Defective Graphene Nanoribbons Research Articles

Long-Range Effects in Topologically Defective Arm-Chair Graphene Nanoribbons.

The electronic structure of 7/9-AGNR superlattices with up to eight unit cells has been studied by means of state-of-the-art Density Functional Theory (DFT) and also by two model Hamiltonians, the first one including only local interactions (Hubbard model, Hu) while the second one is extended to allow long-range Coulomb interactions (Pariser, Parr and Pople model, PPP). Both are solved within mean field approximation. At this approximation level, our calculations show that 7/9 interfaces are better described by spin non-polarized solutions than by spin-polarized wavefunctions. Consequently, both Hu and PPP Hamiltonians lead to electronic structures characterized by a gap at the Fermi level that diminishes as the size of the system increases. DFT results show similar trends although a detailed analysis of the density of states around the Fermi level shows quantitative differences with both Hu and PPP models. Before improving model Hamiltonians, we interpret the electronic structure obtained by DFT in terms of bands of topological states: topological states localized at the system edges and extended bulk topological states that interact between them due to the long-range Coulomb terms of Hamiltonian. After careful analysis of the interaction among topological states, we find that the discrepancy between ab initio and model Hamiltonians can be resolved considering a screened long-range interaction that is implemented by adding an exponential cutoff to the interaction term of the PPP model. In this way, an adjusted cutoff distance λ=2 allows a good recovery of DFT results. In view of this, we conclude that the correct description of the density of states around the Fermi level (Dirac point) needs the inclusion of long-range interactions well beyond the Hubbard model but not completely unscreened as is the case for the PPP model.

Tensile failure mechanisms investigation of mesophase pitch-based carbon fibers based on continuous defective graphene nanoribbon model

Mesophase pitch (MPP)-based carbon fibers exhibit outstanding mechanical properties, notably an exceptionally high Young’s modulus. Despite extensive investigations into the microstructure of MPP-based carbon fibers, the influence of these factors on deformation mechanisms under tension remains unclear. This study employs the continuous defective graphene nanoribbons (dGNR) atomistic structure model for molecular dynamics simulations to explore the tensile failure mechanisms of MPP-based carbon fibers. In the simulation model, the structure of the defective region was generated through high-temperature annealing, and a transition region was introduced to prevent distortion and damage to the active graphene edges. The simulation reveals the evolutionary process of the microstructure of MPP-based carbon fibers under tension and achieves Young’s modulus predictions with greater accuracy than theoretical models. Additionally, the study shows that different strengths of interactions between adjacent graphene nanoribbons can lead to two distinct failure modes. Models with larger crystallite dimensions along the fiber axis and lower average defective concentrations exhibit geometric deformation coordination between adjacent nanoribbons, potentially elucidating the increasing strength trend in MPP-based carbon fibers with rising graphitization levels. Our simulations provide insights into the tensile failure mechanisms of MPP-based carbon fibers, offering valuable guidance for regulating their microstructure to enhance mechanical performance.

Optimal design of thermoelectric properties of graphene nanoribbons with 5-7 ring defects based on Bayesian algorithm

Owing to the huge degree of freedom of structure, the optimal design of thermoelectric conversion performance of defective graphene nanoribbons is one of the difficulties in the field of materials research. In this paper, the thermoelectric properties of graphene nanoribbons with 5-7 ring defects are optimized by using non-equilibrium Green's function combined with Bayesian algorithm.The results show that the Bayesian algorithm is effective and advantageous in the search of graphene nanoribbons with 5-7 ring defects with high thermoelectric conversion efficiency. It is found that the single configuration with the best thermoelectric conversion performance can be quickly and accurately searched from 32896 candidate structures by using Bayesian algorithm. Even in the least efficient round of optimization, only 1495 candidate structures (about 4.54% of all candidate structures) need to be calculated to find the best configuration. It is also found that the thermoelectric value <i>ZT</i> (about 1.13) of the optimal configuration of 5-7 ring defective graphene nanoribbons (21.162 and 1.23 nm in length and width, respectively) at room temperature is nearly one order of magnitude higher than that of the perfect graphene nanoribbons (about 0.14). This is mainly due to the fact that the 5-7 ring defects effectively inhibit the electron thermal conductivity of the system, which makes the maximum balance between the weakening effect of the power factor and the inhibiting effect of the thermal conductivity (positive effect). The results of this study provide a new feasible scheme for designing and fabricating the graphene nanoribbon thermoelectric devices with excellent thermoelectric conversion efficiencies.

Adsorption study of pristine and manganese doped graphene nanoribbon for effective methane gas sensing- A DFT study

The adsorption of methane (CH4) gas is explored on the graphene nanoribbon (GNR) and doped GNR surface by first principle investigation. In present work, doping of GNR with Manganese (Mn) has shown very encouraging results. A comparative study of zigzag (ZGNR), armchair (AGNR) and defective (DGNR) graphene nanoribbon is carried out for sensing of CH4. The pristine ZGNR, AGNR and DGNR form show negligible adsorption of CH4. Whereas adsorption efficiency of all systems increases after doping these with Mn. The adsorption energy of ZGNR changed from −0.05 to −2.10 eV and of AGNR changed drastically from −0.13 to −2.94 eV hence changing electrical conductivity. There is nearly no change in energy value of DGNR. The density of state, band gap, binding distance and adsorption energy of GNR and GNR-Mn before and after CH4 adsorption are calculated. The results show that, AGNR-Mn can be an excellent material for CH4 gas sensing.

Molecular Dynamic Simulation of Defective Graphene Nanoribbons for Tension and Vibration.

As deformation and defects are inevitable during the manufacture and service of graphene resonators, comprehensive molecular dynamic (MD) simulations are performed to investigate the vibrational properties of the defective single-layer graphene sheets (SLGSs) during tension. Perfect SLGSs, SLGSs with single vacancy, SLGSs with low-concentration vacancies, and SLGSs with high-concentration vacancies are considered, respectively. The frequencies of the perfect and defective SLGSs at different stretching stages are investigated in detail. The effects of different external forces are also taken into account to study the vibration properties of the defective SLGSs. Results show that the perfect and defective SLGSs both successively perform four stages, i.e., the elastic stage, the yield stage, the hardening stage, and the fracture stage during stretching, and the elastic properties of the SLGSs are insensitive to the vacancy defects, while the ultimate strain is noticeably reduced by the vacancies. The single vacancy has no effect on the vibration properties of SLGS, while the frequency decreases with the increasing vacancy concentration for SLGS at the elastic stage. The frequency of yielded SLGS with a certain vacancy concentration is almost constant even with a varying external force.

On‐surface synthesis of porous graphene nanoribbons containing nonplanar [14]annulene pores

AbstractThe precise introduction of nonplanar pores in the backbone of graphene nanoribbon represents a great challenge. Here, we explore a synthetic strategy toward the preparation of nonplanar porous graphene nanoribbon from a predesigned dibromohexabenzotetracene monomer bearing four cove‐edges. Successive thermal annealing steps of the monomers indicate that the dehalogenative aryl‐aryl homocoupling yields a twisted polymer precursor on a gold surface and the subsequent cyclodehydrogenation leads to a defective porous graphene nanoribbon containing nonplanar [14]annulene pores and five‐membered rings as characterized by scanning tunneling microscopy and noncontact atomic force microscopy. Although the C–C bonds producing [14]annulene pores are not achieved with high yield, our results provide new synthetic perspectives for the on‐surface growth of nonplanar porous graphene nanoribbons.

Novel hydrogen cyanide gas sensor: A simulation study of graphene nanoribbon doped with boron and phosphorus

Hydrogen Cyanide (HCN) gas is a toxic gas generated by burning of material. In the present study, the sensing material for this gas is optimized with simulation software. The adsorption analysis, stability analysis, structural and electronic properties of armchair graphene nanoribbon (ArGNR) and its doped system has been examined for sensing of HCN using Density Functional Theory with Non Equilibrium Green's Function. The BP co-doped ArGNR is explored for the first time for sensing of HCN gas in this work. The ArGNR studied is in the form of Pristine, Defective state, Boron doped, Phosphorus doped and Boron Phosphorus co-doped. The pristine ArGNR is not much sensitive to HCN gas molecule, whereas on introducing dopants, the sensitivity increased considerably. The changes are observed in optimized geometry and electronic properties of different variants. Among all the variants, Phosphorus doped and BP co-doped ArGNR results in strong adsorption and is most sensitive to the Cyanide molecule, showing adsorption energy 15 and 12 times more as compared to pristine ArGNR. It is proposed that Phosphorus doped and BP co-doped ArGNR may be considered for HCN gas sensor applications. • Boron–Phosphorus co-doped graphene nanoribbon as HCN gas sensing reported for the first time. • DFT analysis of pristine, defective and co-doped armchair graphene nanoribbon carried out. • Boron-Phosphorous co-doped armchair graphene nanoribbon emerges as promising material for sensing. • The large band gap variation from 1.91eV to 1.58eV shows sensitivity towards HCN gas. • The co-doped system shows adsorption energy of -1.23eV which is nearly 12 times higher than its pristine structure.

Synergistic effect of Cu decoration and N doping in divacancy defected graphene nanoribbons on hydrogen gas sensing properties: DFT study

Density functional theory (DFT) calculations have been employed to analyze the molecular hydrogen interaction on Cu decorated nitrogen doped divacancy defected graphene nanoribbons (GNRs). In this study, 5-8-5 double vacancy has been specified as a functional defect in order to study their effect on the electronic properties of GNRs. Divacancies are considered to be thermodynamically more favorable than monovacancies because of low formation energy. Moreover, the introduction of nitrogen defects had a massive influence on adsorption properties. The adsorption capability of the complex systems improved as the concentration of nitrogen atoms increased, but when four nitrogen atoms were doped, the efficiency decreased significantly. Aside from adsorption energy, other parameters such as bonding distance, charge transfer; electronic properties were examined and found to be consistent with the previous findings. Our results suggested that simultaneous doping of nitrogen atoms and Cu decorated defected GNR could be a potential material for hydrogen sensing and could be utilized for future applications. Hence, it is worth noting that adding appropriate dopants and defects to the graphene-based gas sensors could greatly improve their sensitivity.

Local current analysis on defective zigzag graphene nanoribbons devices for biosensor material applications.

In this contribution, we aim at investigating the mechanism of biosensing in graphene-based materials from first principles. Inspired by recent experiments, we construct an atomistic model composed of a pyrene molecule serving as a linker fragment, which is used in experiment to attach certain aptamers, and a defective zigzag graphene nanoribbons (ZGNRs). Density functional theory including dispersive interaction is employed to study the energetics of the linker absorption on the defective ZGNRs. Combining non-equilibrium Green's function and the Landauer formalism, the total current-bias voltage dependence through the device is evaluated. Modifying the distance between the linker molecule and the nanojunction plane reveals a quantitative change in the total current-bias voltage dependence, which correlates to the experimental measurements. In order to illuminate the geometric origin of these variation observed in the considered systems, the local currents through the device are investigated using the method originally introduced by Evers and co-workers. In our new implementation, the numerical efficiency is improved by applying sparse matrix storage and spectral filtering techniques, without compromising the resolution of the local currents. Local current density maps qualitatively demonstrate the local variation of the interference between the linker molecule and the nanojunction plane.

Enhanced hydrogen sensing properties in copper decorated nitrogen doped defective graphene nanoribbons: DFT study

Abstract A theoretical analysis was conducted with the aid of density functional theory to examine the interaction of hydrogen molecule with copper decorated nitrogen doped defective graphene nanoribbons. According to the previous studies, vacancy defects in graphene have been shown to be useful not only to improve its reactivity but also to avoid the clustering tendency of transition metals. Thus, in the present study single vacancy defects were created and doped with nitrogen atoms to form a pyridine like structure. We investigated the capability of Cu decorated SV+1N, SV+2N, SV+3N graphene geometry for hydrogen molecule, and developed potential results after optimization. The observed parameters for the study included binding energies, adsorption energies, band gaps, charge transfer, the density of state plots for the optimized geometries. All these parameters change with the concentration of N atoms around the vacancy site. The results show that Cu decorated SV+3 N is the most efficient candidate for hydrogen molecule interaction. Also, there was no dissociation of hydrogen molecule that enabled reversible storage accessible.

Tuning the electronic and magnetic properties of graphene nanoribbons through phosphorus doping and functionalization

Phosphorus-doped carbon materials are a promising candidate for energy storage devices, water splitting, molecular sensing, spin filtering, and optical quantum computers. We investigated the incorporation of phosphorus in pristine and defected graphene nanoribbons (GNRs) using first-principles density functional theory calculations. We analyzed how P-doping and P-functionalities modify the structure and electronic and magnetic properties of GNRs having armchair (AGNRs) and zigzag (ZGNRs) edges. The functional groups were anchored at the edges of the GNRs. The results were analyzed for band structure, the density of states, charge transfer, wave functions, spin density, oxidation energies, and protonation energies. Our findings revealed that the incorporation of phosphorous into the graphitic structures promotes p-type doping. P-doping and P-functionalization in graphene nanoribbons induced a bandgap reduction. Metallic behavior was found for phosphole-like doping (P in a pentagonal ring), P-2vac configuration (P replacing two vacancies), phosphoramide, and phosphorus-dithiolate. The magnetic properties of ZGNRs were strongly influenced by phosphorus doping and functionalization. Usually, the P-doping in ZGNRs promotes a ferromagnetic ground state with aligned spins at the edges and a total magnetization ranging in 3.18–3.90 μB. AGNRs functionalized with phosphate, phosphite, and phosphorodithiolate groups exhibited a ferromagnetic ground state with magnetic moments localized at the functional groups with a total magnetization of 1.03–1.33 μB. The energetic stability of the magnetic properties is discussed. From protonation and oxidation energy calculations, Phosphorus-doping edges (phosphole-like and phosphine-like) are more susceptible to trap H or O atoms. The ribbon width dependence of the total magnetization and protonation energy for phosphate and phosphite functional groups are also discussed. The results obtained from this investigation provide a theoretical basis for better understanding experimental evidence of ferromagnetism in phosphorus-doped graphene and chemical activity of phosphorus-doped graphitic materials. Our investigations propose possible scenarios on the magnetism source in recent experimental findings on ferromagnetism in P-doped graphene and provide a theoretical basis to understand the phosphorus further into graphitic materials.

Rectification, transport properties of doped defective graphene nanoribbon junctions

The transport properties and rectification behavior of junctions which contain armchair graphene nanoribbons (AGNRs) with double vacancy defects or nitrogen-doped in three different sizes of 9, 10 and 12 atoms are studied. The non-equilibrium Green function method and density functional based tight-binding approach are used for different computations. The double vacancy (DV) defects are along the direction of current pathways of graphene devices. We calculated transmission probability, density of states, the current–voltage curves, rectification ratio, and electrodes band structures. We found that I–V graph has nonlinear characteristic and displays rectification behavior. Devices which posses the size of 9 atoms show significant sign of rectification in contrast to other cases (10, 12 atoms). But the current value is more important for the device of 12 atoms size. Moreover, it is shown that extra energy bands are created by the DV defects and nitrogen (N) doped atoms. These bands of DV defects and N-doped cause the Fermi level to shift upwards and can change the behavior (n-type semiconductor, or metal-like) of devices of 9, 10 and 12 AGNRs. Also, various orbital distributions of MPSH (molecularly projected self-consistent Hamiltonian) states in the DV-9AGNR device are investigated.

Highly tunable charge transport in defective graphene nanoribbons under external local forces and constraints: A hybrid computational study

In this paper, we propose a combined modeling of molecular mechanics (MM) and the tight-binding (TB) approach, which enables us to study the effect of factors such as external local forces, constraints, and vacancy defects on electronic transport properties of nanomaterials. Nanostructures selected in this work are armchair graphene nanoribbons (AGNRs). According to this method, the nanostructure is modeled as a frame, and the beam element is applied for illustrating the covalent interatomic interactions in bonds. In our calculations, the terms of torsional, stretching, and bending energies are considered. The selected pristine nanoribbon is a metal, and the purpose of this study is to find the effects of mechanical loading, the vacancy defects and their positions on the electrical conductance of the structure. We observe that the presence of vacancy defects in the structure leads to the opening of an energy gap, which changes the phase of the nanostructure from metal to the semiconductor. We find that with increasing the number of point defects, the energy gap size of the strained system grows. Besides, increasing the magnitude of the local force reduces the conductance, and the energy gap of the system. By changing parameters such as the number of point defects and magnitude local forces, the transport gap of the system can be controlled. The results of this research may be useful in the design of nanoelectromechanical systems.

Electronic Current Mapping of Transport through Defective Zigzag Graphene Nanoribbons

In this contribution, we aim at supporting theoretical transistor material design using a combination of electronic structure theory, transport simulations, and local current analysis. Our effort f...

Atomistic Modelling of Size-Dependent Mechanical Properties and Fracture of Pristine and Defective Cove-Edged Graphene Nanoribbons.

Cove-edged graphene nanoribbons (CGNR) are a class of nanoribbons with asymmetric edges composed of alternating hexagons and have remarkable electronic properties. Although CGNRs have attractive size-dependent electronic properties their mechanical properties have not been well understood. In practical applications, the mechanical properties such as tensile strength, ductility and fracture toughness play an important role, especially during device fabrication and operation. This work aims to fill a gap in the understanding of the mechanical behaviour of CGNRs by studying the edge and size effects on the mechanical response by using molecular dynamic simulations. Pristine graphene structures are rarely found in applications. Therefore, this study also examines the effects of topological defects on the mechanical behaviour of CGNR. Ductility and fracture patterns of CGNR with divacancy and topological defects are studied. The results reveal that the CGNR become stronger and slightly more ductile as the width increases in contrast to normal zigzag GNR. Furthermore, the mechanical response of defective CGNRs show complex dependency on the defect configuration and distribution, while the direction of the fracture propagation has a complex dependency on the defect configuration and position. The results also confirm the possibility of topological design of graphene to tailor properties through the manipulation of defect types, orientation, and density and defect networks.

Thermal conductivity enhancement of defective graphene nanoribbons

We study the heat transfer of graphene nanoribbons (GNRs) with different doped atoms (N, Si) and grain boundaries using non-equilibrium molecular dynamics and thermal relaxation method. It is found that even at low doping concentrations, with the increase of doping concentrations, the thermal conductivities of GNRs decrease greatly, and the thermal resistances of grain boundaries increase drastically. In addition, the mass difference between nitrogen and silicon atoms results in the difference in heat transfer. Further, we investigate the effect of the relative positions of nitrogen atoms and Stone-Wales (SW) defects on the thermal conductivity. We find that the thermal conductivity of GNR with doping atoms close to defects is higher than the thermal conductivity of GNR with doping atoms far away from defects, and when the dopant atoms are located in the heat flow path and close to more defects, it is better for heat transfer. Finally, it is found that the doping atoms can enhance the thermal conductivity when they are close to the heat source and heat sink, maybe this is the fact that doping atoms can inhibit phonon scattering in the heat source and heat sink.

The effects of a Stone–Wales defect on the performance of a graphene-nanoribbon-based Schottky diode

The effects of a Stone–Wales defect on the performance of a graphene-nanoribbon-based Schottky diode are studied herein. To this end, the transmission, energy band structure, density of states, carrier concentration, and current density of the proposed device are modeled analytically in two cases, viz. a pristine and defective graphene nanoribbon, and the results are compared. The results reveal that the introduction of a Stone–Wales defect into the symmetric graphene nanoribbon system obviously changes some of the distinctive properties. After the introduction of a Stone–Wales defect, the slope of the energy levels in the graphene nanoribbon is reduced, leading to a decrease in the Fermi velocity. In this case, the band gap near the Dirac points in the energy band structure is increased. The minimum density of states of the defect-free graphene is almost zero, which can be explained by the shape of the energy band diagram at the Dirac point. Moreover, the minimum density of states in the presence of a Stone–Wales defect is higher than in the defect-free condition, owing to the presence of bands throughout the energy diagram. Finally, the effects of the temperature and channel width on the I–V characteristic of the proposed Schottky diode based on a defect-free or defective graphene nanoribbon are studied analytically, and the efficiency of the device is investigated.

The influence of vacancy-induced local strain on the transport properties in armchair and zigzag graphene nanoribbons

We investigate the transport properties of defected graphene nanoribbons with single C vacancy using non-equilibrium Green’s function formalism within the tight-binding model approach. The insights derived from the analysis of geometric and electronic structure allow us to infer the localized nature of the defect-induced structure relaxation and transport properties. We show that the single vacancy position and concentration in graphene nanoribbons can alter the transmission spectrum and current-voltage characteristics. We consider the dependence of the transport properties on the local strain caused by the C vacancy positions and concentration. We conclude that such defect profoundly modifies the mechanical and electronic properties of the graphene nanoribbons, and introduce new transport properties by allowing the atomic rearrangement.

Comparison of fracture behavior of defective armchair and zigzag graphene nanoribbons

Molecular dynamics simulations of armchair graphene nanoribbons and zigzag graphene nanoribbons with different sizes were performed at room temperature. Double vacancy defects were introduced in each graphene nanoribbon at its center or at its edge. The effect of defect on the mechanical behavior was studied by comparing the stress–strain response and the fracture toughness of each pair of pristine and defective graphene nanoribbon. Results show that the effect of vacancies in zigzag graphene nanoribbon is more profound than in armchair graphene nanoribbon. Also, the effect of double vacancy defect on the ultimate failure stress is greater in zigzag graphene nanoribbons than in armchair graphene nanoribbon due to bond orientation with respect to loading direction. Strength reduction can be as high as 17.5% in armchair graphene nanoribbon with no significant difference between single and double vacancies, while for zigzag graphene nanoribbon, the strength reduction is up to 30% for single vacancy and 43% for double vacancy defects. It is observed that for zigzag graphene nanoribbon with double vacancy at the edge, the direction of the failure plane is oriented at ±30° with respect to the loading direction while it is always perpendicular to the direction of loading in armchair graphene nanoribbon. Results have been verified through studying the fracture toughness parameters in each case as well.

Adsorption Site of Gas Molecules on Defective Armchair Graphene Nanoribbon Formed Through Ion Bombardment

High sensitivity and selectivity is desired in sensing devices. The aim of this study is to investigate the use of the ion bombardment process in creating a defect on graphene nanoribbons (GNR), which significantly affects sensing properties, in particular adsorption energy, charge transfer and sensitivity. A process has been developed to form the defect on the GNR surface using molecular dynamic (MD) with a reactive force field with nitrogen ion. The sensing properties were calculated using the extended Huckel theory when oxygen (O2) and ammonia (NH3) molecules are exposed to different areas on the defective site. Through simulation, it was found that the ion bombardment process formed various types of defects on the GNR surface. Most notably, molecules adsorbed on the ripple area considerably improve the sensitivity by more than 50%. This indicates that the defect on the armchair graphene nanoribbon (AGNR) surface can be a method to enhance graphene-based sensing performance.