Conductivity Of Carbon Nanotubes Research Articles

Superior Conductive, Large Diameter CNT Composite Yarn of Insulative Polymer: Inferences of a Unidirectional Compression‐Stretching Technique

ABSTRACTLarge diameter yet highly conductive Carbon Nanotube (CNT) yarn could have prospective control on high‐tech application field spanning from electronic devices to wearable textiles; although the development of such macroscopic CNTs is extremely challenging. Especially, while fabricating CNT composite yarn with polymer, insulative nature of polymeric materials inherently propagates poor electrical conductivity to CNT yarn. To address this, we have proposed an exciting approach to fabricate large dimension, highly conductive yet flexible CNT‐Thermoplastic Polyurethane (TPU) composite yarn through unidirectional compression‐stretching process. Our technique allowed TPU molecules to be well dispersed into inner and inter‐CNT bundles facilitating well flexibility while the simultaneous functions of pressure and tension allowed more closely packed CNTs network within densified CNT yarn reducing the inherent voids and contact resistance. The consequent yarn possessed high conductivity of 1613 S/cm, attractive mechanical performance (tensile strength 1.3 GPa, Young's modulus 12 GPa, toughness 100.75 MJ/m3), exceptional anti‐abrasive ability (up to 46,350 cycles) endowing its multidirectional adaptability for smart textiles. Moreover, the desirable E‐heating performance together with excellent electrical stability allows successful exploitation of the prepared CNT yarn as stretchable heater. Such amazing integrated characteristics may allow the resultant yarn to replace traditional carbon fiber in various high‐tech arena as well.

Electrospun Mesoporous Ni0.5Zn0.5Fe2O4 - CNT - Hollow Carbon Ternary Composite Nanofibers as High Performance Electrodes for Advanced Symmetric Supercapacitors.

Spinel ferrites have attracted considerable interest in energy storage systems due to their unique magnetic, electrical and catalytic properties. However, they suffer from poor electronic conductivity and low specific capacity. We have addressed this limitation by synthesizing composite hollow carbon nanofibers (HCNF) embedded with nanostructured Nickel Zinc Ferrite (NZF) and Multiwalled carbon nanotubes (CNT), through coaxial electrospinning. These ternary composite nanofibers NZF-CNT-HCNF have a high specific capacity of 833 C g-1 at a current density of 1 A g-1 and have a capacity retention of 90 % after 3000 cycles. Their performance is much better than pure NZF fibers (180 C g-1) or hollow carbon nanofibers (96 C g-1), suggesting synergy between various constituents of the composite. A symmetric supercapacitor fabricated from NZF-CNT-HCNF composite nanofibers (30 % NZF) has a high specific capacity of 302 C g-1 (302 A g-1) at a current density of 1 A g-1 and has a capacity retention of 95 % after 5000 cycles. At the same current density, the device has a high energy density of 39 Whkg-1 and power density of 1000 Wkg-1 at a current density of 1 A g-1. This performance can be attributed to the high specific surface area (776 m2 g-1), mesoporosity (pore size ~4 nm), interconnectedness of the nanofibers and high electrical conductivity of CNTs. These fibers can be used as light-weight high performance electrode materials in advanced energy storage devices.

Informatics-based design of polyaniline-carbon nanotube thermoelectric nanocomposite using ANN and GA

Abstract Conducting polymer and carbon nanotube (CNT) based nanocomposites have emerged as prospective thermoelectric (TE) materials due to their potential application in flexible electronics. Non-conventional charge and heat transport in these nanocomposites, presents the possibility to enhance the TE conversion efficiency, given by ZT. However, the highly non-linear and complex association of structure and composition with the overall TE properties have hindered the development of any general strategy to develop high ZT nanocomposites. Here, we implement artificial neural network (ANN) and genetic algorithm (GA) to develop data driven models followed by optimization to design high efficiency nanocomposites based on CNT dispersed in polyaniline (PANI) matrix. Our models suggest that CNT concentration plays the most crucial role in determining ZT. Non-dominated Pareto optimal solutions consisting of different combinations of design variables are obtained by multi-objective optimization. Although a range of optimal solutions span over different regions of the search space, in general we note that longer CNTs boost Seebeck coefficient (S) and electrical conductivity (σ), and smaller length lowers thermal conductivity (k), while higher diameter of CNTs increase S and lowers σ and k. The results provide a general guideline for developing CNT-PANI nanocomposites with enhanced TE figure of merit.

Flexible antibacterial strain sensor with low electrical hysteresis, ultralow detection limit, and wide linear sensing range for human motion monitoring and human–machine interaction

Achieving low electrical hysteresis, an ultralow detection limit, and a wide linear sensing range is critical for the practical application of flexible strain sensors. However, the intrinsic viscoelasticity of the elastomer macromolecules can adversely affect the behavior of the conductive sensing network during stretching and relaxation, rending it challenging to simultaneously achieve these properties. Herein, a novel strategy is proposed to design a hybrid covalent-ionic crosslinking network within the elastomer and to construct a robust conductive carbon nanotube (CNT) layer on the elastomer surface using a swelling-driven penetration method. The hybrid crosslinking network gives the elastomer enhanced mechanical strength and exceptional stretchability, while reducing the dynamic losses of the macromolecules. It also reduces the impact of the elastomer macromolecules on the conductive layer during stretching. Even minimal strains are sufficient to induce slippage of the CNTs, leading to changes in resistance. As the strain increases, further disentanglement and slippage of the CNTs results in crack formation, which enables greater resistance variation and dominates the sensing mechanism. As a result, the as-prepared conductive elastomer-based strain sensors exhibit exceptional sensing performance, including low electrical hysteresis (2.3 %), ultralow detection limit (0.1 %), wide linear working range (690 %), and excellent durability (>10,000 cycles). The strain sensors have been successfully employed in human motion monitoring, human–machine interaction, and angle measurement. In addition, the incorporation of the ionic crosslinking network endows the sensor with excellent antibacterial properties. Consequently, the developed conductive elastomers hold significant promise for applications in smart wearable electronics.

Mussel-inspired, fully biobased, mechanically robust, and room temperature healable supramolecular elastomer composites for sustainable strain sensors

The sustainable development of strain sensors necessitates the use of mechanically robust and self-healing elastomers derived from biobased feedstocks to ensure durability, extend service life, and reduce reliance on fossil resources. Herein, we report mussel-inspired, fully biobased, mechanically robust, room-temperature healable supramolecular elastomer composites (SECs) fabricated from natural rubber (NR), polydopamine (PDA), and cellulose nanofiber (CNF). Hydrogen bonds were formed among the hydroxyl and secondary amine groups of PDA, hydroxyl groups of CNF, and the non-rubber components of NR, resulting in room-temperature self-healing and mechanically reinforced NR/PDA/CNF SECs. The SECs achieved a tensile strength of up to 9.5 MPa and recovered over 80 % of its strength after self-healing at room temperature for 3 h. The robust adhesion properties of PDA within the SECs enabled the surface coating of the SECs with conductive carbon nanotubes (CNT) to fabricate flexible strain sensors without additional adhesives through a simple dip-coating technique. These flexible strain sensors exhibited excellent structural stability, high sensitivity, and reliability, making them suitable for human motion signal detection. This study underscores the potential of biobased and self-healing elastomers in enhancing the performance and sustainability of flexible strain sensors, contributing significantly to the development of sustainable and durable sensing technologies.

Highly-improved microwave absorption performance of LaFeO3/Fe@CNTs nanocomposites through in-situ synthesis of Fe@CNTs

In order to enhance the microwave absorption performance, the multi-phase nanocomposites composed of magnetic medium and carbon nanotubes (CNTs) is designed and developed based on impedance matching. In this paper, LaFeO3/Fe@CNTs nanocomposites are prepared in situ using LaFeO3 as catalysts and C2H2 as carbon sources with CVD method, and then the microstructures, magnetic properties and microwave absorption performance are investigated in detail. The specific surface area of LaFeO3/Fe@CNTs nanocomposites increases greatly from 16.39 m3/g for LFC0 to 52.29 m3/g for LFC5 with the increasing CNTs content due to the enhanced heterogeneous interfaces. Ms also increases from 0.68 emu/g for LFC0 to 10.24 emu/g for LFC5 from magnetic Fe nanoparticles. LFC5 exhibits the best microwave absorption properties with the minimum reflection loss of -38.758 dB and a broad effective absorption bandwidth of 2.32 GHz at 2.5 mm. Impedance matching is balanced by permittivity from CNTs and permeability from Fe nanoparticles. Owing to the conductive CNTs with more defects, the dielectric loss and eddy current loss both increases to some extent. The synergistic loss mechanism of magnetic Fe nanoparticles and dielectric CNTs result in impedance matching and outstanding microwave attenuation.

Spherical NiS2/Ni17S18–C accelerates ion transport and enhances kinetics for lithium-sulfur battery host material

Transition metal sulfides exhibit notable catalytic activity and possess a high theoretical specific capacity as host materials in lithium-sulfur batteries. However, their restricted conductivity and sluggish Li+ transport hinder their broader application. In this research, we developed a Ni-based metal-organic framework (Ni-MOF) using nitrogen-containing benzimidazole and coupled it with a highly conductive carbon nanotube (CNT) to form NixSy (NiS2–Ni17S18)–C/CNT. The N-doped carbon skeleton derived from the MOF enhances the adsorption and chemical anchoring of polysulfides, while the even distribution of NiS2 and Ni17S18 enhances the redox reaction kinetics. Additionally, the conductive CNT networks aid in rapid electron transport, resulting in improved sulfur utilization. Consequently, the NixSy-C/CNT@S electrode demonstrates an impressive initial specific capacity of 1468 mAh g−1 at 0.2C and maintains 904.4 mAh g−1 after 200 cycles. Moreover, NixSy-C/CNT@S displays exceptional cycle stability, with a capacity retention of 76.20 % and a decay rate of only 0.05 % per cycle after 500 cycles at 0.5C. This study paves the way for the development and synthesis of cathode materials with outstanding electrochemical performance in LSBs.

Conductivity Insights Into the Carbon Nanotubes Mobility Restricted by the Long‐Branched Chains During the Thermal Annealing, Fast Shear Flow and Melt to Solid Cooling Process

AbstractThe present work provides a unique insight to reveal the long chain branching (LCB) influence to the nano‐fillers, that is via analyzing the conductivity evolution during the thermal annealing, fast shear flow and melt to solid cooling process. Meanwhile the crystallization behavior is also discussed. A linear polypropylene (PPC) and a long chain branched polypropylene (PPH) are chosen as the two polymer matrices with carbon nanotubes (CNTs) as the nanofillers. During the thermal annealing process, a more obvious growth of electrical conductivity of linear PPC nanocomposites are observed compared with LCB PPH nanocomposites. The harder movement of CNTs inside LCB PPH matrix may be the main reason. This also can be reflected by the conductivity evolution during slow cooling process where a decrease‐then‐increase (DTI) phenomenon is found for PPC/CNTs systems due to the rebuilding of CNTs conductivity network after crystallization. By contrast, this does not happen for PPH/CNTs systems.

An acoustic nanogenerator based on porous PDMS/ZnO/PVDF-TrFE structure for self-powered intermediated-frequency sound monitoring

Abstract Sound energy is widely present in natural environment, nowadays predominantly collected using voluminous and heavy rigid devices, limiting their portability. Till now, there are few reports about using flexible materials to collect sound energy, and it is usually susceptible to environmental humidity. This study combines flexible polymer polydimethylsiloxane (PDMS), piezoelectric material polyvinylidene difluoride trifluoroethylene (PVDF-TrFE), nano zinc oxide (ZnO), and conductive carbon nanotubes (CNTs) to fabricate a porous nano ZnO/PVDF-TrFE/CNTs PDMS sound-driven nanogenerator (PZPCP SNG). It amalgamates frictional and piezoelectric effects: its porous structure enables efficient collection of vibration and frictional energy generated by sound waves; the piezoelectric effect of PVDF-TrFE and nano ZnO facilitates the conversion of acoustic mechanical energy, collectively enhancing the generator's output. Experimental optimization yields the best production conditions, achieving optimal outputs of 481.1 mV (open-circuit voltage), 209.13 nA (short-circuit current) under 400 Hz/125 dB sound stimuli, with a surface power density of 9.1 µW/m² (volumetric power density of 2.28 mW/m³). And it can convert sound ranging from 63-3000 Hz. With hardware circuitry, up to 5 series-connected light-emitting diodes (LEDs) can be illuminated within the circuit, demonstrating a certain degree of sound recognition capability. The proposed PZPCP SNG design is simple, effective, and lightweight, enabling flexible and stable intermediated-frequency acoustic energy harvesting. Its hydrophobic structural characteristics render it adaptable to various humidity, presenting a new approach toward widespread low-power sound detection and self-powering applications.

Facile Incorporation of Carbon Nanotubes into the Concrete Matrix Using Lignosulfonate Surfactants

One of the ways to turn concrete into smart concrete involves the incorporation of conductive fillers. These fillers should be evenly distributed in the matrix to enable the charge propagation necessary for sensing. To homogenize the mixture, typical surface-active chemical compounds are routinely employed. Unfortunately, their presence often negatively impacts the characteristics of concrete. In this work, we show that conductive multi-walled carbon nanotubes (MWCNTs) can be included in the concrete matrix by using off-the-shelf lignosulfonate-based plasticizers. These plasticizers showed a much-improved capability to disperse MWCNTs compared to other routinely used surfactants. They also prevented a significant deterioration of the consistency of the mixture and inhibited the acceleration of the hydration process by MWCNTs. In concretes with MWCNTs and lignosulfonate-based plasticizers, the mechanical properties were largely preserved, while the nanocomposite became electrically conductive. Consequently, it enabled evaluation of the condition of the material by electrical impedance measurements.

Conductive Framework Materials for Chemiresistive Detection and Differentiation of Toxic Gases.

ConspectusSensing complex gaseous mixtures and identifying their composition and concentration have the potential to achieve unprecedented improvements in environmental monitoring, medical diagnostics, industrial safety, and the food/agriculture industry. Electronically transduced chemical sensors capable of recognizing and differentiating specific target gases and transducing these chemical stimuli in a portable electronic device offer an opportunity for impact by bridging the utility of chemical information with global wireless connectivity. Among electronically transduced chemical sensors, chemiresistors stand out as particularly promising due to combined features of low-power requirements, room temperature operation, non-line-of-sight detection, high portability, and exceptional modularity. Relying on changes in resistance of a functional material triggered by variations in the surrounding chemical environment, these devices have achieved part-per-billion sensitivities of analytes by employing conductive polymers, graphene, carbon nanotubes (CNTs), metal oxides, metal nanoparticles, metal dichalcogenides, or MXenes as sensing materials. Despite these tremendous developments, the need for stable, selective, and sensitive chemiresistors demands continued innovation in material design in order to operate in complex mixtures with interferents as well as variations in humidity and temperature.To fill existing gaps in sensing capabilities, conductive metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) have recently emerged as a promising class of materials for chemiresistive sensing. In contrast to previously reported chemiresistors, these materials offer at least three unique features for gas sensing applications: (i) bottom-up synthesis from molecularly precise precursors that allows for strategic control of material-analyte interactions, (ii) intrinsic conductivity that simultaneously facilitates charge transport and signal transduction under low power requirements, and (iii) high surface area that enables the accessibility of abundant active sites and decontamination of gas streams by coordinating to and, sometimes, detoxifying harmful analytes. Through an emphasis on molecular engineering of structure-property relationships in conductive MOFs and COFs, combined with strategic innovations in device integration strategies and device form factor (i.e., the physical dimensions and design of device components), our group has paved the way to demonstrating the multifunctional utility of these materials in the chemiresistive detection of gases and vapors. Backed by spectroscopic assessment of material-analyte interactions, we illustrated how molecular-level features lead to device performance in detection, filtration, and detoxification of gaseous analytes. By merging the bottom-up synthesis of these materials with device integration, we show the versatility and scalability of using these materials in low-power electronic sensing devices. Taken together, our achievements, combined with the progress spearheaded on this class of materials by other researchers, establish conductive MOFs and COFs as promising multifunctional materials for applications in electronically transduced, portable, low-power sensing devices.

Wet-Spinning Carbon Nanotube/Shape Memory Polymer Composite Fibers with High Actuation Stress and Predesigned Shape Change.

Actuators based on shape memory polymers and composites incorporating nanomaterial additives have been extensively studied; achieving both high output stress and precise shape change by low-cost, scalable methods is a long-term-desired yet challenging task. Here, conventional polymers (polyurea) and carbon nanotube (CNT) fillers are combined to fabricate reinforced composite fibers with exceptional actuation performance, by a wet-spinning method amenable for continuous production. It is found that a thermal-induced shrinkage step could obtain densified strong fibers, and the presence of CNTs effectively promotes the tensile orientation of polymer molecular chains, leading to much improved mechanical properties. Consequently, the CNT/ polyurea composite fibers exhibit stresses as high as 33MPa within 0.36 s during thermal actuation, and stresses up to 22MPa upon electrical stimulation enabled by the built-in conductive CNT networks. Utilizing the flexible thin fibers, various shape change behavior are also demonstrated including the conversion between different structures/curvatures, and recovery of predefined simple patterns. This high-performance composite fibers, capable of both thermal and electrical actuation and produced by low-cost materials and fabrication process, may find many potential applications in wearable devices, robotics, and biomedical areas.

Stochastic Multiscale Modeling of Electrical Conductivity of Carbon Nanotube Polymer Nanocomposites: An Interpretable Machine Learning Approach

This study introduces an interpretable machine learning (ML) framework for efficiently predicting the electrical conductivity of carbon nanotube (CNT)/polymer nanocomposites. A stochastic multiscale numerical model based on representative volume element (RVE) is employed to generate a representative dataset. This dataset is used to train three ML models, including random forest, XGBoost, and artificial neural networks (ANN). The dataset includes six input features: CNT length, aspect ratio, intrinsic CNT conductivity, number of CNT conduction channels, energy barrier height, and volume fraction, with the electrical conductivity of the nanocomposites as the output feature. The findings highlight the exceptional accuracy of the ANN model in predicting electrical conductivity at significantly lower computational costs. Furthermore, the use of Shapley additive explanations (SHAP) enhances the interpretability of these ML models, identifying the volume fraction, energy barrier height, and intrinsic CNT conductivity as the most influential factors affecting conductivity. This approach sets the stage for rapid and efficient modeling of CNT/polymer nanocomposites facilitating the design of materials with tailored electrical properties for diverse applications.

Ultrasmall Fe‐Nanoclusters‐Anchored Carbon Polyhedrons Interconnected with Carbon Nanotubes for High‐Performance Zinc‐Air Batteries

The catalytic activity of metal catalyst is closely related to its particle size. Yet, the size effect in electrocatalytic oxygen reduction reaction (ORR), an important reaction for metal‐air batteries and fuel cells, has not been clearly studied. Herein, a two‐step anchoring method is utilized to control the Fe catalyst in forms of nanoparticles (NPs), ultrasmall nanoclusters (NCTs), and isolated atoms as well as stabilized and dispersed by carbon polyhedrons interconnected with carbon nanotubes (CNTs). The uniformly distributed Fe NCTs displays superior ORR performance compared with Fe NPs, isolated Fe atoms, and commercial Pt/C. The brilliant ORR activity of Fe NCTs is a result of its unique electron structure and abundant edge and corner active sites. Due to the porous structure of carbon polyhedrons and high electron conductivity of CNTs, Fe NCTs also delivers an excellent discharge performance in zinc‐air battery with a peak power density of 213.3 mW cm−2 and long‐term stability. In these findings, a new strategy for the design of metal NCTs catalysts applied in various catalytic reactions is opened up.

Dual carbon confining SnO2 nanocrystals as high-performance anode for sodium-ion batteries

The increasing global demand for sustainable energy sources has driven research into sodium-ion batteries (SIBs) for large-scale energy storage. However, their electrochemical performance is hindered by poor reaction kinetics and significant volume expansion in electrode materials. In this work, we developed a dual-carbon-confined SnO2 nanocrystal anode (CNTs@SnO2@NC) designed for high-performance SIBs. This innovative structure uses carbon nanotubes (CNTs) and a nitrogen-doped carbon (NC) coating to stabilize SnO2, ensuring structural integrity during charge/discharge cycles. The CNTs network in CNTs@SnO2@NC can alleviate the agglomeration of SnO2 nanocrystals to a certain extent; With its superior electronic conductivity, CNTs can enhance the anode's conductivity and function as an electronic highway; The sodiophilic properties and good electrical conductivity of CNTs enable sodium ions to migrate rapidly on the surface of the nanotubes. Moreover, numerous external defects and active sites generated by nitrogen doping enhance the sodium ion absorption capabilities; The existence of nitrogen-doped carbon coating can effectively accommodate the volume changes of SnO2 and enhance the structural stability of CNTs@SnO2@NC composites during the repeated charge and discharge cycles. As a result, the CNTs@SnO2@NC composite demonstrates excellent electrochemical performance, achieving capacity of 235 mAh g−1 at 0.1 A g−1 over 100 cycles and 102 mAh g−1 at 1.0 A g−1 over 300 cycles. In a full-cell configuration with a Na3V2(PO4)3 cathode, it delivers 38 mAh g−1 at 100th cycle at 0.1 A g−1. This study underscores the substantial improvements achieved by dual-carbon confinement for high-performance SIB anodes, offering a promising direction for future anode material design.

In-situ self-catalyzed fabricating carbon nanotubes on [010] preferential LiMn0.5Fe0.5PO4 nanoplates to achieve excellent high rate performance

Nano carbon material composites significantly enhance the performance of lithium manganese iron phosphate (LMFP) cathode materials. This study investigates the self-catalytic growth mechanism of highly conductive carbon nanotubes (CNTs) on bare LMFP particles via chemical vapor deposition (CVD), focusing on the influence of particle size and crystallographic orientation. It is found that the Fe3C particles formed on static solvothermal synthesized LMFP nanoplates with high [010] orientation were effective to catalyze the generation of CNTs. Diverse CVD durations produced CNTs coatings with varying structures to impact electrochemical properties of final products. The MP-L/CNTs-2 sample, with 3.6 wt% carbon, showed the highest reversible capacity of 158 mAh g−1 at 1 C with 99.3 % capacity retention after 400 cycles, after 3000 cycles at 10 C, the retention rate was 74.5 %. In contrast, LMFP synthesized via solid-phase method (MP-S/C) only formed a carbon film on the surface and delivered 143 mAh g−1 at 1 C (97.6 % retention after 400 cycles) with prominent capacity loss at 10 C. This study provides new insights into the self-catalytic growth mechanism of CNTs to promote ion-electron conductivity and structural stability of LMFP materials, thus improving kinetic property and cycling stability for high-performance lithium-ion batteries.

Microscopic in situ observation of electromechanical instability in a dielectric elastomer actuator utilizing transparent carbon nanotube electrodes.

Electromechanical instability (EMI) restricts the performance of dielectric elastomer actuators (DEAs), leading to premature electrical breakdown at a certain voltage. However, macro-level observations using traditional carbon grease electrodes have failed to capture the detailed features of EMI. In this study, we investigated EMI at the microscopic scale by fabricating transparent and conductive single-walled carbon nanotube (SWCNT) electrodes. Our findings reveal that EMI predominantly occurs in highly localized regions with dimensions on the order of tens of micrometers. This snap-through instability is likely induced by pre-existing defects within the elastomer, such as air voids or conductive particles, which reduce the critical voltage required for EMI in the flawed areas. From the perspective of phase transition principles, these defects act as heterogeneous nucleation sites for new phase embryos, thereby lowering the energy barrier for the electromechanical phase transition (i.e., EMI) compared to homogeneous nucleation in an ideally impurity-free elastomer. This study clarifies the longstanding discrepancy between theoretically predicted deformation bursts and the experimentally observed macroscopic continuous expansion of DEAs under low pre-stretch conditions. Additionally, it underscores the critical importance of material purity in mitigating electromechanical instability.

Electrocatalyst with a covalent organic framework and conducting skeleton for simultaneous determination of adenine and guanine

In this study, we integrated Cu porphyrin-based covalent organic frameworks (TTCOF-Cu) with high-activity CuNC centers and conductive backbone-functionalized carbon nanotubes (NH2-CNTs). The obtained NH2-CNTs@TTCOF-Cu composites exhibited a unique structure, and the bonding of TTCOF-Cu to NH2-CNTs allowed their in situ growth, which demonstrated high conductivity and more active sites. Consequently, well-separated and defined oxidation peaks for guanine (G) and adenine (A) were presented by differential pulse voltammetry (DPV) at NH2-CNTs@TTCOF-Cu modified electrode, and high sensitivity and selectivity were also achieved. The linear range for detecting G and A was 0.05–200 μM, respectively, and the detection limits for G and A were as low as 0.0163 and 0.0155 μM. It was also successfully applied to the analysis of G and A in heat-denatured herring sperm DNA samples.

Significant performance enhancement of Zn-ion hybrid supercapacitors based on microwave-assisted pyrolyzed active carbon via synergistic effect of NaHCO3 activation and CNT networks

Zinc-ion hybrid supercapacitors (ZIHSCs) represents a promising technological approach for large-scale energy storage with the combined advantages of supercapacitors and zinc-ion batteries. Unfortunately, it is still challengeable to quickly fabricate low-cost, high-performance carbonaceous cathode materials at relatively low temperature. To address such issues, herein, taking waste Eucommia ulmoides Oliver (EUO) wood as an example, we present a novel microwave-assisted carbonization (MWC) approach at relatively low temperature to quickly prepare active carbon, and we present a synergistic strategy to significantly enhance the electrochemical performance by introducing sodium bicarbonate activation (SA) and constructing conductive carbon nanotubes (CNT) networks. The MWC-SA@CNT hybrid exhibits outstanding specific capacitance of 344.2 F/g at 0.2 A/g within three-electrode system, much better than conventional high-temperature pyrolyzed AC, MWC carbon, and MWC-SA carbon. The superior performance of MWC-SA@CNT can be attributed to the synergistic effect of its large specific surface area of 1102.7 m2/g, high mesoporous percentage of 53.5%, and rich –OH and CO groups due to microwave-assisted carbonization and sodium bicarbonate activation, and rich electron transport paths due to the presence of CNT networks. Furthermore, ZIHSCs assembled by MWC-SA@CNT cathode could delivers impressive performance with excellent capacity (194.37 mA h/g at current density of 1 A/g), energy density (142.30 Wh/kg), and durability (capacitance retention rate of 97.65% after 5000 cycles). This work offers a rapid and low-temperature method for preparing wood-based active carbon with rich nanopores and strong conductivity to improve performance of Zinc ion storage.

Novel metal-organic anode material by in-situ chelating Ni2+ with tannic acid on carbon nanotube for high-performance Li storage

Lithium-ion batteries (LIBs) with natural organic anode are attracting intensive interest for application owing to their structural diversity, cost-effectiveness, eco-friendliness, and high specific capacity. However, directly usage of natural organic materials as anode materials usually encounters poor electrochemical properties such as low reversible capacity and short cycling life. Thus, developing high-performance organic electrode materials for LIBs remains a great challenge. Herein, we present a rational design and fabrication of TA-Ni@CNTs by in-situ coating TA-Ni polymers onto the surface of carbon nanotubes (CNTs) as a superior anode material for LIBs. Specifically, the highly conductive CNTs can effectively relieve the aggregation of TA-Ni and improve the electronic conductivity. Meanwhile, the strong chelation among nickel irons and catechol groups enhances the structure stability and inhibits the dissolving property. Consequently, as an anode material for LIBs, the resulting TA-Ni@CNTs achieves a high reversible capacity of 1418.8 mAh·g−1 at 0.1 A·g−1 after 216 cycles and an outstanding cycling stability with 951.1 mAh·g−1 at 0.5 A·g−1 after 323 cycles. The presented design strategy holds great promise for developing more-efficient electrode materials for LIBs.