Length Of Carbon Nanotubes Research Articles

Heat Transfer in Carbon-Nanotube Dispersions: A Simulation Study of the Role of Nanotube Morphology and Connectivity

Simulation of the behavior of carbon nanotubes (CNTs) can become a very challenging task considering their complicated shape and large aspect ratio. This study aims to elucidate the role of CNT shape, length, and connectivity during heat transfer in CNT dispersions through a three-dimensional (3D) simulator. Three characteristic shapes for the CNTs are considered, namely, straight, moderately curved, and strongly curved. The results reveal that the commonly used assumption of viewing CNTs as straight cylinders leads to significant overestimation of the overall medium conductivity. The CNT length has an important effect on the nanofluid conductivity for all types of CNT shapes considered here. In addition, use of CNTs with higher conductivity than a certain value appears to have no further beneficial effect, thus relaxing the need for extremely pure or single-wall CNTs. On the contrary, the conductivity remains a strong function of the CNT concentration and may be even increased upon organization of CNTs into loose clusters. The overall approach and concept can be extended to CNT composites in a straightforward manner.

Synthesis of in situ grown CNTs on MOF-derived Ni@CNT with tailorable microstructures toward regulation of electromagnetic wave absorption performance

Metal-Organic framework (MOF) derivatives have been applied as electromagnetic wave absorption (EMA) materials in recent years. Carbon nanotubes (CNTs) can achieve in situ growth on the surface of MOF derivatives. However, there is limited research on the EMA performance by regulating the morphology of the in situ grown CNTs. In this work, we prepared MOF-derived Ni@carbon nanotubes (Ni@CNT) with controllable length of CNTs by solvothermal and simple one-step pyrolysis method and revealed the CNT growth mechanism. We further investigated the effect of in situ grown CNT morphology on electromagnetic parameters and EMA performance. In situ grown CNTs of similar length on the surface of MOF derivatives lead to similar electromagnetic parameters. When the length of CNTs is short, the relaxation strength (Δε=εs−ε∞) is high, leading to excellent microwave absorption performance. For Ni@CNT-600, the reflection loss of −44.4 dB can be achieved at merely 1.72 mm. Finite element (FE) simulation was used to evaluate the EMA mechanism of different samples by calculating electric field and polarization strength. This work has explored the electromagnetic wave absorption performance from the perspective of microstructural tailoring, helpful for understanding the unique role of the in situ grown CNTs on the surface of MOF derivatives and investigating the ultra-thin electromagnetic wave absorption materials.

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.

A Mechanism of Resistance Switching in CNT Based Memory Devices

Carbon nanotubes (CNTs) show promise for high energy efficiency electronic devices due to their high electrical conductivity. One possible application is in the fabrication of resistance-change computer memory, where the application of an external electrical bias can use a CNT layer as the switching element in a RAM cell. Memory cells of this type have been extensively demonstrated, where the electrical resistance of a switching layer of CNTs can be reversibly controlled by the application of external bias [1].To better understand these devices, we have developed a nanoscale model of their electrical switching. Towards this end, first-principles calculations of the electrical conductivity of CNT-CNT junctions were performed using the Density Functional Tight Binding (DFTB) in combination with the Non-Equilibrium Greens functions (NEGF) approach, enabling an improved understanding of the tunnelling of electrons across a range of CNT junctions [2]. These results demonstrate that the conductivity of CNT contacts depends on the overlap area between nanotubes and exponentially on the distances between the carbon atoms of the interacting CNTs. Secondly, we employed coarse-grained molecular dynamics [3,4] to produce nanoscale dense CNT film models like those used in the devices. We devise a set of metrics for characterising the structural properties of CNT films, and apply them to a set of model films designed to mimic those used in microelectronics devices. In order to understand how the geometrical properties of CNTs affect the film structure, we analyse films with different CNT chirality and length distributions. Unlike previous studies that focused on relatively low-density systems below ∼0.4 g/cm3, we also consider films with density of ∼0.6 g/cm3, as employed in experimentally fabricated CNT-based NRAM devices. By adding amorphous carbon to the film models, in varying amounts, we are then able to assess its effects. Finally, these two elements were combined to produce electrical simulations of the conductivity of the CNT films connected to TiN electrodes. These electrodes are shown to be partially oxidized during the device fabrication. The electrical conductivity in a device is characterized by formation of conduction paths formed by CNTs between the electrodes and connected via the CNT junctions. The conductivity is modulated by charging of CNTs and amorphous carbon present in the film.Using these simulations, we propose a resistance switching mechanism in TiN/CNT/TiN devices based on the physical movement of CNTs. During the initial operation of the device, oxygen is released from the oxidized bottom electrode and this readily reacts with individual CNTs to form charge trapping sites. Once these sites have become charged, they enable controllable movement of CNTs at the bottom electrode under the application of electric field. By reversibly connecting and disconnecting such CNTs from the bottom electrode, the electrical conductivity through the CNT film as a whole can be controlled.

Fabrication of composite nanostructures for impedance biosensors using anodic aluminum oxide templates and carbon nanotubes

A hybrid material consisting of an array of vertically ordered carbon nanotubes (CNTs) in porous anodic alumina was fabricated directly on oxidized Si substrates. Individual CNTs with vertical orientation were grown using the catalyst Ni nanoparticles (NPs) embedded in the pore walls of a thin template based on porous anodic alumina with a pore diameter of 40 ± 5 nm. The initial film was a two-layer Ti-Al structure on a Si/SiO2 substrate. A vertically oriented porous structure was formed by anodizing the Al layer. Electrochemical deposition was used to form the catalyst Ni-NPs with dimensions of 30 ± 5 nm. CNTs were synthesized by high-temperature chemical vapor deposition. Scanning and transmission electron microscopy, Raman spectroscopy, and X-ray diffraction were used to analyze the surface morphology and microstructure of the composite nanostructures. The CNT length was (0.6–1.5) μm, and the CNT spacing was 110 ± 10 nm. It is expected that the resulting structure will serve as a basis for the development of CNT-based electrodes for electrochemical impedance biosensors. Electrochemical impedance spectroscopy was used for the electrochemical characterization of the fabricated CNT-based electrodes. The results showed that the CNT-based electrodes are characterized by improved electron transfer kinetics.

Purification of carbon nanotubes for dissolution in chlorosulfonic acid

Carbon nanotubes (CNTs) can be scalably processed into high-performance fiber with a low environmental footprint by solution spinning from chlorosulfonic acid (CSA). CNTs are produced by numerous manufacturers, but CNTs typically need to undergo purification to improve solubility in CSA. For over two decades, oxidative techniques have been used to remove amorphous carbon species to improve CNT dissolution in acid. However, more recent work has attributed the improved solubility after single-walled carbon nanotube (SWCNT) oxidation to the inclusion of oxygen groups in the sidewall of the SWCNT. Here, we refute the recent claim that oxidation incorporates oxygen into the sidewall of CNTs to improve CNT dissolution to CSA. Instead, we provide experimental evidence in support of classical purification literature: at the appropriate time and temperature, oxidation removes amorphous carbon shells and defective SWCNTs without oxidizing the SWCNT sidewall. Once these amorphous carbon shells are removed, CSA can access and protonate the sp2-bonded carbon sites, which results in SWCNT dissolution. Additionally, we explore how oxidation conditions impact SWCNT aspect ratio (length of CNT divided by CNT diameter), which directly controls macroscale fiber properties.

Comprehensive correlation analysis of electromechanical behavior in high-stretchable carbon nanotube/polymer composites

In this study, a comprehensive correlation analysis of highly stretchable carbon nanotube (CNT)/polymer composites was conducted to predict the change in electrical conductivities in response to uniaxial deformation. To this end, the representative volume elements (RVEs) were generated by randomly distributing CNTs in a polymer matrix using a Monte Carlo simulation algorithm. The effective electrical conductivity was then calculated through a network model. Under uniaxial tensile strain, where the length of CNTs was maintained constant and their configuration kept straight, CNT translation and rotation were considered along with the effects of tensile strain and shrinkage, incorporating Poisson’s ratio. The RVE configuration was updated to account for changes in the network under these conditions. To achieve a strong correlation between the simulation and test results from the previously published works, numerous trade-off studies have been conducted on the RVE size, geometric periodicity, the length of CNT fibers, the mixing ratio of CNT fibers of CNT/polymer composites, and tensile strain. From the results it can be seen that excellent correlations can be only achieved with careful control of the aforementioned parameters.

Mechanical improvement of carbon fiber/epoxy composites by sizing functionalized carbon nanotubes on fibers

AbstractA sizing agent mainly consisting of polyethersulfone and acidified multi‐walled carbon nanotubes (MWCNT) was developed for surface modification of carbon fibers (CF) to enhance the interfacial bond and to form carbon fiber‐carbon nanotube (CF‐MWCNT) multiscale reinforcements. To prepare the modified carbon fiber/epoxy resin composites (CFRP), a vacuum molding technique was used in this study. The effects of the MWCNT‐containing sizing agent on the morphology and chemical structure of the CF surface were observed by scanning electron microscopy and Fourier transform infrared spectroscopy. The influence of MWCNT length and content on the mechanical properties of CFRP were also studied. The experimental results showed that the strength of the CFRP decreased with the increase of MWCNT length, and the MWCNT with a content of 0.05 wt% had a good reinforced effect on the CFRP. After the sizing treatment, the interlaminar shear strength (ILSS) of the CFRP is increased. These enhancements are attributed to the improved mechanical bonding and chemical bonding between CF and resin matrix. The MWCNT provides nanosized rough surface to CF and these acidified MWCNTs attached to the surface of CF with polar oxygen‐containing functional groups improve the compatibility with reinforcement and resin matrix.Highlights Carbon fiber was modified by a sizing agent mainly consisting of polyethersulfone and acidified carbon nanotube (CNT). CNTs enhance the interfacial chemical bonding and mechanical bonding. The CNT length affects the mechanical properties of the carbon fiber/epoxy resin composites (CFRP). The modified carbon fiber has enhanced the mechanical properties of the CFRP.

Microstructure regulation and enhanced VOC removal performance of carbon aerogels by surface carbon nanotube grown

Carbon aerogels were newly employed in adsorption for volatile organic compounds (VOCs) as an emerging material. In contrast, the microstructure and high carbon consumption are the primary factors restricting their application scenarios. Carbon nanotubes, recognized for their controllable cylindrical hollow structure and hydrophobic walls, generally possess higher adsorption capacities than typical carbon adsorbents. In this study, carbon nanotubes were grown on the surface of carbon aerogels using the chemical vapor deposition method by controlling different deposition conditions. The results showed that the modified samples displayed the maximum adsorption capacity of 145.0 mg/g and 178.3 mg/g for toluene and 1,2- dichlorobenzene, respectively. After ten regeneration cycles, the performance decreased by 7.9 % and 5.6 %, respectively. Meanwhile, the carbon replenishment was about 0.2 g/g, which is an excellent complement for carbon consumption. Various characterization patterns showed that deposition temperature was reflected in its deposition rate, deposition times influenced the formation of multi-walled carbon nanotubes, and deposition concentration affected the length of carbon nanotubes. This study offers valuable insight into the growth patterns of carbon nanotubes and the microscale regulation of carbon material surfaces, and this method is expected to be an effective means of carbon replenishment, carbon addition to carbon-poor materials, and enhancement of VOCs removal performance, and the growth mechanisms investigated are instructive for practical applications.

Ultra-low detection limit self-sensing nanocomposites with self-assembled conductive microsphere arrays for asphalt pavement health monitoring

Accurately monitoring micro-level strain within pavements poses a significant challenge in contemporary road engineering, limiting the effectiveness of early-stage pavement health diagnostics. Addressing this critical gap, this study introduces an innovative ultra-low detection limit sensor, specifically designed for intricate pavement health monitoring. It pivots on the unique structural design of a well-ordered 3D conductive network, where the self-assembly effect of microsphere arrays ingeniously mitigates the prevalent issue of nanofiller agglomeration within polymer matrices. The study highlights the significant role of carbon nanotubes (CNTs) length in shaping the structure of conductive networks, revealing that while longer CNTs lead to less uniform microsphere assemblies, they significantly enhance the bridging effect crucial for conductive pathways. To balance these traits, surface chemical modifications were strategically applied, effectively enhancing microsphere organization and dispersion, thereby elevating the conductive and sensing performance. The optimized sensor stands out for the ultra-low detection limit of 0.0005% (5 uε), significantly surpassing those of current strain sensors. Moreover, it exhibits remarkable sensitivity, evidenced by a gauge factor of 13.2, along with swift response and recovery times of 19 ms and 26 ms respectively, and impressive durability, enduring over 100,000 loading-unloading cycles. Field tests under diverse vehicular loads and speeds further validate the sensor's accuracy in capturing dynamic responses within pavement structures, a key factor in proactive pavement maintenance and management. Hence, this advancement shows promise in contributing to the development of safer and more resilient road networks, playing a beneficial role in the significant progress of intelligent transportation and sustainable infrastructure management.

Impact of length and radius of carbon nanotubes on flow and heat transfer in converging and diverging channels with entropy generation

This research examines the complex interplay between the carbon nanotubes' length and radius and how that affects flow patterns, heat transfer properties, and entropy creation in both convergent and divergent channels. Our research elucidates the mechanisms at play by revealing a crucial link between carbon nanotube dimensions and the efficacy of heat transfer processes. In particular, carbon nanotubes with a longer length have better heat transmission properties, while carbon nanotubes with a smaller radius generate less entropy. From microfluidics to energy-efficient materials, these results show significant promise for optimizing thermal systems and improving performance. This research looks on the differences between the thermal transports of single- and multi-walled carbon nanotubes in water. Thermo physical characteristics of carbon nanoparticles are one of a kind and essential for this purpose. The fluid is assumed to be incompressible and to flow steadily a two-dimensional plane. The effects of thermal radiation on the heat transfer of a water-based fluid in convergent and divergent channels with decreasing and expanding walls have been studied. In order to quickly sketch the equations, the RK-4 method with shooting approach is used, and similarity transformation is employed to reduce their dimensionality. The key factors influencing hydrothermal performance have been visualized through the use of graphs. The production numbers of entropy are also shown and explained at length. The obtained data supports the reliability of the approach used. Surface heat transport was found to be negatively impacted by elongation. Colloidal single-walled carbon nanotube (SWCNT) suspensions in water had higher thermal conductivity than water itself.

A multiscale modeling framework for predicting strain‐dependent electrical conductivity of carbon nanotube‐incorporated nanocomposites considering the electron tunneling effect

AbstractThe present work proposes a multiscale modeling framework for predicting the strain‐dependent electrical conductivity of carbon nanotube (CNT)‐incorporated nanocomposites considering the electron tunneling effect. A micromechanical model taking into account the waviness of the CNTs is utilized and molecular dynamics simulations estimating changes in distance between CNTs in the polymer matrix are conducted in an attempt to incorporate the electron tunneling effect. A series of numerical parametric studies are carried out to examine the influence of model parameters (e.g., CNT length, number of CNT segments, and intrinsic interfacial resistivity) on the strain‐dependent electrical conductivity of the nanocomposites. In addition, CNT/polydimethylsiloxane samples are fabricated and their strain‐dependent electrical conductivity is experimentally evaluated. Finally, to verify the predictive capability of the proposed modeling framework, the present predictions are compared with experimental results.Highlights A multiscale modeling framework of CNT‐incorporated nanocomposites is proposed. A micromechanics model and molecular dynamics simulations are used. The study includes a numerical parametric investigation. The present predictions are compared with those obtained experimentally.

Predicting mechanical properties of 3D printed nanocomposites using multi-scale modeling

The main objective of this research is to predict the Young’s modulus of 3D-printed specimens made of nanocomposites. Printable nanocomposites filaments reinforced with various portions of carbon nanotubes (CNTs) are produced at the first stage. At the second stage, extruded nanocomposite filaments are fed into a 3D desktop printer and tensile specimens are printed with two different infill patterns. A multi-scale modeling is developed as a hierarchical computational procedure covering involved scales of micro, meso and macro. Treating CNT length, orientation and agglomeration as random parameters, stochastic modeling is performed. CNT length is considered at microscale, while CNT agglomeration and orientation are taken into account at the scale of meso. The infill patterns and printing parameters are captured at the uppermost scale of macro. The Young’s modulus of both nanocomposite filaments and 3D printed samples are predicted and compared with the results of experimental characterization.

Multiple graphdiyne‐like chains self‐assemble into carbon nanotubes

The formation process of core–shell structure from multiple graphdiyne‐like chains and carbon nanotube is investigated by a molecular dynamics simulation. Multiple graphdiyne‐like chains self‐curl into helical structures located inside carbon nanotubes. The entire process involves two steps: sliding and twisting. A detailed analysis is conducted on the formation mechanism. Both the van der Waals potential well and the π–π stacking interaction between carbon nanotube and graphdiyne‐like chains play a major role in the self‐assemble process. Furthermore, the influence factors such as the number of graphdiyne‐like chains, the diameter of carbon nanotube, the length of carbon nanotube, the length of graphdiyne‐like chains, and the simulation temperature is also investigated. The research results are an important theoretical basis for manufacturing high‐quality carbon nanomaterials and other novel nanostructures.

Analytical modeling of the electrical conductivity of CNT-filled polymer nanocomposites

Electrical conductivity of most polymeric insulators can be drastically enhanced by introducing a small volume fraction [Formula: see text] of conductive nanofillers. These nanocomposites find wide-ranging engineering applications from cellular metamaterials to strain sensors. In this work, we present a mathematical model to predict the effective electrical conductivity of carbon nanotubes (CNTs)/polymer nanocomposites accounting for the conductivity, dimensions, volume fraction, and alignment of the CNTs. Eshelby’s classical equivalent inclusion method (EIM) is generalized to account for electron-hopping—a key mechanism of electron transport across CNTs, and is validated with experimental data. Two measurements, namely, the limit angle of filler orientation and the probability distribution function, are used to control the alignment of CNTs within the composites. Our simulations show that decreasing the angle from a uniformly random distribution to a fully aligned state significantly reduces the transverse electrical conductivity, while the longitudinal conductivity shows less sensitivity to angle variation. Moreover, it is observed that distributing CNTs with non-uniform probability distribution functions results in an increase in longitudinal conductivity and a decrease in transverse conductivity, with these differences becoming more pronounced as the volume fraction of CNTs is increased. A reduction in CNT length decreases the effective electrical conductivity due to the reduced number of available conductive pathways while reducing CNT diameter increases the conductivity.

Effects of Topological Parameters on Thermal Properties of Carbon Nanotubes via Molecular Dynamics Simulation

Due to their unique properties, carbon nanotubes (CNTs) are finding a growing number of applications across multiple industrial sectors. These properties of CNTs are subject to influence by numerous factors, including the specific chiral structure, length, type of CNTs used, diameter, and temperature. In this topic, the effects of chirality, diameter, and length of single-walled carbon nanotubes (SWNTs) on the thermal properties were studied using the reverse non-equilibrium molecular dynamics (RNEMD) method and the Tersoff interatomic potential of carbon–carbon based on the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). For the shorter SWNTs, the effect of chirality on the thermal conductivity is more obvious than for longer SWNTs. Thermal conductivity increases with increasing chiral angle, and armchair SWNTs have higher thermal conductivity than that of zigzag SWNTs. As the tube length becomes longer, the thermal conductivity increases while the effect of chirality on the thermal conductivity decreases. Furthermore, for SWNTs with longer lengths, the thermal conductivity of zigzag SWNTs is higher than that of the armchair SWNTs. Thermal resistance at the nanotube–nanotube interfaces, particularly the effect of CNT overlap length on thermal resistance, was studied. The simulation results were compared with and in agreement with the experimental and simulation results from the literature. The presented approach could be applied to investigate the properties of other advanced materials.

Controlled synthesis, properties, and applications of ultralong carbon nanotubes.

Carbon nanotubes (CNTs) are typical one-dimensional nanomaterials which have been widely studied for more than three decades since 1991 because of their excellent mechanical, electrical, thermal, and optical properties. Among various types of CNTs, the ultralong CNTs which have lengths over centimeters and defect-free structures exhibit superior advantages for fabricating superstrong CNT fibers, CNT-based chips, transparent conductive films, and high-performance cables. The length, orientation, alignment, defects, cleanliness, and other microscopic characteristics of CNTs have significant impacts on their fundamental physical properties. Therefore, the controlled synthesis and mass production of high-quality ultralong CNTs is the key to fully exploiting their extraordinary properties. Despite significant progress made in the study of ultralong CNTs during the past three decades, the precise structural control and mass production of ultralong CNTs remain a great challenge. In this review, we systematically summarize the growth mechanism and controlled synthesis strategies of ultralong CNTs. We also introduce the progress in the applications of ultralong CNTs. Additionally, we summarize the scientific and technological challenges facing the mass production of ultralong CNTs and provide an outlook and in-depth discussion on the future development direction.

Significant thermal rectification induced by phonon mismatch of functional groups in a single-molecule junction

Single-molecule junctions (SMJs) may bring exotic physical effects. In this work, a significant thermal rectification effect is observed in a cross-dimensional system, comprising a diamond, a single-molecule junction, and a carbon nanotube (CNT). The molecular dynamics simulations indicate that the interfacial thermal resistance varies with the direction of heat flow, the orientation of the crystal planes of the diamond, and the length of the CNT. We find that the thermal rectification ratio escalates with the length of the CNT, achieving a peak value of 730% with the CNT length of 200 nm. A detailed analysis of phonon vibrations suggests that the primary cause of thermal rectification is the mismatched vibrations between the biphenyl and carbonyl groups. This discovery may offer theoretical insights for both the experimental exploration and practical application of SMJs in efficient thermal management strategy for high power and highly integrated chips.

Understanding the Mechanism of the Structure-Dependent Mechanical Performance of Carbon-Nanotube-Based Hierarchical Networks from a Deformation Mode Perspective.

Carbon nanotube (CNT)-based networks have wide applications, in which structural design and control are important to achieve the desired performance. This paper focuses on the mechanism behind the structure-dependent mechanical performance of a CNT-based hierarchical network, named a super carbon nanotube (SCNT), which can provide valuable guidance for the structural design of CNT-based networks. Through molecular dynamic (MD) simulations, the mechanical properties of the SCNTs were found to be affected by the arrangement, length and chirality of the CNTs. Different CNT arrangements cause variations of up to 15% in the ultimate tensile strains of the SCNTs. The CNT length determines the tangent elastic modulus of the SCNTs at the early stage. Changing the CNT chirality could transform the fracture modes of the SCNT from brittle to ductile. The underlying mechanisms were found to be associated with the deformation mode of the SCNTs. All the SCNTs undergo a top-down hierarchical deformation process from the network-level angle variations to the CNT-level elongations, but some vital details vary, such as the geometrical parameters. The CNT arrangement induces different deformation contributors of the SCNTs. The CNT length affects the beginning point of the CNT elongation deformation. The CNT chirality plays a crucial role in the stability of the junction's atomic topology, where the crack propagation commences.

Tensile strength and toughness of carbon nanotube-graphene foam composite materials and the corresponding microscopic influence mechanism

Carbon nanotube (CNT)-graphene foam (GF) composites (CGFCs) have garnered considerable attention due to their unique properties. However, the factors and mechanisms influencing their tensile strength and toughness remain unclear. Here, the influence of graphene stiffness, CNT length, and CNT number on the tensile strength and toughness of pure GF and CGFC was investigated using coarse-grained molecular dynamics. It shows that CGFC exhibits improved strength (66.5 MPa) and toughness (34.4 MJ/m3) compared to pure GF (18.0 MPa and 11.2 MJ/m3) due to enhanced interconnectivity among graphene flakes through additional graphene-CNT-graphene contacts. Notably, the effect of graphene stiffness on the tensile properties reveals an interesting observation: lower stiffness of the graphene correlates with higher strength and toughness of the foam. This phenomenon arises from the increased deformability of softer graphene, promoting the formation of more graphene-graphene and graphene-CNT-graphene contacts. As a result, the interconnectivity is significantly enhanced, leading to improved strength and toughness. Furthermore, greater CNT length and number contribute to the increased strength and toughness. This effect can predominantly be attributed to the growing number of graphene-CNT-graphene contacts, which enhances the connectivity between graphene. These insights inform the design of high-strength and tough materials using CNTs and graphene.