Graphene Network Research Articles

Bubbling resilient 3D free-standing nanoporous graphene with an encapsulated multicomponent nano-alloy for enhanced electrocatalysis.

The design and synthesis of highly durable and active electrocatalysts are crucial for improving the hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR) in proton exchange membrane fuel cells (PEMFCs). In this work, we present a novel dealloyed nanoporous PtCuNiCoMn multicomponent alloy with ligaments/pores ranging from 2-3 nm, which is in situ encapsulated in a three-dimensional, free-standing nanoporous nanotubular graphene network featuring a pore/tube diameter of ∼200 to 300 nm. This method allows precise control over the noble metal loading and alloy composition while preventing noble metal loss throughout the preparation process. The innovative bimodal nanoporous graphene/alloy structure, coupled with an open 3D spongy morphology, and optimized surface Pt electronic structure through multicomponent interaction, significantly enhances the activity for the HER/ORR, outperforming commercial Pt/C. Moreover, this design addresses the issues of Pt nanoparticle aggregation and detachment from carbon supports that typically exist in Pt/C-type catalysts, thereby substantially improving the catalytic durability, even under intense gas bubbling conditions.

Quantifying the effect of nanosheet dimensions on the piezoresistive response of printed graphene nanosheet networks.

Printed networks of 2D nanosheets have found a range of applications in areas including electronic devices, energy storage systems and sensors. For example, the ability to print graphene networks onto flexible substrates enables the production of high-performance strain sensors. The network resistivity is known to be sensitive to the nanosheet dimensions which implies the piezoresistance might also be size-dependent. In this study, the effect of nanosheet thickness on the piezoresistive response of nanosheet networks has been investigated. To achieve this, we liquid-exfoliated graphene nanosheets which were then subjected to centrifugation-based size selection followed by spray deposition onto flexible substrates. The resultant devices show increasing resistivity and gauge factor with increasing nanosheet thickness. We analyse the resistivity versus thickness data using a recently reported model and develop a new model to fit the gauge factor versus thickness data. This analysis allowed us to differentiate between the effect of strain on inter-nanosheet junctions and the straining of the individual nanosheets within the network. Surprisingly, our data implies the nanosheets themselves to display a negative piezo response.

Thermal transport in a defective pillared graphene network: insights from equilibrium molecular dynamics simulation.

Graphene-based hybrid nanostructures have great potential to be ideal candidates for developing tailored thermal transport materials. In this study, we perform equilibrium molecular dynamics simulations employing the Green-Kubo method to investigate the influence of topological defects in three-dimensional pillared graphene networks. Similar to single-layer graphene and carbon nanotubes, the thermal conductivity (k) of pillared graphene systems exhibits a strong correlation with the system size (L), following a power-law relation k ∼ Lα, where α ranges from 0.12 to 0.15. Our results indicate that the vacancy defects significantly reduce thermal conductivity in pillared graphene systems compared to Stone-Wales defects. We observe that, beyond defect concentration, the location of the defects also plays a crucial role in determining thermal conductivity. We further analyze the phonon vibrational spectrum and the phonon participation ratio to obtain more insight into the thermal transport in the defective pillared graphene network. In most scenarios, longitudinal and flexural acoustic phonons experience significant localization within the 15-45 THz frequency range in the defective pillared graphene system.

Binder-free ultrathin pellets of nanocomposites based on Fe3O4@nitrogen-doped reduced graphene oxide aerogel for electromagnetic interference shielding

The synergistic effects of a hybrid nanocomposite (Fe3O4@NrGO) and their influence on electromagnetic pollution shielding (EMI SE) were explored. This is a current concern where the impacts need to be fully clarified and assertively addressed. Thus, the main focus of the paper was based on the physical and mechanical properties of porosity, surface area, flexibility and, mainly, electrical conductivity of the graphene aerogels, which do not require the use of a binder and are of great interest for the EMI SE area. The precursors (rGO, NrGO and Fe3O4), as well as the nanocomposite, underwent thorough structural characterisation to understand their nature. Characteristic bands of C-N/C=N bonds and a content of 8.03 at% N were identified, with a high N:O ratio of 1.31, indicating efficient doping of the conductive matrix. The aerogel NrGO phase, with a quality of just 5 layers, and the Fe3O4 phase, with domains around 5 nm, were confirmed, as well as the superposition of the signals in the Fe3O4@NrGO pattern. Electron microscopy images and elemental map also demonstrated the efficient distribution of Fe3O4 in the matrix and its porous appearance. Thus, leveraging the advantages of aerogel, extremely light ultra-thin pellets measuring 0.1 mm and weighing 10 mg were produced. The high nitrogen doping of the graphene network, the presence of magnetic nanoparticles, as well as the high surface area and porosity achieved in the production of the nanocomposite, were responsible for high specific shielding effectiveness of 2730 dB · cm−1 at 10.7 GHz and an average in the X-band of 1590 dB · cm−1. Thus, the improved and synergistic mechanisms highlighted the promising advantages of using these highly porous doped materials, demonstrating that the Fe3O4@NrGO hybrid presents high value for investigations in the application of EMI SE.

Interlayer growth of SiC nanowires in graphene aerogel for thermal conductivity enhancement of epoxy resin and its mechanism

AbstractThe chemical reduction method is a simple and popular way to contrast the graphene network to improve the polymer matrix's thermal conductivity. And hybrid thermal conductive fillers composed of two or more mixed fillers through chemical synthesis usually have better thermal conductivity because of the synergistic effort. In this work, silicon carbide nanowires (SiC NWs) in graphene aerogels are synthesized with the chemical vapor deposition method, acting as bridges for phonon transmission between adjacent graphene sheets. The RGO/SiC NWs aerogel‐endowed EP composites have a high thermal conductivity of 3.79 W/mK at a filler loading of 5.5 wt%, and 4.23 W/mK at a filler loading of 7.5 wt%, which is 1895% and 2126% higher than pure EP resin, respectively. Finite element analysis (FEA) is utilized to analyze the heat conduction mechanism of composites at last.

Core-Sheath Heterogeneous Interlocked Conductive Fiber Enables Smart Textile for Personalized Healthcare and Thermal Management.

Whereas thermal comfort and healthcare management during long-term wear are essentially required for wearable system, simultaneously achieving them remains challenge. Herein, a highly comfortable and breathable smart textile for personal healthcare and thermal management is developed, via assembling stimuli-responsive core-sheath dual network that silver nanowires(AgNWs) core interlocked graphene sheath induced by MXene. Small MXene nanosheets with abundant groups is proposed as a novel "dispersant" to graphene according to "like dissolves like" theory, while simultaneously acting as "cross-linker" between AgNWs and graphene networks by filling the voids between them. The core-sheath heterogeneous interlocked conductive fiber induced by MXene "cross-linking" exhibits a reliable response to various mechanical/electrical/light stimuli, even under large mechanical deformations(100%). The core-sheath conductive fiber-enabled smart textile can adapt to movements of human body seamlessly, and convert these mechanical deformations into character signals for accurate healthcare monitoring with rapid response(440ms). Moreover, smart textile with excellent Joule heating and photothermal effect exhibits instant thermal energy harvesting/storage during the stimuli-response process, which can be developed as self-powered thermal management and dynamic camouflage when integrated with phase change and thermochromic layer. The smart fibers/textiles with core-sheath heterogeneous interlocked structures hold great promise in personalized healthcare and thermal management.

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.

Mechanical Properties of Conducting Printed Nanosheet Network Thin Films Under Uniaxial Compression.

Thin film networks of solution processed nanosheets show remarkable promise for use in a broad range of applications including strain sensors, energy storage, printed devices, textile electronics, and more. While it is known that their electronic properties rely heavily on their morphology, little is known of their mechanical nature, a glaring omission given the effect mechanical deformation has on the morphology of porous systems and the promise of mechanical post processing for tailored properties. Here, this work employs a recent advance in thin film mechanical testing called the Layer Compression Test to perform the first in situ analysis of printed nanosheet network compression. Due to the well-defined deformation geometry of this unique test, this work is able to explore the out-of-plane elastic, plastic, and creep deformation in these systems, extracting properties of elastic modulus, plastic yield, viscoelasticity, tensile failure and sheet bending vs. slippage under both out of plane uniaxial compression and tension. This work characterizes these for a range of networks of differing porosities and sheet sizes, for low and high compression, as well as the effect of chemical cross linking. This work explores graphene and MoS2 networks, from which the results can be extended to printed nanosheet networks as a whole.

Photoconversion and photoelectron storage coatings based on PANI, BiVO4 and graphene

Based on one of the most abundant resources on earth—sunlight, photocathodic protection (PCP) coating is a photoelectron-saving and intelligent anti-corrosion measure. Herein, we created a photoconversion and photoelectron storage coating composed of epoxy resin matrix, graphene, and sunlight-responsive polyaniline@bismuth vanadate nanocomposites (PANI@BiVO4). The PANI@BiVO4 nanocomposites were evenly distributed into the 3D network formed by graphene flakes. Such a unique design allows for storing the generated electrons, from the photoelectric conversion of BiVO4 upon light exposure, in the layer of PANI via electrochemical reactions. The stored electrons can be released along the 3D conductive graphene network to the metal interface even in dark conditions for more than 12 h.

Emergent high conductivity in size-selected graphene networks

Nanomaterial networks are attractive for a diverse range of printed device applications including electronics, sensing, energy capture and storage. At present, the influence of morphology on the network properties, such as electrical transport, is poorly understood. Here, we develop an understanding of structure-property relationships in these systems by performing size selection from bulk to few-layer graphene. We observe size-dependent electrical conductivity spontaneously during film formation, with the smallest nanosheets realizing electrical conductivity exceeding 105 S/m, a record value for liquid-exfoliated graphene and competitive with electrochemically-exfoliated graphene. Given the high electrical conductivity exhibited by these networks, and the applicability of graphene as a model layered nanosheet system, we explore the use of this size-selected graphene for thermoelectric applications. We interpret our understanding of the high conductivities obtained in terms of nanosheet packing and its influence on the number density and nature of inter-sheet junctions. This work represents an approach to overcome junction-limited electronic transport and enable nanoparticulate networks for printed device applications.

Anchoring Ultrasmall Pt Nanocrystals onto Carbon Nanohorn-Decorated 3D Graphene Networks to Boost Methanol Oxidation Reaction

The successful commercialization of the direct methanol fuel cell (DMFC) is inseparable from the development of advanced Pt-based anode catalysts with high electrocatalytic activity and acceptable manufacturing cost. Here, we present a robust bottom-up strategy to anchor ultrasmall Pt nanocrystals with an average diameter of only 2.3 nm onto carbon nanohorn-decorated three-dimensional (3D) graphene networks (Pt/CNH-G) through a controllable self-assembly process. The as-derived 3D Pt/CNH-G catalysts manifest a series of distinctive architectural advantages, such as interconnected porous frameworks, large accessible surface areas, plentiful active cones, highly dispersed Pt nanoparticles, and good electron conductivity. Consequently, the optimized Pt/CNH-G catalyst is endowed with exceptional methanol oxidation properties with a large electrochemical active surface area of 128.6 m2 g-1, a high mass activity of 1626.0 mA mg-1, and excellent long-term stability, which are significantly superior to those of conventional Pt catalysts supported by carbon black, carbon nanotube, carbon nanohorn, and graphene matrices.

Intelligent laser-induced graphene sensor for multiplex probing catechol isomers

Herein, we unveil the intelligent detection of multiple catechol isomers in complex environments utilizing both laser-induced graphene (LIG) and artificial neural network (ANN). The large scale-up manufacturing of LIG-based sensors (LIGS) with three-electrode configuration on polyimide (PI) is achieved by direct laser-writing and screen-printing technologies. Our LIGS shows excellent electrochemical performance toward catechol isomers, i.e., hydroquinone (1,4-dihydroxybenzene, HQ), catechol (1,2-dihydroxybenzene, CT), and resorcinol (1,3-dihydroxybenzene, RC), with a low limit of detection (LOD) (CC, 0.079 µmol/L; HQ, 0.093 µmol/L; RC, 1.18 µmol/L). Moreover, the ANN model is developed for machine-intelligent to predict concentrations of catechol isomers under an interfering environment via a single LIGS. Using six unique parameters extracted from the differential pulse voltammetry (DPV) response, the machine learning-based regression provides a coefficient of correlation with 0.998 and is able to correctly predict the total and individual concentrations in complex river samples. Hence, this work provides a guide for the preparation and application of LIGS via facile and cost-efficient mass production and the development of an intelligent sensing platform based on the ANN model.

NiCo2O4 on monolithic 3DGF/CNT for high performance hybrid zinc batteries

Hybrid Zn-Air and Zn-MX (MX refers to metal species with cation redox properties) batteries that combine the merits of both types are attracting increasing interest. However, the low areal capacity of the Zn-MX segment hinders their applications toward power resilience. Increasing the electrochemically active material loading is critical to achieving sufficient capacity but poses a challenge for conventional electrodes to maintain fast gas diffusion, which is necessary for the Zn-air function. Herein, we report an advanced, monolithic, carbon-based current collector by growing carbon nanotubes (CNT) onto a 3D graphene network (3DGF). The porous and highly conductive current collector readily accommodates more electrochemically active material, NiCo2O4 (NCO), thereby improving the Zn-NCO segment’s capacity without sacrificing the Zn-air segment’s performance. The 3DGF/CNT/NCO electrode was fabricated into a hybrid Zn battery which achieved a superior areal specific capacity of 2.87 mAh cm−2 at 5 mA cm−2, almost threefold of previously reported values, and an impressive rate capability and cycling stability with 98% of original capacity retained after 1000 cycles at 20 mA cm−2 charging/discharging current density. This work showcases 3DGF/CNT as an advanced current collector architecture for new and novel batteries.

The synergy of ferric surface anchoring and interior doping engineering enables anode with boosted potassium ion storage performances

Interfacial engineering, especially atomic substitution at the interface or inside the nanomaterials, is a promising strategy for fabricating high-performance electrode materials. Herein, an interfacial modification strategy was reported to develop cobaltous sulfide (CoS2) nanomaterials with Fe clusters modified on their interface and Fe single atoms partially substituted Co atoms in CoS2 (Fe-CFS), which were further wrapped by graphene networks, forming highly active Fe-CFS@graphene nanomaterials (Fe-CFS@C) with triple reaction interfaces. As the 1st interface, graphene can decrease their electrical resistance. At the 2nd interface, partial substitution of Co atoms in CoS2 by Fe single atoms can reduce its band gap and boost the potassium ion (K+) diffusion rate. At the 3rd interface, anchoring Fe clusters on the surface of CoS2 results in the formation of Schottky junction and promotes the formation of built-in electric fields, which accelerates the K+ insertion/extraction kinetics and depresses the dynamic polarization. Acting as anode for K+ battery, Fe-CFS@C exhibits a high reversible capacity of 755.8 mA h g−1 at 0.05 A g−1. Even at 10 A g−1, it can maintain 178.3 mA h g−1 over 4000 cycles due to the greatly enhanced electrochemical reaction kinetics and effectively improved structural stability.

The effects of formation and functionalization of graphene-based membranes on their gas and water vapor permeation properties

The gas and water vapor permeabilities of graphene-based membranes can be affected by the presence of different functional groups directly bound to the graphene network. In this work, one type of carboxylated graphene oxide (GO-COOH) and two types of graphene oxide synthesized i) under strong oxidative conditions directly from graphite (GO-1) and ii) under mild oxidative conditions from exfoliated graphene (GO-2) were used as precursors of self-standing membranes prepared with thicknesses in the range of 12–55 μm via slow-vacuum filtration preparation method. It was observed that the permeabilities for all tested gases decreased in order GO-2 > GO-1 > GO-COOH and depended on both the arrangement of graphene sheets and their functionalization. The GO-1 membrane with a high content of oxygen-containing groups showed the best performance for water vapor permeability. The GO-2 membrane with a thickness of 43 μm exhibited a disordered GO sheet morphology and, therefore, unique gas-separation performance towards H2/CO2 gas pair, showing high hydrogen permeability while keeping extremely high H2/CO2 ideal selectivity that exceeds the Robeson 2008 upper bound of polymer membranes.

Tailoring the strength and ductility of graphene/metal composites with percolation network

The graphene network architecture is a promising structure for improving both strength and ductility of graphene/metal composites that has attracted widespread attention. A key issue in designing and optimizing networked graphene/metal composites is the development of theoretical model that can quantitatively predict their overall mechanical properties. Herein, we present a novel computational framework to investigate the effect of graphene percolation network on the strength-ductility of graphene/metal composites utilizing the Cauchy’s probabilistic model, the field fluctuation method and the irreversible thermodynamics principle. Simultaneously, the accuracy of multiscale model is demonstrated by the reported experimental data. To detect how the strength and ductility of networked graphene/metal composites are elevated synchronously, the influences of the primary microstructural parameters including percolation threshold, graphene concentration and aspect ratio on the strength-ductility are quantitatively assessed. Overall, the computational framework can provide theoretical guidance for the architecture optimization of networked graphene/metal composites.

Exceptional dynamic compressive properties of bio-inspired three-dimensional interlocking graphene network reinforced copper matrix composites

Insights into the reinforcement spatial architectures and their fundamental effects on the dynamic mechanical behaviors are of great importance for designing shock-resistant metallic structures. In this study, we report copper matrix composites (CMCs) reinforced by three-dimensional interlocking graphene network (3D-IGN) with a unique bio-inspired “brick-bridge-mortar” structure. Our results demonstrate that the 3D-IGN/Cu shows simultaneously enhanced dynamic strength and ductility as compared to the uniformly-distributed RGO/Cu and pure Cu at the specific strain rate from 1000 s−1 to 8000 s−1. The interlocking network structure not only blocks dislocation movement and restricts grain boundary sliding, but also alleviates the heat-induced softening by improving the thermal conductivity in the horizontal direction. The finite element simulation results further confirm the important role of the graphene network on strain delocalization. This work offers a promising bottom-up tactic to fabricate CMCs with network architecture and superior dynamic properties for high-rate applications.

Strategies and Applications of Graphene and Its Derivatives-Based Electrochemical Sensors in Cancer Diagnosis.

Graphene is an emerging nanomaterial increasingly being used in electrochemical biosensing applications owing to its high surface area, excellent conductivity, ease of functionalization, and superior electrocatalytic properties compared to other carbon-based electrodes and nanomaterials, enabling faster electron transfer kinetics and higher sensitivity. Graphene electrochemical biosensors may have the potential to enable the rapid, sensitive, and low-cost detection of cancer biomarkers. This paper reviews early-stage research and proof-of-concept studies on the development of graphene electrochemical biosensors for potential future cancer diagnostic applications. Various graphene synthesis methods are outlined along with common functionalization approaches using polymers, biomolecules, nanomaterials, and synthetic chemistry to facilitate the immobilization of recognition elements and improve performance. Major sensor configurations including graphene field-effect transistors, graphene modified electrodes and nanocomposites, and 3D graphene networks are highlighted along with their principles of operation, advantages, and biosensing capabilities. Strategies for the immobilization of biorecognition elements like antibodies, aptamers, peptides, and DNA/RNA probes onto graphene platforms to impart target specificity are summarized. The use of nanomaterial labels, hybrid nanocomposites with graphene, and chemical modification for signal enhancement are also discussed. Examples are provided to illustrate applications for the sensitive electrochemical detection of a broad range of cancer biomarkers including proteins, circulating tumor cells, DNA mutations, non-coding RNAs like miRNA, metabolites, and glycoproteins. Current challenges and future opportunities are elucidated to guide ongoing efforts towards transitioning graphene biosensors from promising research lab tools into mainstream clinical practice. Continued research addressing issues with reproducibility, stability, selectivity, integration, clinical validation, and regulatory approval could enable wider adoption. Overall, graphene electrochemical biosensors present powerful and versatile platforms for cancer diagnosis at the point of care.

Simulation approach to electron transport phenomenon in graphene

This investigation was originally designed to verify that the tight-binding approach utilizes an amalgamation of estimated wave functions to compute the electrical band structure. Utilizing computational tools has become essential, especially for challenging and dull problems in physics. Computer programs, in general, once utilized in the approved manner, allow physical problems to be solved and explained rapidly and efficiently at the same time. The case then is to comprehend how to swap from the abstract equations to the computer program, i.e., codes. In this research, valid and numerical strategies are utilized to examine the electrical characteristics of 2D crystals through fluctuating geometries and magnetic fields. Certainty in the mathematical model is based upon those assessments of the two procedures utilizing the dispersal relationship and density of states. The numerical strategies become the importance as the examined systems goes into more complex to be investigated precisely. Throughout this study, it is confirmed that the tight-binding model utilizes a superposition of estimated wave functions to estimate the electrical band structure. This model was showed to a four-sided network and a hexagonal network to confirm the characteristics of electrons as they move over the graphene network. Particularly, this setup provides a way of investigating energy-reliant transport in graphene. The outcomes of this investigation are significant since the energy dependance of transport in mesoscopic graphene is the core of numerous odd transportation occurrences. Also, the conductance for the four-sided framework is considered utilizing the mathematical approaches and shows the accurate appearances for the quantum Hall effect.

Multifunctional nanocomposites reinforced by aligned graphene network via a low-cost lyophilization-free method

Compared with a disordered network, the ordered framework is more beneficial to improving the multifunctional properties (including thermal, electrical, and mechanical properties) of epoxy-based composites. However, current methods for building aligned structures are both energy and time-consuming on account of the tedious and lengthy lyophilization process. Herein, a new strategy is proposed to obtain low-density graphene aerogels (GAs) with long-range oriented structures through a lyophilization-free processes. Due to the minimum thermal boundary resistance, the prepared aligned graphene/epoxy composite exhibits an ultrahigh thermal conductivity of ∼11.6 W/(m·K) at a graphene content of 1.84 vol%, i.e., an enhancement efficiency of 3640% per 1 vol%. In addition, the compressive strength of the composite is increased by 2.6 times compared to epoxy (from 0.29 MPa to 0.76 MPa). Because the composite shows a modulus as low as 0.5–1.0 MPa, it has excellent deformability and compression performance. Moreover, the obtained 3-mm-thick composite achieves an electromagnetic interference shielding effectiveness (EMI SE) of 40 dB due to the interconnected graphene network structure, which meets the requirements of commercial EMI shielding applications. Hence, this strategy can be used to synthesize aligned graphene/epoxy composites with excellent multifunctional performances, which can be simultaneously used as elastic thermal interface materials (TIMs) and EMI shielding materials in the fields of advanced electronic packaging.