Graphene Nanoplatelets Reinforcement Research Articles

Performance Comparison of Al2O3 Cutting Tool with and without Reinforcement of Graphene Nanoplatelets

Al2O3 is a commonly used cutting tool material for machining cast iron and hard steels. However its low fracture toughness has been its potential drawback to use it for wider applications. In order to improve the fracture toughness, graphene nanoplatelets has been used as the reinforcement. The Al2O3 -TiCN composite have been made by powder metallurgy. The present work compares the performance characteristics of Al2O3 -TiCN with and without graphene nanoplatelets (GNP) in CNC machining. The machining performance of the prepared cutting tools is tested in terms of temperature generated, flank wear, cutting force and surface finish. It is observed that the prepared composite tool with GNP has much improved machining performance over the Al2O3 cutting tool that has no GNP reinforcement. The work has the unique novelty of using GNP as the reinforcement in Al2O3 cutting tool material.

Effect of graphene nano-platelet reinforcement on the mechanical properties of pressureless-sintered boron carbide

Boron carbide (B4C) doped with graphene nano-platelet (GNP) as reinforcement has been prepared by pressureless sintering. Effect of GNP addition on mechanical properties of the composite, such as fracture toughness, hardness, flexural strength was investigated. Phase evolution and microstructure was characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Results demonstrated that addition of GNP improved the fracture toughness (KIC) of B4C with the decrease of hardness, flexural strength. The fracture toughness (KIC) can reach 4.45 MPam1/2 with 1wt% addition of GNP, which was 49.3% higher than that of the composite without graphene platelets. It was found that the toughening mechanism can be contributed to pulling-out of graphene platelets, crack deflection, bridging and branching.

Milling of Graphene Reinforced Ti6Al4V Nanocomposites: An Artificial Intelligence Based Industry 4.0 Approach.

The studies about the effect of the graphene reinforcement ratio and machining parameters to improve the machining performance of Ti6Al4V alloy are still rare and incomplete to meet the Industry 4.0 manufacturing criteria. In this study, a hybrid adaptive neuro-fuzzy inference system (ANFIS) with a multi-objective particle swarm optimization method is developed to obtain the optimal combination of milling parameters and reinforcement ratio that lead to minimize the feed force, depth force, and surface roughness. For achieving this, Ti6Al4V matrix nanocomposites reinforced with 0 wt.%, 0.6 wt.%, and 1.2 wt.% graphene nanoplatelets (GNPs) are produced. Afterward, a full factorial approach was used to design experiments to investigate the effect of cutting speed, feed rate, and graphene nanoplatelets ratio on machining behaviour. After that, artificial intelligence based on ANFIS is used to develop prediction models as the fitness function of the multi-objective particle swarm optimization method. The experimental results showed that the developed models can obtain an accurate estimation of depth force, feed force, and surface roughness with a mean absolute percentage error of 3.87%, 8.56%, and 2.21%, respectively, as compared with experimentally measured outputs. In addition, the developed artificial intelligence models showed 361.24%, 35.05%, and 276.47% less errors for depth force, feed force, and surface roughness, respectively, as compared with the traditional mathematical models. The multi-objective optimization results from the new approach indicated that a cutting speed of 62 m/min, feed rate of 139 mm/min, and GNPs reinforcement ratio of 1.145 wt.% lead to the improved machining characteristics of GNPs reinforced Ti6Al4V matrix nanocomposites. Henceforth, the hybrid method as a novel artificial intelligent method can be used for optimizing the machining processes with complex relationships between the output responses.

Coupled Free Vibration of Spinning Functionally Graded Porous Double-Bladed Disk Systems Reinforced with Graphene Nanoplatelets.

This paper presents, for the first time, the mechanical model and theoretical analysis of free vibration of a spinning functionally graded graphene nanoplatelets reinforced composite (FG-GPLRC) porous double-bladed disk system. The nanocomposite rotor is made of porous metal matrix and graphene nanoplatelet (GPL) reinforcement material with different porosity and nanofillers distributions. The effective material properties of the system are graded in a layer-wise manner along the thickness directions of the blade and disk. Considering the gyroscopic effect, the coupled model of the double-bladed disk system is established based on Euler–Bernoulli beam theory for the blade and Kirchhoff’s plate theory for the disk. The governing equations of motion are derived by employing the Lagrange’s equation and then solved by employing the substructure mode synthesis method and the assumed modes method. A comprehensive parametric analysis is conducted to examine the effects of the distribution pattern, weight fraction, length-to-thickness ratio, and length-to-width ratio of graphene nanoplatelets, porosity distribution pattern, porosity coefficient, spinning speed, blade length, and disk inner radius on the free vibration characteristics of the FG-GPLRC double-bladed disk system.

Structural, mechanical, and dielectric properties of polyvinylchloride/graphene nano platelets composites

Composites of polyvinylchloride (PVC) embedded with different ratios of graphene nano-platelets (GnP) were prepared by the casting method. Some techniques as X-ray diffraction technique (XRD), Fourier transform infrared (FT-IR), optical microscopy, and scanning electron microscopy (SEM) were investigated. The crystalline structure of GnP dominated by increasing its ratio to 2.5 wt.% in the hosting matrix compared to the amorphous structure of the pristine PVC. Microstructural analysis showed uniform distribution of GnP in PVC with some aggregates. Also, the article represents a study of the impact of GnP loading on PVC dielectric parameters such as dielectric loss, electric modulus, ac conductivity, and their dependencies on frequency and temperature. The permittivity ε' displayed an increase in its values with increasing GnP content due to the creation of a strengthened interfacial polarization phenomenon. The values of the activation energy of the polymer were decreased with increasing the content of GnP due to the growing number of conductive networks in the composites. Therefore, GnP enhanced considerably the conductivity of the polymer composites. The mechanical strength of PVC improved with increasing GnP content in which the tensile strength increased up to ∼100%. However, Young’s modulus of PVC enhanced remarkably to be about 109%. In contrast, the elongation at break of PVC decreased by GnP reinforcement from 139.5 to 28.4% by incorporate 0.25% GnP.

On the machining analysis of graphene nanoplatelets reinforced Ti6Al4V matrix nanocomposites

Abstract Negligible work has been reported on exploring the machinability aspects of titanium-based nanocomposites. High-density graphene nanoplatelets (GNPs) reinforced Ti6Al4V matrix nanocomposites are developed by using a high-frequency induction heating technique. The nanocomposites are developed with different percentages of GNPs, including 0 wt.% (base-Ti6Al4V), 0.3 wt.%, 0.6 wt.%, and 1.2 wt.% (GNPs/Ti6Al4V). Afterward, the machining behavior of the Ti6Al4V nanocomposites is investigated in detail during milling in terms of the cutting force components, surface roughness, surface morphology, microhardness and chips morphology. The milling results show that the addition of GNPs reinforcements considerably affects the machining performance of the nanocomposites. Even with high hardness, the 0.3 wt.% and 1.2 wt.% GNPs/Ti6Al4V nanocomposites showed lower cutting forces than the base-Ti6Al4V, i.e., leading to energy conservation. This is mainly due to the profound effect of the GNPs on the hardness, microstructure, and developed phases (TiC and graphene agglomeration) in the nanocomposites. Despite having a higher hardness, all the GNPs/Ti6Al4V nanocomposites revealed improved surface morphology as compared to the base-Ti6Al4V samples. For instance, at a high feed rate of 210 mm/min, the nanocomposites with 0.3 wt.%, 0.6 wt.%, and 1.2 wt.% GNPs contents exhibited approximately 39%, 13%, and 24%, respectively, lower roughness as compared to the base-Ti6Al4V. The 1.2 wt.% GNPs/Ti6Al4V samples show the lowest increase (3.2%) in the surface hardness even after machining at a higher cutting speed of 75 m/min. In comparison, the base-Ti6Al4V samples, which have lower (8.6%) initial hardness, exhibit an increase of 12.7% in surface hardness after machining at the same cutting speed (75 m/min). Overall, the 0.3 wt.% and 1.2 wt.% GNPs nanocomposites are close contestants for yielding the lower cutting forces, improved surface roughness, lower variation in the machined surface hardness, and smoother surface quality with minimum defects in most of the milling conditions, i.e., leading to sustainable machining and clean environment.

Effect of graphene nanoplatelets and montmorillonite nanoclay on mechanical and thermal properties of polymer nanocomposites and carbon fiber reinforced composites

Multifaceted effects of Graphene Nanoplatelets (GNP) and Montmorillonite Nanoclay (MMT) reinforcement on mechanical and thermal properties of DGEBA epoxy resin nanocomposites were investigated. Multi-step dispersion techniques involving ultrasonication, shear mixing and magnetic stirring were used to disperse nanoparticles. Impact on thermal properties was investigated via Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA), while mechanical properties were studied using Tensile and Three-point flexure tests. Graphene sheets were instrumental in increasing modulus and strength at a very low percentage whereas nanoclay was helpful in preserving thermal stability of the matrix thus creating a synergistic effect to reflect the reinforcing ability of both GNP and MMT in mechanical and thermal aspects respectively. X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) studies showed mixed intercalation and exfoliation of nanoparticles with increased inter-planar spacing and decrease in intensity of crystal peaks. SEM micrographs of failed samples revealed failure mechanisms and the aid of GNP to resist failure. To further investigate the effect of binary nano-reinforcement, hybrid Carbon Fiber Reinforced Polymer (CFRP) samples were fabricated and tested for mechanical properties via Tensile and Flexural tests. The mode of failure was analyzed by SEM imaging. It was confirmed that GNP reinforcement helped in increasing the mechanical properties of material.

A comprehensive analysis of auxetic honeycomb sandwich plates with graphene nanoplatelets reinforcement

Nowadays, sandwich plates with cellular core structures are gaining the attention of researchers owing to their outstanding features. For a better insight into auxetic structures, in this study, we propose an excellent computational approach based on polygonal meshes to comprehensively examine the free vibration, buckling and dynamic instability behaviors of the auxetic honeycomb sandwich plate structures. A generalized C0-type higher-order shear deformation theory (C0-HSDT) in conjunction with both Laplace and quadratic serendipity shape functions is employed to approximate the strain fields for polygonal plate elements. The sandwich plate structures are constituted by an auxetic honeycomb core layer with negative Poisson’s ratio and two skin layers reinforced by graphene nanoplatelets (GNPs). Ultra-light features of the plate structures can be obtained by using the auxetic honeycomb cells with negative Poisson’s ratio while the GNPs are embedded into skin layers to enhance the structural stiffness. In order to determine the dynamic instability region of the sandwich plate, Bolotin’s approach is utilized in the current research. Several numerical examples are carried out to investigate the influences of geometrical parameters of auxetic cell and GNPs reinforcement on the structural behaviors. The results obtained in the current research can be considered as benchmark ones to investigate auxetic sandwich plate structures.

Influence of Pin Offset and Weave Pattern on the Performance of Al-Cu Joints Reinforced with Graphene Particles

The friction stir welding technique is currently employed for different alloy combinations like magnesium, titanium, copper, nickel-based composites. Dissimilar materials may be efficiently joined by the process and this has been used in several structural applications such as automotive components, aircraft structure, shipbuilding, and space shuttle external tank and train bodies. Even though improvement in the joint strength was achieved, problems such as voids, tunnels, cracks persisted in the weldments. The objective is to achieve defect-free joints. Tool pin offset for joining of aluminum alloy enables better stirring action and an easy flow of plasticised material in the weld nugget. Hence, to overcome the above-mentioned problem, a technique of combined effect of weaving, tool pin offset, and reinforcement of self-lubricated graphene nanoplatelets was attempted. The tensile strength obtained with the effect of tool rotational speed under weave weld with pin offset condition with reinforcement was 13.82 % higher than the weld obtained under the same condition without reinforcement. IMCs such as AlCu, Al2Cu, and Al4Cu9 large size band layers were observed with the linear welding condition, whereas weave welding conditions resulted in the formation of the thin uniform layer.

Influence of hot extrusion on strain hardening behaviour of graphene platelets dispersed aluminium composites

Experimental work on the determination of strain hardening behaviour of Graphene Nano Platelets (GNPs) dispersed aluminium composites carried out during cold upsetting. The present work aimed to predict the effect of hot extrusion and GNPs content on strain hardening behaviour of aluminium composites. By varying the weight percentage of GNPs reinforcement from 0 to 2 wt %, aluminium composites prepared with powder metallurgy and hot extrusion technique. After each stage of deformation, each non-extruded and extruded GNP dispersed aluminium composites subjected to incremental compressive loading. The stress in axial and hoop direction, hydrostatic stress, instantaneous strain hardening exponent, and strength coefficient calculated for extruded and non-extruded GNPs dispersed aluminium composites. Found that tri-axial stresses, instantaneous strain hardening exponent, and strength coefficient have shown tremendous variation in their values for different weight percentage addition of GNPs and extrusion process. Further identified that extruded aluminium composites consisting of 1.5 wt % GNPs have a significant effect on influencing both strain hardening exponent and strength coefficient.

Spark Plasma Sintering of Graphene-Reinforced Inconel 738LC Alloy: Wear and Corrosion Performance

This study aims to investigate the microstructure, corrosion and tribological properties of spark plasma sintered graphene nanoplatelets (GNPs) reinforced Inconel 738 low carbon composites. The matrix and reinforcement were thoroughly milled in order to ensure homogeneity. Thereafter, the milled powders were consolidated by using spark plasma sintering. The microstructural evolution and the phases formed were examined by the using scanning electron microscopy and X-ray diffractometry techniques. The corrosion analysis was investigated in acidic and basic media, while the tribological test was conducted under dry sliding conditions at varying loads. The results show that the microhardness values were significantly influenced by varying the GNPs constituents in Inconel 738LC from 384 to 459 HV0.5, while the sintered density was influenced by the sintering parameters. The corrosion response of the sintered composites in both acidic and basic media are comparable, irrespective of the varying GNPs content in the matrix. The wear performance suggests that the addition of GNPs to IN738LC, greatly enhanced the wear resistance and reduced the friction coefficient of the sintered IN738LC-GNPs composites. The improvement is attributed to the influence of the graphene-based tribofilm that formed on the sliding contact interface, which reduced friction coefficient. Likewise, graphene has a slight potential of forming continuous tribofilms at the friction interface due to its lubricity. It is thought that the GNPs reinforcement reduced the pull-out tendency, during wear activities.

Effect of graphene nanoplatelet reinforcements on the dynamics of rotating truncated conical shells

In this paper, a parametric study is presented for free vibration analysis of rotating truncated conical shells reinforced with graphene nanoplatelets (GNPs). The composite shell is considered to be composed of epoxy as the matrix and the GNPs which are distributed along the thickness direction based on the various distribution patterns. The shell is modeled based on the first-order shear deformation theory (FSDT), and effective material properties are calculated based on the Halpin–Tsai model and the rule of mixture. Incorporating centrifugal and Coriolis accelerations along with initial hoop tension, the set of the governing equations and boundary conditions are derived using Hamilton’s principle and are solved numerically using generalized differential quadrature method. Convergence and accuracy of the presented solution are confirmed, and influences of various parameters on the forward and backward frequencies are investigated including circumferential mode number, boundary conditions, rotational speed, semi-vertex angle and also mass fraction, distribution pattern, width and thickness of the GNPs. It is noteworthy that for the first time, the initial hoop tension is incorporated for a rotating conical shell modeled based on the FSDT.

The effect of graphene nanoplatelets on technical properties of micro- and nano-sized TiO2 matrix: a comparative research study on electrical and optical characteristics

In this study, titanium dioxide (TiO2)-based graphene nanoplatelets (GNPs)-reinforced composite materials were produced and the electrical and optical properties of the composite materials were investigated. Graphene, which was used as a reinforcing material, was produced by using liquid-phase exfoliation method. While the TiO2 used as matrix material was commercially available for the first group of samples, it was produced by using the sol–gel method for the second group of the samples. Different rates of graphene were added to the TiO2 powders which were commercially available and produced by using sol–gel method. GNPs used as a reinforcing material were subjected to TEM analysis. The resulting composite materials were structurally examined in SEM and XRD. Then, the changes in electrical conductivity of these composites under the impact of temperature were measured. UV–Vis spectrometers of the samples were taken and their optical properties were determined. When temperature-based electrical examination of the produced composite materials was performed, an increase was observed on the electrical conductivity values in both groups of samples as a result of addition of the reinforcing element. In addition, TiO2-containing composites produced by using sol–gel method had lower electrical conductivity comparing with commercially purchased TiO2-containing composites especially at high temperatures. In the optical measurements, it was observed that there was an increase in the optical bandgap energy range values with GNPs reinforcement but a decrease in the reflectance values.

Evaluation of CNT/GNP’s synergic effects on the Mechanical, Microstructural, and durability properties of a cementitious composite by the novel dispersion method

In this paper, the synergic effects of carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) on the mechanics, microstructure, and durability of cementitious composites were investigated. Furthermore, due to the high potential of CNTs and GNPs to agglomerate, a novel technique was proposed by utilizing the combined effect of Pluronic F-127 and Tributyl phosphate (TBP) while optimizing the effective factors such as surfactant concentration, sonication time, and temperature to achieve an affordable and compatible industrial scale-up method for a high-quality dispersion of CNT + GNP (50/50). The UV–Vis spectroscopy, optical microscopy image analysis, zeta potential, and bundle size measurements indicated that a high-quality CNT + GNP dispersion with a low agglomeration area and bundle size (<1.2% and 219 nm) was achieved with 10% Pluronic (wt% of nanoparticles) over 3 h of sonication at 40 °C with the presence of TBP (50 wt% of surfactant). Flexural and compressive tests of the reinforced cementitious composites using different CNT + GNP concentrations showed a significant improvement in mechanical behavior during different periods of hydration. The measured bulk density, none destructive ultrasonic, and capillarity tests also indicated a denser and improved composite microstructure for the CNT + GNP reinforced specimens. The formation of an adsorption layer due to the presence of phosphate and hydroxyl functional groups (proven by FTIR analysis) had positive effects on regulating the microstructures of the hydration crystals. The SEM, TGA, XRD, and EDX analysis results showed that CNTs + GNPs increased the hydration rate. Moreover, CNT + GNP reinforcement led to a significant reduction in carbonation depth. Ultimately, the results obtained demonstrate that an optimum concentration of CNT + GNP is around 0.5%.

Additively Manufactured Polyetheretherketone (PEEK) with Carbon Nanostructure Reinforcement for Biomedical Structural Applications

This study is focused on carbon nanostructures (CNS), including both carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs), reinforcement of medical‐grade polyetheretherketone (PEEK), and in vitro bioactivity for biomedical structural applications. CNS/PEEK scaffolds and bulk specimens, realized via fused filament fabrication (FFF) additive manufacturing, are assessed primarily in the low‐strain linear‐elastic regime. 3D printed PEEK nanocomposites are found to have enhanced mechanical properties in all cases while maintaining the desired degree of crystallinity in the range of 30–33%. A synergetic effect of the CNS and sulfonation toward bioactivity is observed—apatite growth in simulated body fluid increases by 57% and 77%, for CNT and GNP reinforcement, respectively, doubling the effect of sulfonation and exhibiting a fully‐grown mushroom‐like apatite morphology. Further, CNT‐ and GNP‐reinforced sulfonated PEEK recovers much of the mechanical losses in modulus and strength due to sulfonation, in one case (GNP reinforcement) increasing the yield and ultimate strengths beyond the (non‐sulfonated) printed PEEK. Additive manufacturing of PEEK with CNS reinforcement demonstrated here opens up many design opportunities for structural and biomedical applications, including personalized bioactivated surfaces for bone scaffolds, with further potential arising from the electrically conductive nanoengineered PEEK material toward smart and multifunctional structures.

Tensile characterization of graphene nanoplatelets (GNP) mortar using acoustic emissions

This study characterizes tensile behavior of graphene nanoplatelets (GNPs) reinforced cementitious composites using acoustic emissions (AE). Two acoustic sensors were attached to dog-bone specimens that were cast using GNP nano-reinforced mortar composites at concentration levels of 0% to 0.5 % by weight of cement. The specimens were tested under direct tensile loading and the average tensile strength was calculated. AE parameters such as average frequency (AF) and rise time over amplitude (RA) were used to analyze the cracking mode. Average RA was studied to investigate the effect of GNPs reinforcement. A correlation between average acoustic energy and the tensile strength was established. In addition, the acoustic emissions data was analyzed for the localization of cracks along the length of the specimens. Results indicated that the addition of GNPs increased the tensile strength of the cementitious composites by 8%–48%. In addition, the AE analysis revealed a delay in crack initiation shear stress transfer on the matrix -GNPs interface for mortar composites with GNPs and was able to localize cracks as they are initiated.

Insulator-conductor transition in carbon nanotube and graphene nanoplatelates reinforced plasma sprayed alumina single splat: Experimental evidence by conductive atomic force microscopy

Splats are the most fundamental and paramount unit of any plasma sprayed coating and splats are having the potential to manipulate the overall property of the same. Current study shows the insulator-conductor transition of alumina (Al2O3) splat by the hybrid addition of carbonaceous nanofillers, namely carbon nanotubes (CNTs) and Graphene nanoplatelets (GNPs) into it. Reinforcement of CNTs and GNPs changed the splat shape from fragmented to nearly disk shaped as well as from porous splat to densified one upon the reinforcement. Further, Current mapping over the splats were carried out using conductive atomic force microscopy (cAFM). Current map for Al2O3 splat showed fully black region, evincing its insulating nature; whereas hybrid addition of CNTs and GNPs into the splat dramatically improved the electrical conductivity of Al2O3 splat, coining its non-conductive map to conductive one. This transition was attributed to electron tunneling mechanism, which is a function of electron hopping distance of these conductive nanofillers. The electron hopping distance of the matrix got minimized when CNTs and GNPs were simultaneously added to Al2O3 splat, due to their higher aspect ratio. This led to the formation of a 3-dimensional conductive channels for the electron transport in the matrix, converting the whole splat as conductive.

Flutter analysis of laminated composite quadrilateral plates reinforced with graphene nanoplatelets using the element-free IMLS-Ritz method

This paper investigates the flutter characteristics of graphene nanoplatelet (GPL) reinforced laminated composite quadrilateral plates using the element-free IMLS-Ritz method. The modified Halpin-Tsai model and rule of mixture are employed to predict the effective material properties including Young's modulus, mass density and Poisson's ratio. The energy functions of GPL reinforced composite (GPLRC) quadrilateral plates are obtained by the first-order shear deformation theory (FSDT) and first order piston theory. Based on the IMLS-Ritz approximation, the discrete dynamic equation of GPLRC quadrilateral plates is derived. The accuracy of the IMLS-Ritz results is examined by comparing the natural frequencies with those obtained from published values. A comprehensive parametric study is carried out, with a particular focus on the effects of weight fraction, distribution pattern, total number of layers, geometry and size of GPL reinforcements and geometric parameters of quadrilateral plates on the flutter boundary of GPLRC quadrilateral plates.

Static and dynamic analyses of FG-GNPs reinforced porous nanocomposite annular micro-plates based on MSGT

The metal foams are widely used in different areas of technologies due to their both, low specific weight and good stiffness. Adding nanofillers as reinforcement to metal foams makes them stiffer while keeping their lightweight. Graphene nanoplatelets (GNPs) are recently known as the best nanofillers due to their exciting features such as high Young's modulus and extremely high thermal conductivity. In the present article, bending, buckling, and free vibration analyses of micro-scaled functionally graded GNPs reinforced porous nanocomposite annular plate located on the bi-parameter elastic foundation exposed to hygro-thermo-mechanical loads are carried out. The GNPs reinforcement and also porous matrix properties are functionally graded along with the plate's thickness based on overall sixteen combination patterns. The Gaussian random field (GRF) scheme for closed-cell cellular solids is considered for the porous matrix properties, and the effective properties of the porous nanocomposite micro plate are determined via Halpin–Tsai and extended rule of mixture (ERM) micromechanics models. The modified strain gradient theory (MSGT) suggesting three material length-scale parameters is employed to cope with the size effect, and the shear deformation effects are taken into account using the first-order shear deformation theory (FSDT). The governing differential equations are derived using energy method and variational approach. The normalized, discretized equations are then solved using the generalized differential quadrature (GDQ) scheme for various boundary conditions. The reliability of the results is ensured by comparing with the previously published ones in the literature for simpler cases. The influence of the prominent parameters on the results is considered.

Analysis and active control of geometrically nonlinear responses of smart FG porous plates with graphene nanoplatelets reinforcement based on Bézier extraction of NURBS

In this paper, we propose an effective computational approach to analyze and active control of geometrically nonlinear responses of functionally graded (FG) porous plates with graphene nanoplatelets (GPLs) reinforcement integrated with piezoelectric layers. The key concept behind this work is to utilize isogeometric analysis (IGA) based on Bézier extraction technique and C0-type higher-order shear deformation theory (C0-HSDT). By applying Bézier extraction, the original Non-Uniform Rational B-Spline (NURBS) control meshes can be transformed into Bézier elements which allow us to inherit the standard numerical procedure like the standard finite element method (FEM). In this scenario, the approximation of mechanical displacement field is calculated via C0-HSDT whilst the electric potential field is considered as a linear function across the thickness of each piezoelectric sublayer. The FG plate includes internal pores and GPLs dispersed into metal matrix either uniformly or non-uniformly along plate’s thickness. To control responses of structures, the top and bottom surfaces of FG plate are firmly bonded with piezoelectric layers which are considered as sensor and actuator layers. The geometrically nonlinear equations are solved by Newton-Raphson iterative procedure and Newmark’s integration. The influence of porosity coefficient, weight fraction of GPLs as well as external electrical voltage on the geometrically nonlinear behaviors of plate structures with various distributions of porosity and GPLs are thoroughly investigated. A constant displacement and velocity feedback control approaches are then adopted to actively control geometrically nonlinear static and dynamic responses, where structural damping effect is taken into account, based on a closed-loop control with sensor and actuator layers.