Conductivity Volume Research Articles

Understanding the Relation Between Intrinsic Parameters of Substituents and Physical‐Chemical Properties of NVP

AbstractNASICON‐type Na3V2(PO4)3 (NVP) is regarded as an intriguing cathode material choice for sodium ion batteries (SIBs) due to its cycling stability and relatively high capacity. However, its voltage and electronic conductivity still need to be improved for larger‐scale fast‐charging applications (e.g. electric vehicles and mobile phones). In this work, we investigate the influence of Vanadium (V) substitution by other environmentally friendly, cheap, and/or high‐valent transition metal (TM) elements on the electrochemical performance of NVP. Density functional theory calculation was used to study the volume change, voltage, conductivity, and redox mechanism during charge/discharge of different compositions. It is found that a substitution of 50% of V by Mn, Mo or W ions resulting in Na3VMn(PO4)3 (NVMnP), Na3VMo(PO4)3 (NVMoP), and Na3VW(PO4)3 (NVWP) significantly alters the cathode materials’ physical and chemical properties, notably decreasing the band gap. In particular, NVMnP has lesser than 1 eV theoretical band gap and provides a higher voltage, while NVWP a much lower voltage in comparison to NVP. This means that NVMnP and NVWP can be promising cathode and anode materials respectively. This work also establishes a relation between fundamental properties of substituents (i.e. ionization energy and ionic size) and the overall performance of NVP.

An analytical observational study for diagnostic accuracy of volume, conductivity & scatter (VCS) indices of neutrophils for diagnosis of sepsis in an emergency hospital setting.

Background & objectives The newer technique using an innovative volume conductivity scatter (VCS) technology is emerging as a surrogate for sepsis diagnosis. The VCS technology offers a more objective method to measure cell volume (V), characterize conductivity (C) and light scatter (S) directly from more than 8,000 white blood cells (WBCs). However, diagnostic performance of VCS parameters in sepsis has not been extensively tested in routine hospital emergency settings. Therefore, the present study aimed to investigate the diagnostic and prognostic performance of VCS markers of neutrophils in our local hospital emergency setting. Methods It was an observational analytical study with 41 cases of sepsis and 43 healthy controls aged above 18 yr. Individuals with acute coronary syndrome and individuals with already diagnosed Human Immunodeficiency Virus (HIV) infection were excluded from the study. Results The mean neutrophil volume (MNV) values were not significantly different between cases and controls (P 0.138) whereas mean neutrophil conductance (MNC) and mean neutrophil scatter (MNS) measurements were significantly higher among cases as compared to controls (both P-values <0.001). According to Receiver Operating Characteristics (ROCs) curve analysis, MNV in our study failed to show statistically significant discriminatory ability in sepsis (AUC 0.54) whereas MNC (AUC 0.98) and MNS (AUC 0.95) showed marked discriminatory ability in diagnosing sepsis in this study cohort. Interpretation & conclusions Among VCS parameters, MNV failed as a standalone biomarker of sepsis in routine emergency setting whereas MNC and MNS had statistically significant diagnostic and discriminatory accuracies among hospitalized affected individuals with sepsis.

Improved body and interface properties of EPDM insulation for HVDC cable accessory by grafted voltage stabilizer

As a key component in HVDC cable accessory, EPDM insulation is prone to breakdown both in body and along interface. To improve the comprehensive electrical strength of EPDM, voltage stabilizer 2-propenyl-4,6-dibenzoylresorcinol (ADR) was simultaneously grafted onto macromolecules through free radical reaction on its vinyl during crosslinking of EPDM. After modification, the mechanical strength and thermal stability of EPDM are improved. In terms of body properties, the injection and rapid transfer of space charge under normal electric field are weakened, the volume conductivity is reduced, the breakdown strength is improved and the growth of electrical tree is suppressed. In terms of interface properties, the normal electric field at the EPDM/XLPE interface is weakened, hence reduced potential risk of deterioration initiated from interface. Moreover, the surface conductivity of EPDM is reduced, the charge accumulation and migration along the EPDM/XLPE interface are suppressed, and the interface breakdown strengths under different interface pressures are significantly increased under tangential electric field. Molecular simulations and UV absorption characteristics indicate that the grafted ADR molecules not only introduce charge traps into EPDM, but also absorb the high energy from trapped electrons and consume it through multiple excitations, thus preventing the electron avalanche and subsequent degradation of EPDM.

Acoustoelectric Effect due to an In-Depth Inhomogeneous Conductivity Change in ZnO/Fused Silica Substrates

The acoustoelectric (AE) effect induced by the absorption of ultraviolet (UV) light at 365 nm in piezoelectric ZnO films was theoretically and experimentally studied. c-ZnO films 4.0 µm thick were grown by the RF reactive magnetron sputtering technique onto fused silica substrates at 200 °C. A surface acoustic wave (SAW) delay line was fabricated with two split-finger Al interdigital transducers (IDTs) photolithographically implemented onto the ZnO-free surface to excite and reveal the propagation of the fundamental Rayleigh wave and its third harmonic at about 39 and 104 MHz. A small area of a few square millimeters on the surface of the ZnO layer, in between the two IDTs, was illuminated by UV light at different light power values (from about 10 mW up to 1.2 W) through the back surface of the SiO2 substrate, which is optically transparent. The UV absorption caused a change of the ZnO electrical conductivity, which in turn affected the velocity and insertion loss (IL) of the two waves. It was experimentally observed that the phase velocity of the fundamental and third harmonic waves decreased with an increase in the UV power, while the IL vs. UV power behavior differed at large UV power values: the Rayleigh wave underwent a single peak in attenuation, while its third harmonic underwent a further peak. A two-dimensional finite element study was performed to simulate the waves IL and phase velocity vs. the ZnO electrical conductivity, under the assumption that the ZnO layer conductivity undergoes an in-depth inhomogeneous change according to an exponential decay law, with a penetration depth of 325 nm. The theoretical results predicted single- and double-peak IL behavior for the fundamental and harmonic wave due to volume conductivity changes, as opposed to the AE effect induced by surface conductivity changes for which a single-peak IL behavior is expected. The phenomena predicted by the theoretical models were confirmed by the experimental results.

Correlation of proton conductivity and free volume in sulfonated polyether ether ketone electrolytes: A positron annihilation lifetime spectroscopy study

Proton-conducting polymers play a pivotal role in clean energy technologies and various industrial applications, with a significant emphasis on enhancing energy efficiency and minimizing environmental impact. Sulfonated polyether ether ketone (SPEEK), which is renowned for its proton conductivity, has emerged as a key material in electrochemical processes, notably in proton exchange membrane (PEM) fuel cells. This study investigated the proton conductivity and dielectric behavior of SPEEK electrolytes at varying degree of sulfonation (DS) of 65% and 80%, correlating these properties with free volume profiles determined by positron annihilation lifetime spectroscopy (PALS). The SPEEK-65 and SPEEK-80 electrolytes were prepared via a controlled sulfonation process and characterized by FTIR, TGA, and SEM analyses. Proton conductivity and dielectric measurements were conducted at temperatures ranging from 300-370 K and frequencies ranging from 20 Hz to 1 MHz. The results revealed that SPEEK-80 exhibited a maximum proton conductivity of 3.4×10-2 S/m at 300 K and 1 MHz, which was significantly greater than the 4.38×10-3 S/m observed for SPEEK-65 under the same conditions. PALS analysis demonstrated a notable increase in free volume with increasing DS, with SPEEK-80 showing a higher o-Ps lifetime and intensity, indicating larger free volume sizes and fractions. These findings underscore the critical interplay between DS, free volume, and proton conductivity, offering insights into optimizing SPEEK-based electrolytes for advanced electrochemical applications.

Robust estimation of hydrogeological parameters from wireline logs usingsemi-supervised deep neural networks assisted with global optimization-based regression methods

Understanding the distribution of hydrogeological properties of the aquifers is crucial for sustainable groundwater resource development. This research explores the application of deep autoencoder neural networks (AE-NN), assisted with global optimization methods for estimating hydrogeological parameters in the Quaternary aquifer system in the Debrecen area, Hungary. Traditional methods for estimating aquifer parameters typically depend on field experiments and laboratory analyses, which are both costly and time-consuming, and often fail to account for the heterogeneity of groundwater formations. In this study, deep AE-NN models are trained to extract latent space (LS) representations that capture key features from the available well logs, including spontaneous potential (SP), natural gamma ray (NGR), shallow resistivity (RS), and deep resistivity (RD). The LS log is then correlated with shale volume and hydraulic conductivity, as determined by the Larionov and Csókás methods, respectively. Regression analysis revealed a Gaussian relationship between the LS log and shale volume and a negative nonlinear relationship with hydraulic conductivity. Global optimization methods, including simulated annealing (SA) and particle swarm optimization (PSO), were used to refine the regression parameters, enhancing the predictive capabilities of the models. The results demonstrated that AE-NN assisted with global optimization methods can be effectively used to estimate shale volume and hydraulic conductivity, proposing a novel and independent approach for estimating hydrogeological parameters critical to groundwater flow and contaminant transport modeling.

Facile fabrication of graphene aerogel/Cu/CuO for enhanced sodium storage performance

It is widely recognized that CuO experiences volume expansion and conductivity issues, leading to unsatisfactory performance in sodium-ion batteries. A feasible approach to mitigate these challenges is the combination of Cu/CuO nanosheets with porous reduced graphene oxide aerogel (GA). In this study, an innovative composite of Cu/CuO nanosheets encapsulated within a 3D GA structure (GA/Cu/CuO) was synthesized via an alkaline exfoliation-mild self-assembly method. The results reveal that the Na+ storage properties of Cu/CuO/GA significantly surpassed those of pure CuO. Specifically, the GA/Cu/CuO exhibited a capacity retention of 320 mAh g–1 after 220 cycles at a current density of 0.1 A g–1, and demonstrated an optimized rate capability of 225 mAh g–1 at a current density of 1 A g–1. The enhanced rate and long-cycle performances are attributed to the synergistic effects of Cu/CuO nanosheets and porous GA, which shorten the Na+ transfer pathway, improve electronic/ionic conductivity, and buffer volume expansion during the discharge/charge process. Furthermore, the facile and innovative design strategy presented could be applicable to the synthesis of other composites for energy storage applications.

Novel C/MoS2 hollow nanocomposites enhance lithium storage in battery anodes

With society's rapid progress, there is an increasing need for electricity among individuals, but the prevailing source of electricity is still mainly obtained through the burning of nonrenewable fossil fuels, which are not renewable and pose serious environmental hazards. Lithium-ion batteries are used widely for excellent rechargeable capabilities and high energy density. Recently, researchers have become increasingly interested in transition metal sulfides owing to their cost-effectiveness and remarkable specific capacity. However, their commercialization has been hindered by the expansion of material volume and low electrical conductivity during charging and discharging. We have successfully designed and synthesized MoS2 nanosheets loaded on carbon spheres with a 3D hollow structure starting from SiO2 as a template. Due to the doping of carbon materials and particular 3D hollow structures, the optimal C/MoS2-0.3 hollow nanocomposites exhibit excellent electrochemical performance. Following exposure to over 900 cycles at a 0.5 A g-1 ampere density, the materials exhibited an exceptional 958.50 mAh g-1 reversible capacity, demonstrating their remarkable performance.

Machine Learning Techniques to Analyze the Influence of Silica on the Physio-Chemical Properties of Aerogels.

This study explores the application of machine learning techniques, specifically principal component analysis (PCA), to analyze the influence of silica content on the physical and chemical properties of aerogels. Silica aerogels are renowned for their exceptional properties, including high porosity, large surface area, and low thermal conductivity, but their mechanical brittleness poses significant challenges. The study initially utilized cross-correlation analysis to examine the relationships between key properties such as the Brunauer-Emmett-Teller (BET) surface area, pore volume, density, and thermal conductivity. However, weak correlations prompted the application of PCA to uncover deeper insights into the data. The PCA results demonstrated that silica content has a significant impact on aerogel properties, with the first principal component (PC1) showing a strong positive correlation (R2 = 94%) with silica content. This suggests that higher silica levels correspond to lower thermal conductivity, porosity, and BET surface area, while increasing the density and elastic modulus. Additionally, the analysis identified the critical role of thermal conductivity in the second principal component (PC2), particularly in samples with moderate to high silica content. Overall, this study highlights the effectiveness of machine learning techniques like PCA in optimizing and understanding the complex inter-relationships among the physio-chemical properties of silica aerogels.

An electric conductive wide-temperature flexible phase change material for all-climate battery thermal management

Battery thermal management with phase change materials (PCM) has been limited by leakage, low thermal conductivity and rigidity, and the inability to preheat at low temperatures. To solve these problems, a wide-temperature flexible composite PCM (FCPCM) was prepared with a high-temperature open refining method. Styrene ethylene butylene styrene (SEBS) and expanded graphite (EG) absorb paraffin (PA) onto a three-dimensional network. The FCPCM possesses good flexibility before and after phase transition. It can be bent and stretched arbitrarily at room temperature, and the shape memory function enable it can be restored to its original state after heating. The latent heat of the FCPCM-15 is 159.9 J/g and its thermal conductivity was 7.45 times higher than that of pure paraffin. The FCPCM also possesses a good volume conductivity of 92–2952 S/m and allows for uniform electrical heating. The excellent thermal and electrical performance of the FCPCM allows it to cool batteries at high temperatures and preheat batteries at low temperatures. After ten charge/discharge cycles at 30 °C, the battery pack’s temperature based on FCPCM cooling is still reduced by 3.9 °C. At a low temperature of −20 °C, the preheating rate of the battery pack can reach 12.9 °C/min, and the discharge voltage and capacity of the battery pack were increased by 15 % and 20.8 % after preheating. The FCPCM suggests a promising and practical approach way for the all-climate thermal management of batteries.

Strong flexible conductive hydrogel based on adaptive temperature and humidity characteristics

The development of conductive hydrogels has attracted great attention due to their broad applications. In this work, based on a dual-network structure, a highly flexible and adaptive conductive hydrogel has been developed, using the catalytic polymerization method, which also obtains Poly(3,4-ethylenedioxythiophene)-poly (styrene sulfonate) (PEDOT: PSS). Upon environmental warming, the double-network-structured hydrogel featuring a LiBr solution (LiBr@PAM-SA) undergoes a gradual water loss. However, significant moisture depletion occurs only when the temperature reaches 180 °C. Notably, compared to hydrogels devoid of a LiBr solution that experiences dehydration at 120 °C, LiBr@PAM-SA hydrogels manifest a superior capacity for adapting to varying environmental temperatures. Furthermore, this hydrogel maintains 90% of its inherent conductivity after undergoing 1000 cycles of stretching and compression. Upon incorporating 1 wt% PEDOT: PSS, the conductive hydrogel (LiBr@PAM-SA) displays the smallest volume resistivity of 0.022 Ω-cm and the highest volume conductivity of 44.665 µS/cm, in comparison to the hydrogels of single-layer graphene oxide (SLGO) and AgNWs. Additionally, its light transmittance and hydrogel quality improve in environments with lower temperatures or higher humidity. Finally, this conductive hydrogel might show great potential in varied fields of dynamic environment monitoring, intelligent conductive transmission, and intelligent sensing identification.

Estimation of Urine Volume and Urine Conductivity Using Electrical Bioimpedance Based on the Neural Network Method

Purpose: Urine volume and urine conductivity monitoring allow better care for urinary tract infection disease. Urine volume and conductivity involve electrical bioimpedance change at the lower abdomen. In previous studies, bioimpedance has been only used for estimating the volume, and the estimation error significantly increases when the conductivity changes. Materials and Methods: In this work, the neuron network technique is proposed to determine both the volume and the conductivity based on the measured bioimpedance data on a sixteen-electrode configuration. Nine architectures of neuron networks were investigated by simulation. Eleven body models were created, consisting of muscle, fat, pelvis bone, rectum, and bladder. Seven bladder sizes, eleven conductivities, and eight levels of Signal-to-Noise Ratio (SNRs) were simulated. Results: The result showed that the neural network method could efficiently estimate with an average of 1.04% volume error and 2.85% conductivity error. The performance remained stable with a signal-to-noise ratio higher than 60 dB, but it may reduce 2-8 times at lower SNRs. The moderate fat content provided high performance. The performance would be worsened if the bladder size was very small and the conductivity was low. The performance was increased when the volume was moderate, i.e. 302 ml, and the conductivity was higher than 1.76 S/m. The 3-layer architecture with 1024, 512, and 2 neurons yielded the highest performance. The 2-layer architecture with hidden neurons higher than 512 provided a comparative performance with only 0.9-1.5% lesser performance. Conclusion: Neural network technique can be used to estimate urine volume and urine conductivity with excellent performance.

Effect of Boric Acid on Electronically Controlled Solid Propellants

Electrically controlled solid propellants (ECSPs) were modified with boric acid (HB). HB affects ECSPs’ combustion performance by changing the volume conductivity. Increasing the HB content can enhance the compressive properties by further increasing the crosslink density of the ECSPs. Based on the calculation results of NASA’s Chemical Equilibrium with Applications program, HB has no apparent effect on the specific impulse and adiabatic flame temperature of the propellant. The volume conductivity of the ECSPs were measured using a three-electrode system. After the addition of HB, the volume conductivity of the ECSPs decreased. In the process of thermal decomposition, the addition of HB can improve the thermal stability of ECSPs as a whole, although this effect is small. The effects of HB on the combustion rate and minimum theoretical ignition voltage of hydroxyammonium nitrate (HAN)-based propellants were studied at 0.1 MPa. The results demonstrate that the combustion rate of HAN-based propellants increases with increasing voltage, and that this characteristic is not affected by HB. However, the combustion rate decreases with increasing HB content, and the minimum theoretical ignition voltage increases accordingly.

Investigation of the influence of morphology on thermal conductivity in hexagonal honeycomb structures and computational models with varied volume fraction and conductivity ratio

The effective thermal conductivity (ETC) is a critical parameter for simulating macroscopic heat transfer processes in composite materials, which estimation is particularly critical where the thermal conductivity of the composite phases is completely different. The huge difference in thermal conductivity of the composite phases makes their volume fraction modulation a classical way to reach the desired thermal conductivity. Nevertheless, the typical manufacturing process of honeycomb cellular structures allows various degrees of stretching of the structure, leading to various honeycomb geometries. In these ‘real’ structures some of the honeycomb wall sides are twice as thick as other parts, modifying the symmetry of the system with respect to honeycomb with uniform wall side thickness. A noticeable example of these composites is that of a hexagonal metallic honeycomb structure filled with phase change material (PCM) which is a widely utilized material in the field of thermal storage and thermal management by exploiting the heat absorbed/released by the PCM phase during its melting/solidification. While the thermal response of a PCM composite during a thermal cycle is not only defined by thermal conductivity (but also by cell size), this represents the basis for the with the optimization of a system based on a composite PCM.For this reason, in this study, steady-state simulations of heat transfer in unit honeycomb cells in different directions perpendicular to the cell axis are conducted to quantify the impact of morphology on the thermal property of the different wall types within honeycomb structures. The results demonstrate that in both SHS and DHS, the porosity exhibiting maximum anisotropy of ETC decreases as the thermal conductivity ratio increases. Moreover, simple predictive models for calculating the ETC in all directions are proposed for each type of honeycomb, considering a wide range of porosity and thermal conductivity ratio, with a relative error limited to 2 %.

Performance of novolac resin‐ and resole resin‐based carbon/carbon composites in relation to their fabrication conditions

AbstractThe demands of cost‐driven industrial applications can be satisfied by manufacturing composites with a low volume fraction of carbon fibres as phenolic carbon fibre‐reinforced composites and C/C composites, both with acceptable performances, for low‐ or high‐temperature applications, respectively. Polymeric composites reinforced with a low volume fraction (7.5% v/v) of carbon fibres were fabricated using laboratory‐produced phenolic resins, novolac (N) and resole (R), as matrices after different curing/post‐curing temperature profiles. By optimising the manufacturing conditions, the N‐based polymeric composites exhibited higher flexural strength, whereas the R‐based composites showed higher shear strength. C/C composites, namely N‐based and R‐based, were manufactured by pyrolysis of the previously prepared polymeric composites up to 1000 °C. The pyrolysed composites were then densified by impregnation with an appropriate resin solution, followed by curing and new pyrolysis, and particularly by employing 1 up to 4 consecutive cycles of ‘impregnation–curing/pyrolysis’. Weight changes resulting from the impregnation–curing and pyrolysis stages were determined. The curing of both resins was verified by Fourier Transform Infrared Analysis. The apparent density and X‐ray diffraction data of the C/C composites were used to calculate their total percent porosities. The morphology and elemental composition of the C/C composites at their failure region (after flexural testing) were examined by Scanning Electron Microscopy/Energy‐Dispersive X‐ray Analyses. In comparison to the N‐based C/C composites, the R‐based ones exhibited: higher shear strength, lower flexural strength, higher Shore D hardness, slightly higher surface conductivity and lower volume conductivity. The optimum conditions for the manufacture of C/C composites were achieved by applying two consecutive cycles of ‘pyrolysis–impregnation–pyrolysis’ to the polymeric composites. © 2024 The Authors. Polymer International published by John Wiley &amp; Sons Ltd on behalf of Society of Industrial Chemistry.

Armoring hydrophilic wood-structured ultrathick electrode with bimetallic nitride enables high energy-density supercapacitor

Thick electrodes can reduce the ratio of inactive constituents in a holistic energy storage system while improving energy and power densities. Unfortunately, traditional slurry-casting electrodes induce high-tortuous ionic diffusion routes that directly depress the capacitance with a thickening design. To overcome this, a novel 3D low-tortuosity, self-supporting, wood-structured ultrathick electrode (NiMoN@WC, a thickness of ∼1400 μm) with hierarchical porosity and artificial array-distributed small holes was constructed via anchoring bimetallic nitrides into the monolithic wood carbons. Accompanying the embedded NiMoN nanoclusters with well-designed geometric and electronic structure, the vertically low-tortuous channels, enlarged specific surface area and pore volume, superhydrophilic interface, and excellent charge conductivities, a superior capacitance of NiMoN@WC thick electrodes (∼5350 mF cm−2 and 184.5 F g−1) is achieved without the structural deformation. In especial, monolithic wood carbons with gradient porous network not only function as the high-flux matrices to ameliorate the NiMoN loading via cell wall engineering but also allow fully-exposed electroactive substance and efficient current collection, thereby deliver an acceptable rate capability over 75% retention even at a high sweep rate of 20 mA cm−2. Additionally, an asymmetric NiMoN@WC//WC supercapacitor with an available working voltage of 1.0–1.8 V is assembled to demonstrate a maximum energy density of ∼2.04 mWh cm−2 (17.4 Wh kg−1) at a power density of 1620 mW cm−2, along with a decent long-term lifespan over 10,000 charging-discharging cycles. As a guideline, the rational design of wood ultrathick electrode with nanostructured transition metal nitrides sketch a promising blueprint for alleviating global energy scarcity while expanding carbon-neutral technologies.

Development and experimental characterization study of cesium doped zinc oxide polymer conductive films for sensing applications

Development and experimental characterization study of cesium doped zinc oxide polymer conductive films for sensing applications

Assessing heterogeneous groundwater systems: Geostatistical interpretation of well logging data for estimating essential hydrogeological parameters

This research presents an unsupervised learning approach for interpreting well-log data to characterize the hydrostratigraphical units within the Quaternary aquifer system in Debrecen area, Eastern Hungary. The study applied factor analysis (FA) to extract factor logs from spontaneous potential (SP), natural gamma ray (NGR), and resistivity (RS) logs and correlate it to the petrophysical and hydrogeological parameters of shale volume and hydraulic conductivity. This research indicated a significant exponential relationship between the shale volume and the scaled first factor derived through factor analysis. As a result, a universal FA-based equation for shale volume estimation is derived that shows a close agreement with the deterministic shale volume estimation. Furthermore, the first scaled factor is correlated to the decimal logarithm of hydraulic conductivity estimated with the Csókás method. Csókás method is modified from the Kozeny-Carman equation that continuously estimates the hydraulic conductivity. FA and Csókás method-based estimations showed high similarity with a correlation coefficient of 0.84. The use of factor analysis provided a new strategy for geophysical well-logs interpretation that bridges the gap between traditional and data-driven machine learning techniques. This approach is beneficial in characterizing heterogeneous aquifer systems for successful groundwater resource development.

Local field potential journey into the Basal Ganglia

Local field potentials (LFP) in the basal ganglia (BG) have attracted considerable research and clinical interest. The genesis of these signals has been a topic of extensive discourse, focusing on whether they are a manifestation of local synaptic activity or result from the propagation of electrical signals through tissue, as described by the Maxwell equations (volume conduction). To investigate this, we conducted simultaneous recordings of LFPs from two cortical areas— the dorsolateral prefrontal cortex (DLPFC) and the primary motor cortex (M1)—and various sites within the BG nuclei in an awake, non-task-engaged non-human primate (NHP). Employing innovative analytical techniques, we discerned significant cross-correlations indicative of potential connections, while filtering out non-significant correlations. This allowed us to differentiate between synaptic inputs and volume conduction. Our findings indicate two distinct propagation pathways of BG field potentials emanating from the M1 and the DLPFC, each characterized by different temporal delays. The results imply that these anatomical pathways are differentially influenced by the mechanisms of volume conduction and synaptic transmission. Notably, the M1 exhibits more functional links with non-zero-time delays to the BG structures, while the DLPFC-BG connections are marked by zero-time delays, suggesting a predominance of volume conduction effects. Consequently, investigations into the origins of BG LFP should account for the distinct anatomical pathways linking the cortex and the BG, as they differentially represent information flow and volume conductance.

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.