Graphene Hybrid Research Articles

Introducing CuCo2S4 Nanoparticles on Reduced Graphene Oxide for High-Performance Supercapacitor.

In this work, a bimetallic sulfide-coupled graphene hybrid was designed and constructed for capacitive energy storage. The hybrid structure involved decorating copper-cobalt-sulfide (CuCo2S4) nanoparticles onto graphene layers, with the nanoparticles anchored within the graphene layers, forming a hybrid energy storage system. In this hybrid structure, rGO can work as the substrate and current collector to support the uniform distribution of the nanoparticles and provides efficient transportation of electrons into and out of the electrode. In the meantime, CuCo2S4-active materials are expected to offer an evident enhancement in electrochemical activities, due to the rich valence change provided by Cu and Co. Benefiting from the integrated structure of CuCo2S4 nanoparticles and highly conductive graphene substrates, the prepared CuCo2S4@rGO electrode exhibited a favorable capacitive performance in 1 M KOH. At 1 A g-1, CuCo2S4@rGO achieved a specific capacitance of 410 F g-1. The capacitance retention at 8 A g-1 was 70% of that observed at 1 A g-1, affirming the material's excellent rate capability. At the current density of 5 A g-1, the electrode underwent 10,000 charge-discharge cycles, retaining 98% of its initial capacity, which indicates minimal capacity decay and showcasing excellent cycling performance.

“Rooting” engineering strategy for construction of highly stable, scalable, size-customized oxidized graphene/PA6 ultrafine fiber composite nanofiltration membranes for water purification

Nanofiltration membranes based on graphene oxide exhibit substantial potential for practical applications in water treatment, poised to lead the next generation of separation technology. It is noteworthy that the prominent hydration interaction among graphene–graphene oxide nanosheets stands as the primary factor influencing its stability. Simultaneously, the absence of suitable graphene substrates presents challenges to its large-scale production. In this study, our initial endeavor involved constructing a graphene-based selective layer on a PA6 substrate using a quasi-“rooting” strategy. The graphene selective layer was anchored onto the surface of PA6 fibers (with a diameter size of up to 190.0 mm and a selective layer thickness of approximately 5.0 µm). Experimental results reveal that the permeability of the hybrid graphene oxide/PA6 fiber composite nanofiltration membrane consistently maintained within the range of 7.7 to 14.9 L m⁻² h⁻¹ bar⁻1, with a remarkable dye molecule removal rate of 99.06 %. Even under challenging operating conditions (such as strong acid, strong alkali, polar solvent, oxidation, and the coexistence of salt ions), its separation performance remained stable. The permeability of composite membranes was retained between 10.6 and 12.7 L m⁻² h⁻¹ bar⁻1, and the rejection rate of CR dye reached 95.0 % under harsh conditions. Furthermore, the stability and anti-fouling performance of the composite membrane were significantly enhanced. Deposits on the membrane surface could be effectively removed through physical wiping and repeated water rinsing, maintaining membrane integrity even after vigorous ultrasonic cleaning (120 min, 950 W). Additionally, after undergoing 20 cycles of rinsing with deionized water and a 30-day soak in an aqueous solution, the PA6 substrate and graphene selective layer exhibited robust adhesion. No shedding was observed, and the dye rejection rate of the composite membrane consistently exceeded 95 %. This perfectly illustrates the exceptional structural stability and separation durability of the prepared separation membrane. Our work contributes fundamental design principles and theoretical insights for practical applications.

Dual-band perfect absorption graphene metasurface with high modulation in near-infrared

Graphene has garnered significant attention in tunable metasurfaces due to its unique optical properties. The absorption of the graphene metassurface can be dynamically adjusted by manipulating the chemical potential. However, the working wavelengths of most graphene metasurfaces are limited in terahertz and mid-infrared, or have a low reflection range. In this paper, we design a hybrid graphene metasurface with a slot structure. The working wavelengths are optimized to 1550 nm and 1910 nm. Additionally, the slot structure greatly enhances the field intensity near the monolayer graphene to improve its interaction with light. As a result, perfect absorption is achieved at both working wavelengths, along with a maximum reflection range of 0.9 and a modulation depth of 99%.

Strength enhancement of a flame‐retardant hybrid composite by incorporating graphene nanoparticles for structural applications

AbstractHybrid composite's flame retardancy properties play a dynamic role in structural applications. When inorganic nanomaterials form organic/inorganic nanocomposites, they exhibit superior flame‐retardant effects. Therefore, the current work investigates the combined effects of halogen‐free fire‐retardant ammonium polyphosphate (APP) and graphene (GR) nanofillers on the mechanical, and fire‐resistant behavior of hybrid composite fabricated using a vacuum bag process. Mechanical study affirmed that the concurrent incorporation of APP and GR hybrid composite improved the hardness, flexural, and tensile properties by 7%, 26%, and 16%, respectively. Scanning electron microscopy (SEM) confirms that the dispersion of 0.75 wt% GRs improved the mechanical properties by preventing crack propagation and strong binding between fiber‐matrix in the hybrid composite. The vibrational analysis reveals an improved natural frequency (NF) value was obtained with 0.75 wt% GR; further addition of GR increased the damping due to an increase in nanoparticle agglomeration. The combined effect of APP and GR decreased the hybrid composite's water uptake and porosity by 52% and 80%, respectively. The flammability study (Vertical burning) affirmed that the composite's grade score was improved from V‐1 to V‐0. Therefore, the current study emphasizes that this optimized hybrid composite can be utilized in fire‐sensitive structural applications.Highlights UL‐94 VB test reveals the flammability of the hybrid composite. Examine the combined effect of APP and GR in strength and flame‐retardant properties. GR and APP added sample shows better mechanical and flame resistance properties. The optimized wt% of GR and APP for better results is 0.75% and 9.25%. The prepared composite may suitable fire‐sensitive structural applications.

Scalable Generation of Hybrid Graphene Nanoscrolls for High-Performance Solid Lubricants

Graphene and other 2D materials have been extensively studied as solid lubricants in recent years. Low friction can sometimes be observed in those 2D lubricants, and one possible mechanism is that scroll-shaped nanostructures are formed during friction, which decreases the contact area and energy barrier, thus substantially reducing friction. The integration of graphene with metal or metal oxide nanostructures can further enhance its lubrication properties by increasing film formation ability and easy shearing of the nanosheets. However, it is not possible to reliably promote the formation of such nanoscroll-shaped low friction wear products, which limits the reproducibility and application of such nanostructures as solid lubricants. In this study, we address this issue by creating a scalable method for the synthesis of hybrid graphene-titanium oxide (G–TiO2) nanoscrolls and demonstrating their potential as solid lubricants with macroscopic coefficient of friction as low as 0.02 in ambient conditions. Our approach to generate the nanoscrolls is based on the in situ sol–gel synthesis of TiO2 on graphene followed by spray-freeze-drying–induced shape transformation. The solid lubrication performance of such G–TiO2 nanoscrolls can be further enhanced by applying a thin graphene oxide primer layer, which provides high affinity to both the substrate and the active materials. These hybrid nanoscrolls hold promising potential for applications in aerospace, automotive, and precision manufacturing fields as effective solid lubricants.Graphical

Sunlight assisted highly efficient desorption of ammonia by redox graphene hybrid metal–organic framework photothermal conversion adsorbents

The capture, storage and release of NH3 play a pivotal role in sustainable energy applications. However, to simultaneously achieve high adsorption capacity and low energy desorption remains a challenge. In this work, a novel class of hybrid materials with photothermal conversion performance have been developed by doping redox graphene and metal–organic framework of MOF-303(Al). It is found that the optimized rGO@MOF-303(Al)-8% exhibits high NH3 uptake (17.0 mmol g−1) at 25.0 °C and 1.0 bar and exceptional photothermal conversion performance. Under the irradiation of simulated sunlight, its temperature can be raised to about 75 °C in 10 min. Even under direct natural sunlight irradiation, a stable equilibrium temperature of 53 °C may be achieved. Based on this excellent photothermal conversion performance, we investigated the desorption behavior of ammonia under visible light irradiation for the first time. We found that due to the breakdown of hydrogen bonds of NH3 and N-N, N–H sites of rGO@MOF-303(Al)-8% caused by the rapid rise of temperature, approximately 68% of NH3 could be effectively desorbed in 2-hour irradiation under ambient conditions. In addition, the optimized adsorbent demonstrated remarkable cycling stability. After undergoing 10 cycles, high adsorption capacity and efficient light-induced desorption of NH3 were still maintained Thus, the present study provides a novel concept for high-capacity adsorption and low-energy desorption of NH3 and other industrial gases.

Ballistic transport and spin-dependent anomalous quantum tunneling in Rashba–Zeeman and bilayer graphene hybrid structures

In this work, we have studied the spin-dependent ballistic transport and anomalous quantum tunneling in bilayer graphene horizontally placed in between two Rashba–Zeeman (RZ) leads under external electric biasing. We investigated the transmission and conductance for the proposed system using scattering matrix formalism and the Landauer–Büttiker formula considering a double delta-like barrier under a set of experimentally viable parameters. We found that the transmission characteristics are notably different for up- and down-spin incoming electrons depending upon the strength of magnetization. Moreover, the transmission of up- and down-spin electrons is found to be magnetization orientation dependent. The maximum tunneling conductance can be achieved by tuning biasing energy and magnetization strength and choosing a material with suitable Rashba spin–orbit coupling (RSOC). This astonishing property of our system can be utilized in fabricating devices, such as spin filters. We found that the Fano factor of our system is 0.4 under strong magnetization conditions, while it reduces to 0.3 under low magnetization conditions. Moreover, we also noticed that the transmission and conductance significantly depend on the Rashba–Zeeman effect. Therefore, considering a suitable RZ material, the tunneling of the electrons can be tuned and controlled. Our result suggests that considering suitable strength and orientation of magnetization with moderate RSOC, one can obtain a different transmission probability for spin species under suitable biasing energy. These results indicate the suitability of the proposed system in fabrication of spintronic devices, such as spin filter, spin transistor, etc.

Hybrid Renewable Energy System Design using Multi-Objective Optimization

This study investigates the significant changes brought about by hybrid in renewable energy systems. It specifically examines the creation and analysis of hybrids to enhance energy conversion procedures. Graphene hybrids have remarkable potential, with a surface area of 200 m²/g and resulting in a significant 20% increase in energy conversion efficiency, achieving an astonishing 78% compared to control samples. The electrical output metrics highlight the superiority of systems enabled by hybrid, with graphene exhibiting a 20% increase in power production at 1.2 W. Stability assessments focus on the long-term sustainability, with graphene achieving a stability score of 9, suggesting strong and reliable performance. The results demonstrate the exceptional potential of hybrid, namely graphene, to transform the renewable energy sector, offering a significant improvement in efficiency and system stability.

Graphene and metal-organic framework hybrids for high-performance sensors for lung cancer biomarker detection supported by machine learning augmentation.

Conventional diagnostic methods for lung cancer, based on breath analysis using gas chromatography and mass spectrometry, have limitations for fast screening due to their limited availability, operational complexity, and high cost. As potential replacement, among several low-cost and portable methods, chemoresistive sensors for the detection of volatile organic compounds (VOCs) that represent biomarkers of lung cancer were explored as promising solutions, which unfortunately still face challenges. To address the key problems of these sensors, such as low sensitivity, high response time, and poor selectivity, this study presents the design of new chemoresistive sensors based on hybridised porous zeolitic imidazolate (ZIF-8) based metal-organic frameworks (MOFs) and laser-scribed graphene (LSG) structures, inspired by the architecture of the human lung. The sensing performance of the fabricated ZIF-8@LSG hybrid sensors was characterised using four dominant VOC biomarkers, including acetone, ethanol, methanol, and formaldehyde, which are identified as metabolomic signatures in lung cancer patients' exhaled breath. The results using simulated breath samples showed that the sensors exhibited excellent performance for a set of these biomarkers, including fast response (2-3 seconds), a wide detection range (0.8 ppm to 50 ppm), a low detection limit (0.8 ppm), and high selectivity, all obtained at room temperature. Intelligent machine learning (ML) recognition using the multilayer perceptron (MLP)-based classification algorithm was further employed to enhance the capability of these sensors, achieving an exceptional accuracy (approximately 96.5%) for the four targeted VOCs over the tested range (0.8-10 ppm). The developed hybridised nanomaterials, combined with the ML methodology, showcase robust identification of lung cancer biomarkers in simulated breath samples containing multiple biomarkers and a promising solution for their further improvements toward practical applications.

Investigation of flexible graphene hybrid knitted sensor for joint motion recognition based on convolutional neural network fusion long short-term memory network

Wearable electronics have attracted have attracted widespread attentions for their promising applications in motion monitoring and human-computer interaction. This paper proposes a flexible wearable joint movement intelligent sensing and recognition system to achieve stable and reliable motion feature extraction and recognition. Flexible graphene hybrid knitted sensor were prepared by transferring graphenes (GNs) agent onto stretchable knitted products via a simple spray-drying approach. The small dynamic movement of human joints for the prepared GNs hybrid sensing gloves, elbow pads and knee pads were converted into electrical signals for sensitive detection. The convolutional neural network fusion long short-term memory (CNN-LSTM) network with self-attention mechanism (SAM) is established for feature training and intelligent dynamic recognition of the measured joint information. The interconnected conductive networks endowed knitted sensor with good flexibility and remarkable electrical conductivity of 37 S/m. The unique conductive networks in the fabric offered excellent linearity and repeatable resistance response variation for better detection of joint motion. The resistant signal was analyzed by feature extraction, data correlation capture and time sequence relationship modeling. Finally, the test results show that the proposed CNN-LSTM with SAM network achieves 97%, 96% and 100% correct recognition rates for gesture signals, elbow and wrist signals and knee signals respectively, which is obviously higher than other recognition algorithms. It has great application prospects in the fields of smart wear, medical detection, and smart elderly care.

Sensitive and selective detection of heavy metal ions and organic pollutants with graphene-integrated sensing platforms.

Graphene-based sensors have emerged as promising tools for environmental monitoring due to their exceptional properties such as high surface area, excellent electrical conductivity, and sensitivity to various analytes. This paper presents a review of recent advancements in the development and application of graphene-based sensors for the detection of heavy metal ions and organic pollutants. These sensors employ either graphene or its derivatives, often in combination with graphene hybrid nanocomposites, as the primary sensing material. The synthesis methods of graphene and sensing mechanisms of graphene-based sensors are discussed. Furthermore, performance metrics including the determination range and detection limits of these sensors are itemized. The potential challenges and future directions in the field of graphene-based sensors for environmental monitoring are also highlighted. Overall, this review provides valuable insights into the current state-of-the-art technologies and paves the way for the development of highly efficient and reliable sensors for environmental monitoring purposes.

Porous MnO nanoplate–graphene hybrid as a high-capacity anode material for lithium ion batteries and its safety characteristics

Robust reduced graphene oxide (rGO) protected porous MnO nanoplates were constructed to relieve the pulverization and gradual aggregation during the conversion process.

Bipolar conjugated microporous polymer anchoring graphene hybrids for high-performance zinc–organic batteries

A superior molecular design allows a bipolar conjugated microporous polymer to be firmly anchored on the rGO surface. The unique anchoring structure realizes alternate Zn2+/CF3SO3− ion storage while providing high capacity and an ultra-long lifespan for zinc–organic batteries.

Hybrid carbonaceous filler as promising additives for EMI SE of PVDF-based composites: Comparison between monolayered and multilayered structures

Flexible conducting polymeric composites (CPC) for applications as electromagnetic interference (EMI) shielding materials were successfully prepared by melt-mixing approach using poly (vinylidene fluoride) (PVDF) as the matrix, loaded with hybrid carbonaceous fillers, carbon nanotube (CNT) and graphene nanoplatelets (GNP). Composites with as low as 3 wt% of filler with conductivity values in between 10−3 S/m (PVDF/GNP) and 10−1 S/m (PVDF/CNT) were successfully prepared by using hybrid with different proportions. Multi-layered structure composites displayed significantly higher EMI SE values than the bulk composites, mainly those constituted by CNT and the CNT/GNP (1.5:1.5 wt%) hybrid. By stacking PVDF/CNT, PVDF/CNT/GNP and PVDF/GNP with different arrangements, on can achieve EMI SE around 22 dB (in X-band) and 27 dB (in Ku-band) with absorption contribution of 65–70 % in the X-band and 77–81 % in the Ku-band frequency ranges. The effect of the hybrid composites on the morphological, rheological and thermal properties and on the ability of the β-phase formation on PVDF composites was also investigated. By combining appropriate CNT/GNP ratio, a good compromise between flexibility, conductivity, processability and EM attenuation with absorption characteristics was achieved, thus favoring promising application in stealth technology and also in communication devices.

An advanced cement-based geocomposite with autonomous sensing and heating capabilities for enhanced intelligent transportation infrastructure

This study introduces an innovative multifunctional cementitious-based geocomposite with self-sensing and self-heating capability, generated for transportation infrastructural health monitoring and traffic recognition. In this route, hybrid graphene nanoplatelets (GNP) and carbon nanotubes (CNT) were uniformly dispersed within a matrix of stabilized sand containing 10% cement. The mechanical and microstructural performances of the composite were examined using various tests. The self-sensing capabilities of the composite were also investigated. In addition, the effects of temperature, moisture content, and loading shape, speed and magnitudes on the strain and stress sensing capability of the specimens were also investigated. The self-sensing performance of this cementitious geocomposite for the asphalt layer strain detection was assessed in a hybrid section including the asphalt mixture layer and smart geocomposite. Moreover, the research also examined the composite's capacity for self-heating, a highly relevant application within the transportation sector. The 0.98 ˚C/s heating rate, 526 mW/˚C heating power, and 251 ˚C maximum temperature proved the high heating potential of this geocomposite for deicing, self-healing, and temperature sensing applications. The specimens showed a supreme correlation between strain changes and fractional changes in electrical resistance (FCR) values in different loading patterns. Although increasing temperature amplified the piezoresistivity response of the composite, the introduction of humidity had adverse impacts. An appropriate correlation was observed between gauge factor, modulus, and digital image correlation analysis. The piezoresistive response of this geocomposite in the hybrid section including smart geocomposite and asphalt layer, representative of the common structural layers of urban pavements, showed the ability of this geocomposite in terms of strain and stress detection of itself and even in the asphalt layer. This study provides a bright horizon for smart materials development in civil infrastructures, particularly transportation and railways.

A Stable Fe3O4-Based Hybrid Anodes for High Performance Li-Ion Batteries

There is an increasing demand for high-performance Li-ion batteries especially due to environmental concerns. To meet the high-performance requirements of the Li-ion batteries, conversion-type anodes stand out with their capacities. The crystal structure of magnetite (Fe3O4) benefits from its empty interstitial sites which hinders volume changes during the insertion and extraction of lithium ions. Combined with its high theoretical lithium storage capacity and abundance, Fe3O4 has great potential as an alternative anode. Yet in its practical use, the material suffers from severe capacity degradation, mainly due to the formation of a passive metallic iron layer on the electrode [1]. Another suggested mechanism responsible for the deterioration of the performance is the formation of electrochemically inactive FeO-based side products upon delithiation process [2].In this study, we utilize reduced graphene oxide (rGO) as a substrate for the ultrafine Fe3O4 nanoparticles to form a two-dimensional hybrid material with improved characteristics. Under a mild hydrothermal condition, nanoparticles were deposited by a simple redox process in an interconnected porous network of graphene. Graphene aids in improving the Fe3O4 performance not only by reducing the charge transfer resistance, buffering the volume change induced stresses and facilitating the ion transport but also by forming an effective interface with the delocalized electrons of Fe3O4 to further result in the increase of battery capacitance by the interfacial conjugation mechanism, as confirmed by in-situ EIS measurements. The Fe3O4 particles have been effectively stabilized on the rGO surface, becoming less prone to agglomeration during cycling. Consequently, the deliverable specific capacity of the hybrid material was gradually improved upon extended cycling, reaching from 1500 mAh/g up to 2200 mAh/g at 0.5 A/g at the end of 100 cycles of operation. The increase of the specific capacity during the extended cycling was attributed to the chemical and structural changes of the electrode material evaluated by TEM and ex-situ EELS measurements. It was confirmed that the particle size is greatly reduced to 1-2 nm scale, improving the lithium-ion diffusion kinetics by the increased surface area and reversibility of the redox reaction upon graphene contribution. Moreover, the aged cells were observed to still deliver around 1100 mAh/g capacity upon more than 250 times cycling at 1 A/g, indicating the great potential of the ultrafine Fe3O4 decorated reduced graphene hybrids as superior performance Li-ion battery anode materials.

Enhancement of the tribological and thermal properties of UHMWPE based ternary nanocomposites containing graphene and titanium titride

Abstract Ultra-high molecular weight polyethylene (UHMWPE) generally does not have high resistance to wear and are characterised by poor thermal stability when exposed to long working condition. To address these shortcomings, this study used hybrid graphene nanoplatelets (GN) and titanium nitride (TiN) nanoparticles to significantly enhance the wear resistance and thermal stability of UHMWPE. The nanocomposites were prepared by solvent mixing and hot compression process. Scanning electron microscope showed uniform dispersion of the nanoparticles in the UHMWPE matrix. The developed UHMWPE showed improved wear resistance and thermal stability relative to the pure UHMWPE. For instance, the wear rate reduced from 6.7 × 10−3 mm3 N−1 m−1 and 3.67 × 10−2 mm3 N−1 m−1 for pure UHMWPE to 2.687 × 10−5 mm3 N−1 m−1 and 1.34 × 7 × 10−4 mm3 N−1 m−1 for UHMWPE–2 wt% GN–10 wt% TiN at applied loads of 10 N and 20 N respectively. This is about 100 % increment in wear resistance at the respective applied loads compared to the pure UHMWPE. The thermal stability of the fabricated nanocomposites was studied using the thermogravimetric analyser (TGA). The addition of nanoparticles significantly reduced the thermal decomposition of UHMWPE matrix. The enhanced properties of the UHMWPE–GN–TiN nanocomposites may be attributed to the network structures formed from the dispersion of the GN and TiN nanoparticles in the UHMWPE matrix with promoted molecular chains interlocking.

Controllable toughness enhancement in graphene hybrid materials via planar twist-angle of carbon nanotubes

A controllable toughness enhancement in graphene hybrid materials via twist-angle of CNTs was first investigated. The mechanical properties, such as out-of-plane deformation, stress–strain curves, strain energy and interlayer loading transfer of Gr Hybrid model coupled by twist-angle CNTs were investigated by molecular dynamics simulations and nonlinear fracture mechanics theory. We find that these mechanical properties are sensitive to the existence of twist-angle CNTs in the Gr hybrid model. The crosslinking sites can be considered as structural defects. In addition, the CNTs exert a strengthening influence on the out-of-plane deformation, interlayer loading transfer as well as bond strain energies, thereby deflecting the crack paths of Gr Hybrid model under axial tension. Nevertheless, the existence of CNTs also triggers a reduction in the in-plane stress and the associated strain due to sp2 + sp3 hybrid state. We find that this abnormal improvement in toughness derives from the localization of the stress fields arising from their out-of-plane displacements at the interface, resulting in the stress fields being localized only at the crosslinking sites. These interfacial toughening strategies can redistribute crack tip stress in a wider range, avoid stress concentration, and at the same time realize a lot of energy dissipation by promoting crack deflection, thus achieving overall high toughness.

Advanced nanofibrous sorbents for the extraction of pollutants from river water and protein-containing matrices

The extraction efficiencies of thirty types of fibers produced by meltblown, alternating current electrospinning, and meltblown-co-electrospinning technologies were tested as advanced sorbents for on-line solid-phase extraction in a high-performance liquid chromatography system have been tested and compared with a commercial C18 sorbent. The properties of each fiber, which were often depended on the production process, and their applicability were demonstrated with the extraction of the model analytes nitrophenols and chlorophenols from various matrices including river water and to purify complex matrix human serum and bovine serum albumin from macromolecular ballast. Polycaprolactone fibers outperformed other polymers and were selected for subsequent modifications including (i) incorporation of hybrid carbon nanoparticles, i.e., graphene, activated carbon, and carbon black into the polymer prior to fiber fabrication, and (ii) surface modification by dip coating with polyhydroxy modifiers including graphene oxide, tannin, dopamine, hesperidin, and heparin. These novel fibrous sorbents were comparable to commercial C18 sorbent and provided excellent analyte recoveries of 70–112% even from the protein-containing matrices.

Experimental investigation of the mechanical properties of graphene oxide-silica nanoparticles reinforced rigid polyurethane foam

ABSTRACTThis study aims to investigate the influence of rigid polyurethane foam (RPUF) as a filling material on the energy absorption performance of thin-walled tubes through experiments. Hybrid graphene oxide-silica nanoparticles (GO-SiO2) was prepared using the electrostatic adsorption method and its potential application in RPUF enhancement were investigated. The interaction between GO and nano SiO2 inhibits the agglomeration of each other and improved the mechanical properties and energy absorption capacity of RPUF. When the GO-SiO2 hybrid content was 6 wt%, the compressive strength and total energy absorption of the GO-SiO2/RPUF composite material increased by 99.59% and 89.63% compared with those of pure RPUF, respectively. In addition, the deformation characteristics of empty tube and foam-filled tube under lateral compression were compared, and the influence of the RPUF material’s mechanical properties on the energy absorption characteristics of foam-filled tube was further analyzed. Test results show that the foam material can effectively improve the stability of the compression deformation of thin-walled circular tubes and improve the compression resistance of the structure. Improving the mechanical properties of RPUF materials can further increase the bearing capacity and energy absorption of foam-filled tubes. The results in this study validated the feasibility of using GO-SiO2 hybrid as a new nano-reinforcing filler for RPUF, and provide an experimental reference for the engineering application of foam-filled tubes as energy absorption components.