Graphene-Based Polymer Nanocomposites: Recent Advances

Carbon-Based Nanomaterials Decorated Electrospun Nanofibers in Biosensors: A Review

Nanomaterials have revolutionized scientific research due to their exceptional physical and chemical capabilities. Carbon-based nanomaterials such as graphene and its derivates have excellent electrical, optical, thermal, physical, and chemical properties that have made them indispensable in several industries worldwide, including medicine, electronics, and energy. By incorporating carbon-based nanomaterials as nanofillers in electrospun nanofibers (ESNFs), smoother and highly conductive nanofibers can be achieved that possess a large surface area and porosity. This approach provides a superior alternative to traditional materials in the development of improved biosensors. Carbon-based ESNFs, among the most exciting new-generation materials, have many applications, including filtration, pharmaceuticals, biosensors, and membranes. The electrospinning technique is a highly efficient and cost-effective method for producing desired nanofibers compared to other methods. Various types of natural and synthetic organic polymers have been successfully utilized in solution electrospinning to produce nanofibers directly. To create diagnostics devices, various biomolecules like antibodies, enzymes, aptamers, ligands, and even cells can be bound to the surface of nanofibers. Electrospun nanofibers can serve as an immobilization matrix to create a biofunctional surface. Thus, biosensors with desired features can be produced in this way. This study comprehensively reviews biosensors that integrate nanodiamonds, fullerenes, carbon nanotubes, graphene oxide, and carbon dots into electrospun nanofibers.

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.

Recent Advances in Graphene-Based Nanocomposites for Ammonia Detection

The increasing demand to mitigate the alarming effects of the emission of ammonia (NH3) on human health and the environment has highlighted the growing attention to the design of reliable and effective sensing technologies using novel materials and unique nanocomposites with tunable functionalities. Among the state-of-the-art ammonia detection materials, graphene-based polymeric nanocomposites have gained significant attention. Despite the ever-increasing number of publications on graphene-based polymeric nanocomposites for ammonia detection, various understandings and information regarding the process, mechanisms, and new material components have not been fully explored. Therefore, this review summarises the recent progress of graphene-based polymeric nanocomposites for ammonia detection. A comprehensive discussion is provided on the various gas sensor designs, including chemiresistive, Quartz Crystal Microbalance (QCM), and Field-Effect Transistor (FET), as well as gas sensors utilising the graphene-based polymer nanocomposites, in addition to highlighting the pros and cons of graphene to enhance the performance of gas sensors. Moreover, the various techniques used to fabricate graphene-based nanocomposites and the numerous polymer electrolytes (e.g., conductive polymeric electrolytes), the ion transport models, and the fabrication and detection mechanisms of ammonia are critically addressed. Finally, a brief outlook on the significant progress, future opportunities, and challenges of graphene-based polymer nanocomposites for the application of ammonia detection are presented.

Machine Learning for Property Prediction and Optimization of Polymeric Nanocomposites: A State-of-the-Art

Recently, the field of polymer nanocomposites has been an area of high scientific and industrial attention due to noteworthy improvements attained in these materials, arising from the synergetic combination of properties of a polymeric matrix and an organic or inorganic nanomaterial. The enhanced performance of those materials typically involves superior mechanical strength, toughness and stiffness, electrical and thermal conductivity, better flame retardancy and a higher barrier to moisture and gases. Nanocomposites can also display unique design possibilities, which provide exceptional advantages in developing multifunctional materials with desired properties for specific applications. On the other hand, machine learning (ML) has been recognized as a powerful predictive tool for data-driven multi-physical modelling, leading to unprecedented insights and an exploration of the system’s properties beyond the capability of traditional computational and experimental analyses. This article aims to provide a brief overview of the most important findings related to the application of ML for the rational design of polymeric nanocomposites. Prediction, optimization, feature identification and uncertainty quantification are presented along with different ML algorithms used in the field of polymeric nanocomposites for property prediction, and selected examples are discussed. Finally, conclusions and future perspectives are highlighted.

PMMA-Based Nanocomposites for Odontology Applications: A State-of-the-Art

Polymethyl methacrylate (PMMA), a well-known polymer of the methacrylate family, is extensively used in biomedicine, particularly in odontological applications including artificial teeth, dentures and denture bases, obturators, provisional or permanent crowns, and so forth. The exceptional PMMA properties, including aesthetics, inexpensiveness, simple manipulation, low density, and adjustable mechanical properties, make it a perfect candidate in the field of dentistry. However, it presents some deficiencies, including weakness regarding hydrolytic degradation, poor fracture toughness, and a lack of antibacterial activity. To further enhance its properties and solve these drawbacks, different approaches can be performed, including the incorporation of nanofillers. In this regard, different types of metallic nanoparticles, metal oxide nanofillers, and carbon-based nanomaterials have been recently integrated into PMMA matrices with the aim to reduce water absorption and improve their performance, namely their thermal and flexural properties. In this review, recent studies regarding the development of PMMA-based nanocomposites for odontology applications are summarized and future perspectives are highlighted.

Graphene-Based Polymer Composites for Flexible Electronic Applications

Graphene-based nanomaterials have gained a lot of interest over the last years in flexible electronics due to their exceptional electrical, mechanical, and optoelectronic properties, as well as their potential of surface modification. Their flexibility and processability make them suitable for electronic devices that require bending, folding, and stretching, which cannot be fulfilled by conventional electronics. These nanomaterials can be assembled with various types of organic materials, including polymers, and biomolecules, to generate a variety of nanocomposites with greater stretchability and healability, higher stiffness, electrical conductivity, and exceptional thermal stability for flexible lighting and display technologies. This article summarizes the main characteristics and synthesis methods of graphene, its oxidized form graphene oxide (GO), and reduced GO derivative, as well as their corresponding polymeric composites, and provides a brief overview about some recent examples of these nanocomposites in flexible electronic applications, including electrodes for solar cells and supercapacitors, electronic textiles, and transistors.