A review on the mechanical and thermal properties of graphene and graphene-based polymer nanocomposites: understanding of modelling and MD simulation

Atomistic Modeling of Cross-Linking in Epoxy-Amine Resins: An Open-Source Protocol

Atomistic modeling has become an extensively used method for studying thermosetting polymers, particularly in the analysis and development of high-performance composite materials. Despite extensive research on the topic, a widely accepted, standardized, flexible, and open-source approach for simulating the cross-linking process from precursor molecules has yet to be established. This study proposes, tests, and validates a Molecular Dynamics (MD) protocol to simulate the cross-linking process of epoxy resins. We developed an in-house code based on Python and LAMMPS, enabling the generation of epoxy resin structures with high degrees of cross-linking. In our work, the epoxy network is dynamically formed within the MD simulations, modeling the chemical bonding process with constraints based on the distance between the reactive sites. To validate our model against experimental data from the literature, we then computed the density, thermal conductivity, and elastic response. The results show that the produced structures align well with experimental evidence, validating our method and confirming its feasibility for further analyses and in silico experiments. Beyond the case study presented in this work, focusing on bisphenol A diglycidyl ether (DGEBA) epoxy resin and diethylenetriamine (DETA) as curing agents in a 5:2 ratio, our approach can be easily adapted to investigate different epoxy resins.

Recent advancements in mechanical properties of graphene-enhanced polymer nanocomposites: Progress, challenges, and pathways forward

The versatile properties of graphene-based polymers have captured substantial interest in recent years, making them a topic of significant research focus. This review paper aims to provide an in-depth analysis of the reported mechanical properties of graphene polymer nanocomposites, a highly promising class of materials for diverse industrial applications. Within this review, we emphasize the role of interactions between graphene and the polymer matrix in achieving uniform dispersion to prevent agglomeration and mitigate adverse effects on mechanical properties. Furthermore, we focus on functionalization as the main method of enhancing graphene physicochemical properties, highlighting its capacity to enhance homogeneous dispersion and significantly improve mechanical properties. These enhancements are contingent on factors such as the type and quantity of functionalization agents and the chosen technique. Additionally, we comprehensively examine recent experimental and theoretical research pertaining to the mechanical properties of graphene/polymer nanocomposites. Our analysis contains two primary polymer categories, namely thermoset and thermoplastic matrices, while also considering graphene loading type and volume fraction, as well as the influence of functionalization agents. This review uniquely addresses the existing gap in a comparative analysis between thermoset and thermoplastic matrices, offering insights into how different loading and functionalization methods influence mechanical properties. Moreover, we emphasize the need for further research in optimizing functionalization techniques and understanding the long-term stability of these composites, an area underexplored in current literature. This work stands out by highlighting future directions for refining synthesis techniques and expanding applications of graphene/polymer nanocomposites across industries such as aerospace, automotive, and electronics. Future endeavors may focus on addressing the challenges, refining synthesis techniques, and exploring novel applications, thereby contributing to the continued growth and evolution of graphene/polymer nanocomposites in the field of materials science.

Study on Crack Resistance Mechanism of Helical Carbon Nanotubes in Nanocomposites

Helical carbon nanotubes (HCNTs) with different geometrical properties were constructed and incorporated into nanocomposites for the investigation of the anti-crack mechanism. The interfacial mechanical properties of the nanocomposites reinforced with straight carbon nanotubes and various types of HCNTs were investigated through the pullout of HCNTs in the crack propagation using molecular dynamics (MD). The results show that the pullout force of HCNTs is much higher than that of CNTs because the physical interlock between HCNTs and matrices is much stronger than the van der Waals (vdW) interactions between CNTs and matrices. Remarkably, HCNTs with a large pitch length can not only effectively prevent the initiation of breakages but also hinder the growth of cracks, while HCNTs with a small diameter and tube radius cannot even effectively prevent the initiation of cracks, which is similar to straight CNTs. Moreover, the shear resistance of HCNTs increases with the increase in the helix angle, which remains at a high level when the helix angle reaches the critical value. However, HCNTs with a small helix angle and large diameter can carry out more polymer chains, while snake-like HCNTs and HCNTs with a small diameter and helix angle can hardly carry out any polymer chain during the pullout process and show similar interfacial properties to the straight CNTs.

Carbon-based Flame Retardants for Polymers: A Bottom-up Review

This state-of-the-art review is geared toward elucidating the molecular understanding of the carbon-based flame-retardant mechanisms for polymers via holistic characterization combining detailed analytical assessments and computational material science. The use of carbon-based flame retardants, which include graphite, graphene, carbon nanotubes (CNTs), carbon dots (CDs), and fullerenes, in their pure and functionalized forms are initially reviewed to evaluate their flame retardancy performance and to determine their elevation of the flammability resistance on various types of polymers. The early transition metal carbides such as MXenes, regarded as next-generation carbon-based flame retardants, are discussed with respect to their superior flame retardancy and multifunctional applications. At the core of this review is the utilization of cutting-edge molecular dynamics (MD) simulations which sets a precedence of an alternative bottom-up approach to fill the knowledge gap through insights into the thermal resisting process of the carbon-based flame retardants, such as the formation of carbonaceous char and intermediate chemical reactions offered by the unique carbon bonding arrangements and microscopic in-situ architectures. Combining MD simulations with detailed experimental assessments and characterization, a more targeted development as well as a systematic material synthesis framework can be realized for the future development of advanced flame-retardant polymers.

Design of Novel Membranes for the Efficient Separation of Bee Alarm Pheromones in Portable Membrane Inlet Mass Spectrometric Systems

Bee alarm pheromones are essential molecules that are present in beehives when some threats occur in the bee population. In this work, we have applied multilevel modeling techniques to understand molecular interactions between representative bee alarm pheromones and polymers such as polymethyl siloxane (PDMS), polyethylene glycol (PEG), and their blend. This study aimed to check how these interactions can be manipulated to enable efficient separation of bee alarm pheromones in portable membrane inlet mass spectrometric (MIMS) systems using new membranes. The study involved the application of powerful computational atomistic methods based on a combination of modern semiempirical (GFN2-xTB), first principles (DFT), and force-field calculations. As a fundamental work material for the separation of molecules, we considered the PDMS polymer, a well-known sorbent material known to be applicable for light polar molecules. To improve its applicability as a sorbent material for heavier polar molecules, we considered two main factors-temperature and the addition of PEG polymer. Additional insights into molecular interactions were obtained by studying intrinsic reactive properties and noncovalent interactions between bee alarm pheromones and PDMS and PEG polymer chains.

Development of Graphene-Based Materials with the Targeted Action for Cancer Theranostics

The review summarises the prospects in the application of graphene and graphene-based nanomaterials (GBNs) in nanomedicine, including drug delivery, photothermal and photodynamic therapy, and theranostics in cancer treatment. The application of GBNs in various areas of science and medicine is due to the unique properties of graphene allowing the development of novel ground-breaking biomedical applications. The review describes current approaches to the production of new targeting graphene-based biomedical agents for the chemotherapy, photothermal therapy, and photodynamic therapy of tumors. Analysis of publications and FDA databases showed that despite numerous clinical studies of graphene-based materials conducted worldwide, there is a lack of information on the clinical trials on the use of graphene-based conjugates for the targeted drug delivery and diagnostics. The review will be helpful for researchers working in development of carbon nanostructures, material science, medicinal chemistry, and nanobiomedicine.

Multiscale Modeling and Characterization of Graphene Epoxy Nanocomposite

This study aims to characterize graphene epoxy nanocomposite properties using multiscale modeling. Molecular dynamics was used to study the nanocomposite at the nanoscale and finite element analysis at the macroscale to complete the multiscale modeling. The coupling of these two scales was carried out using the Irving-Kirkwood averaging method. First, the functionalization of graphene was carried and 6% grafted graphene was selected based on Young's modulus and the tensile strength of the grafted graphene sheet. Functionalized graphene with weight fractions of 1.8, 3.7, and 5.6 wt.% were reinforced with epoxy polymer to form a graphene epoxy nanocomposite. The results showed that the graphene with 3.7 wt.% achieved the highest modulus. Subsequently, a functionalized graphene sheet with an epoxy matrix was developed to obtain the interphase properties using the MD modeling technique. The normal and shear forces at the interphase region of the graphene epoxy nanocomposite were investigated using a traction-separation test to analyze the mechanical properties including Young's modulus and traction forces. The mean stiffness of numerically tested samples with 1.8, 3.7, and 5.6 wt.% graphene and the stiffness obtained from experimental results from the literature were compared. The experimental results are lower than the multiscale model results because the experiments cannot replicate the molecular-scale behavior. However, a similar trend could be observed for the addition of up to 3.7 wt.% graphene. This demonstrated that the graphene with 3.7 wt.% shows improved interphase properties. The macroscale properties of the graphene epoxy nanocomposite models with 1.8 and 3.7 wt.% were comparatively higher.

A comprehensive review of critical analysis of biodegradable waste PCM for thermal energy storage systems using machine learning and deep learning to predict dynamic behavior

This article explores the use of phase change materials (PCMs) derived from waste, in energy storage systems. It emphasizes the potential of these PCMs in addressing concerns related to fossil fuel usage and environmental impact. This article also highlights the aspects of these PCMs including reduced reliance on renewable resources minimized greenhouse gas emissions and waste reduction. The study also discusses approaches such as integrating nanotechnology to enhance thermal conductivity and utilizing machine learning and deep learning techniques for predicting dynamic behavior. The article provides an overall view of research on biodegradable waste-based PCMs and how they can play a promising role in achieving energy-efficient and sustainable thermal storage systems. However, specific conclusions drawn from the presented results are not explicitly outlined, leaving room, for investigation and exploration in this evolving field. Artificial neural network (ANN) predictive models for thermal energy storage devices perform differently. With a 4% adjusted mean absolute error, the Gaussian radial basis function kernel Support Vector Regression (SVR) model captured heat-related charging and discharging issues. The ANN model predicted finned tube heat and heat flux better than the numerical model. SVM models outperformed ANN and ANFIS in some datasets. Material property predictions favored gradient boosting, but Linear Regression and SVR models performed better, emphasizing application- and dataset-specific model selection. These predictive models provide insights into the complex thermal performance of building structures, aiding in the design and operation of energy-efficient systems. Biodegradable waste-based PCMs' sustainability includes carbon footprint, waste reduction, biodegradability, and circular economy alignment. Nanotechnology, machine learning, and deep learning improve thermal conductivity and prediction. Circular economy principles include waste reduction and carbon footprint reduction. Specific results-based conclusions are not stated. Presenting a comprehensive overview of current research highlights biodegradable waste-based PCMs' potential for energy-efficient and sustainable thermal storage systems.

A Molecular Dynamics Simulation Study of In- and Cross-Plane Thermal Conductivity of Bilayer Graphene

Efficient thermal management of modern electronics requires the use of thin films with highly anisotropic thermal conductivity. Such films enable the effective dissipation of excess heat along one direction while simultaneously providing thermal insulation along the perpendicular direction. This study employs non-equilibrium molecular dynamics to investigate the thermal conductivity of bilayer graphene (BLG) sheets, examining both in-plane and cross-plane thermal conductivities. The in-plane thermal conductivity of 10 nm × 10 nm BLG with zigzag and armchair edges at room temperature is found to be around 204 W/m·K and 124 W/m·K, respectively. The in-plane thermal conductivity of BLG increases with sheet length. BLG with zigzag edges consistently exhibits 30-40% higher thermal conductivity than BLG with armchair edges. In addition, increasing temperature from 300 K to 600 K decreases the in-plane thermal conductivity of a 10 nm × 10 nm zigzag BLG by about 34%. Similarly, the application of a 12.5% tensile strain induces a 51% reduction in its thermal conductivity compared to the strain-free values. Armchair configurations exhibit similar responses to variations in temperature and strain, but with less sensitivity. Furthermore, the cross-plane thermal conductivity of BLG at 300 K is estimated to be 0.05 W/m·K, significantly lower than the in-plane results. The cross-plane thermal conductance of BLG decreases with increasing temperatures, specifically, at 600 K, its value is almost 16% of that observed at 300 K.

Morphology and Dynamics in Hydrated Graphene Oxide/Branched Poly(ethyleneimine) Nanocomposites: An In Silico Investigation

Graphene oxide (GO)-branched poly(ethyleneimine) (BPEI) hydrated mixtures were studied by means of fully atomistic molecular dynamics simulations to assess the effects of the size of polymers and the composition on the morphology of the complexes, the energetics of the systems and the dynamics of water and ions within composites. The presence of cationic polymers of both generations hindered the formation of stacked GO conformations, leading to a disordered porous structure. The smaller polymer was found to be more efficient at separating the GO flakes due to its more efficient packing. The variation in the relative content of the polymeric and the GO moieties provided indications for the existence of an optimal composition in which interaction between the two components was more favorable, implying more stable structures. The large number of hydrogen-bonding donors afforded by the branched molecules resulted in a preferential association with water and hindered its access to the surface of the GO flakes, particularly in polymer-rich systems. The mapping of water translational dynamics revealed the existence of populations with distinctly different mobilities, depending upon the state of their association. The average rate of water transport was found to depend sensitively on the mobility of the freely to move molecules, which was varied strongly with composition. The rate of ionic transport was found to be very limited below a threshold in terms of polymer content. Both, water diffusivity and ionic transport were enhanced in the systems with the larger branched polymers, particularly with a lower polymer content, due to the higher availability of free volume for the respective moieties. The detail afforded in the present work provides a new insight for the fabrication of BPEI/GO composites with a controlled microstructure, enhanced stability and adjustable water transport and ionic mobility.

Effective Removal of Metal ion and Organic Compounds by Non-Functionalized rGO

Effective removal of heavy metals from water is critical for environmental safety and public health. This work presents a reduced graphene oxide (rGO) obtained simply by using gallic acid and sodium ascorbate, without any high thermal process or complex functionalization, for effective removal of heavy metals. FTIR and Raman analysis show the effective conversion of graphene oxide (GO) into rGO and a large presence of defects in rGO. Nitrogen adsorption isotherms show a specific surface area of 83.5 m2/g. We also measure the zeta-potential of the material showing a value of -52 mV, which is lower compared to the -32 mV of GO. We use our rGO to test adsorption of several ion metals (Ag (I), Cu (II), Fe (II), Mn (II), and Pb(II)), and two organic contaminants, methylene blue and hydroquinone. In general, our rGO shows strong adsorption capacity of metals and methylene blue, with adsorption capacity of qmax = 243.9 mg/g for Pb(II), which is higher than several previous reports on non-functionalized rGO. Our adsorption capacity is still lower compared to functionalized graphene oxide compounds, such as chitosan, but at the expense of more complex synthesis. To prove the effectiveness of our rGO, we show cleaning of waste water from a paper photography processing operation that contains large residual amounts of hydroquinone, sulfites, and AgBr. We achieve 100% contaminants removal for 20% contaminant concentration and 63% removal for 60% contaminant concentration. Our work shows that our simple synthesis of rGO can be a simple and low-cost route to clean residual waters, especially in disadvantaged communities with low economical resources and limited manufacturing infrastructure.

Molecular Dynamics Simulation of the Interfacial Shear Properties between Thermoplastic Polyurethane and Functionalized Graphene Sheet

In this study, the effect of the type and content of functional groups on the interfacial shear properties of a functionalized graphene sheet (FGS)/thermoplastic polyurethane (TPU) nanocomposite are investigated by molecular dynamics (MD) simulations. The maximum pull-out force and separation energy were used to characterize the interfacial strength of the FGS/TPU nanocomposite in sliding mode. To find out how the type and content of functional groups affect the interfacial shear properties of the TPU/FGS system from an atomic view, the details of interactions between FGS and TPU were characterized. Based on the results, stronger interfacial shear properties of the TPU/FGS system can be achieved by adding the carboxyl group or hydroxyl group on the surface of graphene than that between TPU and FGS modified by the amine group or epoxy group, because of the strong interaction of electrostatic forces and H-bonds. In addition, interfacial shear properties can also be enhanced by increasing the content of functional groups modified on the surface of graphene.

Thermal rectification in ultra-narrow hydrogen functionalized graphene: a non-equilibrium molecular dynamics study

In this study, the non-equilibrium molecular dynamics simulation (NEMD) has been used to evaluate the thermal properties, especially the rectification of ultra-narrow edge-functionalized graphene with hydrogen atoms. The system's small width equals 4.91 Å (equivalent to two hexagonal rings). The dependence of the thermal rectification on the mean temperature, hydrogen concentration, and temperature difference between the two baths was investigated. Results reveal that the thermal rectification increases to 100% at 550 K by increasing the mean temperature. Also, it is disclosed that hydrogen concentration plays a vibrant role in thermal rectification. As a result of maximum phonon scattering at the interface, a thorough rectification is obtained in a half-fully hydrogenated system. As well, the effects of temperature difference of baths ΔT on thermal rectification has been calculated. As a result, the thermal rectification decreases even though the current heat increases with ΔT. Finally, the thermal resistance at the interface using a mismatching factor between the two-phonon density of states (DOS) on both sides of the interface has been explained.

Carbon Nanodots from an In Silico Perspective

Carbon nanodots (CNDs) are the latest and most shining rising stars among photoluminescent (PL) nanomaterials. These carbon-based surface-passivated nanostructures compete with other related PL materials, including traditional semiconductor quantum dots and organic dyes, with a long list of benefits and emerging applications. Advantages of CNDs include tunable inherent optical properties and high photostability, rich possibilities for surface functionalization and doping, dispersibility, low toxicity, and viable synthesis (top-down and bottom-up) from organic materials. CNDs can be applied to biomedicine including imaging and sensing, drug-delivery, photodynamic therapy, photocatalysis but also to energy harvesting in solar cells and as LEDs. More applications are reported continuously, making this already a research field of its own. Understanding of the properties of CNDs requires one to go to the levels of electrons, atoms, molecules, and nanostructures at different scales using modern molecular modeling and to correlate it tightly with experiments. This review highlights different in silico techniques and studies, from quantum chemistry to the mesoscale, with particular reference to carbon nanodots, carbonaceous nanoparticles whose structural and photophysical properties are not fully elucidated. The role of experimental investigation is also presented. Hereby, we hope to encourage the reader to investigate CNDs and to apply virtual chemistry to obtain further insights needed to customize these amazing systems for novel prospective applications.

Molecular Dynamics Modeling of Interfacial Interactions between Flattened Carbon Nanotubes and Amorphous Carbon: Implications for Ultra-Lightweight Composites

Flattened carbon nanotubes (flCNTs) naturally form in many carbon nanotube-based materials and can exhibit mechanical properties similar to round carbon nanotubes but with tighter packing and alignment. To facilitate the design, fabrication, and testing of flCNT-based composites for aerospace structures, computational modeling can be used to efficiently and accurately predict their performance as a function of processing parameters, such as reinforcement/matrix cross-linking. In this study, molecular dynamics modeling is used to predict the load transfer characteristics of the interface region between the flat region of flCNTs (i.e., bi-layer graphene) and amorphous carbon (AC) with various levels and locations of covalent bond cross-linking and AC mass density. The results of this study show that increasing the mass density of AC at the interface improves the load transfer capability of the interface. However, a much larger improvement is observed when cross-linking is added both to the flCNT-AC interface and between the flCNT sheets. With both types of cross-linking, substantial improvements in interfacial shear strength, transverse tension strength, and transverse tension toughness are predicted. The results of this study are important for optimizing the processing of flCNT/AC composites for demanding engineering applications.

Analysis of Three-Phase Structure of Epoxy Resin/CNT/Graphene by Molecular Simulation

In this study, the three-phase structure consisting of epoxy resin, carbon nanotubes (CNTs), and graphene, which is assumed to be the surface of carbon fiber, was simulated using molecular dynamics. Models in which the CNT number and initial position of CNT are varied were prepared in this study. Relaxation calculation for each three-phase model was implemented, and the movement of molecules was investigated. When CNTs are located between the graphene and epoxy at initial, how the epoxy approaches to graphene was discussed. Besides, interaction energies between CNT/graphene, CNT/epoxy, and graphene/epoxy were evaluated after relaxations. The value of the interaction energy between two individual molecules (epoxy resin and graphene, CNTs and graphene, epoxy resin and CNTs) among three-phase structure were obtained, respectively, and those mechanisms were discussed in this study.

Recent Advances and Trends of Nanofilled/Nanostructured Epoxies

This paper aims at reviewing the works published in the last five years (2016–2020) on polymer nanocomposites based on epoxy resins. The different nanofillers successfully added to epoxies to enhance some of their characteristics, in relation to the nature and the feature of each nanofiller, are illustrated. The organic–inorganic hybrid nanostructured epoxies are also introduced and their strong potential in many applications has been highlighted. The different methods and routes employed for the production of nanofilled/nanostructured epoxies are described. A discussion of the main properties and final performance, which comprise durability, of epoxy nanocomposites, depending on chemical nature, shape, and size of nanoparticles and on their distribution, is presented. It is also shown why an efficient uniform dispersion of the nanofillers in the epoxy matrix, along with strong interfacial interactions with the polymeric network, will guarantee the success of the application for which the nanocomposite is proposed. The mechanisms yielding to the improved properties in comparison to the neat polymer are illustrated. The most important applications in which these new materials can better exploit their uniqueness are finally presented, also evidencing the aspects that limit a wider diffusion.