are implemented for classification and regression. The classification categorized the inputs into three distinct lithologies trained initially by the results of MFV-CA. At the same time, the regression model offered a continuous estimations of hydraulic conductivity trained by the results of the Csókás model. The results demonstrated significant compatibility between the outcomes derived from the clustering and Csókás approaches and DL algorithms. Accordingly, the lithofacies and hydraulic conductivity variations across the main hydrostratigraphical units are mapped. This integration enhanced the understanding of the groundwater system, offering promising inputs for groundwater and development and management.

Signatures of Mesoscopic Transport in Single Non‐Intentionally Doped GaN‐Nanowire Field‐Effect Transistors

In this work, the fabrication and characterization of a fully functional field‐effect transistor (FET) are addressed based on a non‐intentionally doped GaN‐nanowire FET (NW–FET). Universal conductance fluctuations (UCFs) are observed at temperatures below 140 K. In contrast to other reports in literature, UCFs appear in the analyzed NW–FET only under the influence of an electrical field when applying a gate voltage, while no UCF signatures are observed when performing magnetic‐field‐dependent measurements. The reason is the considerable impact of the applied voltage on the narrow conductive channel of the non‐intentionally doped NW. The electrical field influences the Fermi level as well as the width of the depletion region, both changing the effective impurity distribution which determines the set of possible electron paths. The electric‐field‐induced variation of the set of electron paths correlates with a conductance variation, which leads to the occurrence of UCFs. Furthermore, the reliability of determining the phase coherence length from the NW–FET transfer characteristics is analyzed. It is shown that the value of is significantly affected by the choice of the gate voltage range due to the current dependence of the magnitude of the UCFs.

Automatic nutrient estimator: distributing nutrient solution in hydroponic plants based on plant growth.

The primary objective is to address the specific needs of plants at different growth stages by delivering precise nutrient concentrations tailored to their developmental requirements. Challenges such as uneven nutrient distribution, fluctuations in pH and electrical conductivity, and inadequate nutrient delivery pose potential hindrances to achieving optimal plant health and yield in hydroponic systems. By overcoming these challenges, the hydroponic farming community aims to enhance the accuracy of nutrient dosing, streamline automation processes, and minimize resource wastage. Hydroponics, a cultivation technique without soil, facilitates the growth of organic vegetation while concurrently minimizing water use and eliminating the necessity for pesticides. In order to achieve effective cultivation of hydroponic plants, it is essential to maintain a controlled environment that encompasses essential factors such as temperature, carbon dioxide (CO2) levels, oxygen availability, and appropriate lighting conditions. Additionally, it is crucial to ensure the provision of vital nutrients to maximize output and productivity. Due to the demanding nature of a hydroponic farmer's schedule, it is necessary to minimize the amount of time dedicated to nutrient management, as well as pH and EC adjustments. In order to determine and deliver the proper amount of vital nutrients, such as nitrogen, phosphorus, and potassium, based on the plant growth stage, we presented an automatic hydroponic nutrient estimator in this system. We noticed that the plant's nutrient consumption varies depending on its stage of growth according to plant psychology. Four peristaltic pumps with the necessary sensors are controlled by an Arduino board in the suggested system. Both filling and draining the water are done using each pump. To identify the plant stage, we apply the Plant Growth Stage Identification algorithm to encompass the seedling, vegetative, flowers, and fruit stages. The experimental results reveal that the Growth Stage Identification algorithm obtains 97.5% accuracy for the first 5 weeks with 1,715 ppm of nutrition ingestion, identifying the vegetative state. The flowering stage is identified with 97.5% accuracy in the 6-9th week with 2,380 ppm of nutrition consumption, and the fruiting location is determined with 99.4% accuracy in the last 10-15th week with 2,730 ppm of nutrition consumption.

Necklace‐Structured Silicon Suboxide‐Based Anode Materials with Multiple Carbon Networks for Stable Lithium Storage

AbstractSilicon suboxide (SiOx) attracts great attentions from both academy and industry owing to its higher capacity than graphite and smaller volume swelling than Si, making it possible to achieve a tradeoff between capacity and cycling stability. Whereas, the volume expansion problem and poor electrical conductivity of SiOx severely hinder its practical applications. Herein, a unique necklace‐structured SiOx‐based anode material consisting of carbon nanotube wired SiOx/C@C spheres with a surface carbon coating layer (CNT@SiOx/C@C) is constructed. The multiple carbon networks wire the whole composite anode material, effectively confining the volumetric variation of SiOx, and enhancing the structural integrity of the electrode. The as‐synthesized necklace‐structured CNT@SiOx/C@C manifests decent lithium storage behaviors in terms of discharge capacity (857.7 mAh g−1 at 0.1 A g−1), cyclability (81.7% capacity retention over 100 cycles at 0.1 A g−1), and rate capability (333.3 mAh g−1 at 10 A g−1). This study demonstrates the effectiveness of constructing multiple carbon networks for tackling the volume swelling and conductivity issues of SiOx. It is also anticipated that this structural design would be generally applied to other high‐capacity electrode materials suffering from large volume fluctuation and low conductivity.