This review explores the potential of photonic nanoparticles for cancer theranostics. Photonic nanoparticles offer unique properties and photonics capabilities that make them promising materials for cancer treatment, particularly in the presence of near-infrared light. However, the size of the particles is crucial to their absorption of near-infrared light and therapeutic potential. The limitations and challenges associated with the clinical use of photonic nanoparticles, such as toxicity, immune system clearance, and targeted delivery to the tumor are also discussed. Researchers are investigating strategies such as surface modification, biodegradable nanoparticles, and targeting strategies to improve biocompatibility and accumulation in the tumor. Ongoing research suggests that photonic nanoparticles have potential for cancer theranostics, further investigation and development are necessary for clinical use.
Tiny particles called 'photonic nanoparticles' can be used to help treat cancer. These particles have special properties that allow them to be used with special light to treat cancer. However, the size of the particles is really important, so scientists are trying to find ways to make sure they are the right size. There are also some challenges with using these particles in people, like making sure they don't harm the body and that they go to the right place. Scientists are working on ways to improve the safety of these particles and make sure they go where they need to.
Metal Nanoparticles , Nanoparticles , Neoplasms , Humans , Precision Medicine , Optics and Photonics , Theranostic Nanomedicine , Neoplasms/diagnosis , Neoplasms/drug therapy
Owing to the numerous advantages of graphene-based polymer nanocomposite, this study is focused on the fabrication of the hybrid of polyvinyl alcohol (PVA), polypyrrole (PPy), and reduced graphene-oxide. The study primarily carried out the experimentation and the mathematical analysis of the electrical conductivity of PVA/PPy/rGO nanocomposite. The preparation method involves solvent/drying blending method. Scanning electron microscopy was used to observe the morphology of the nanocomposite. The electrical conductivity of the fabricated PVA/PPy/rGO nanocomposite was investigated by varying the content of PPy/rGO on PVA. From the result obtained, it was observed that at about 0.4 (wt%) of the filler content, the nanocomposite experienced continuous conduction. In addition, Ondracek, Dalmas s-shape, dose-response, and Gaussian fitting models were engaged for the analysis of the electrical transport property of the nanocomposite. The models were validated by comparing their predictions with the experimental measurements. The results obtained showed consistency with the experimental data. Moreover, this study confirmed that the electrical conductivity of polymer-composite largely depends on the weight fraction of fillers. By considering the flexibility, simplicity, and versatility of the studied models, this study suggests their deployment for the optimal characterization/simulation tools for the prediction of the electrical conductivity of polymer-composites.
Graphite , Nanocomposites , Electric Conductivity , Polymers , Polyvinyl Alcohol , Pyrroles
In this study, the electrical properties of graphene-polypyrrole (graphene-PPy) nanocomposites were thoroughly investigated. A numerical model, based on the Simmons and McCullough equations, in conjunction with the Monte Carlo simulation approach, was developed and used to analyze the effects of the thickness of the PPy, aspect ratio diameter of graphene nanorods, and graphene intrinsic conductivity on the transport of electrons in graphene-PPy-graphene regions. The tunneling resistance is a critical factor determining the transport of electrons in composite devices. The junction capacitance of the composite was predicted. A composite with a large insulation thickness led to a poor electrochemical electrode. The dependence of the electrical conductivity of the composite on the volume fraction of the filler was studied. The results of the developed model are consistent with the percolation theory and measurement results reported in literature. The formulations presented in this study can be used for optimization, prediction, and design of polymer composite electrical properties.
In this study, a hybrid of graphene nanoplatelets with a polypyrrole having 20 wt.% loading of carbon-black (HGPPy.CB20%), has been fabricated. The thermal stability, structural changes, morphology, and the electrical conductivity of the hybrids were investigated using thermogravimetric analyzer, differential scanning calorimeter, X-ray diffraction analyzer, scanning electron microscope, and laboratory electrical conductivity device. The morphology of the hybrid shows well dispersion of graphene nanoplatelets on the surface of the PPy.CB20% and the transformation of the gravel-like PPy.CB20% shape to compact spherical shape. Moreover, the hybrid's electrical conductivity measurements showed percolation threshold at 0.15 wt.% of the graphene nanoplatelets content and the curve is non-linear. The electrical conductivity data were analyzed by comparing different existing models (Weber, Clingerman and Taherian). The results show that Taherian and Clingerman models, which consider the aspect ratio, roundness, wettability, filler electrical conductivity, surface interaction, and volume fractions, closely described the experimental data. From these results, it is evident that Taherian and Clingerman models can be modified for better prediction of the hybrids electrical conductivity measurements. In addition, this study shows that graphene nanoplatelets are essential and have a significant influence on the modification of PPy.CB20% for energy storage applications.
The problem associated with mixtures of fillers and polymers is that they result in mechanical degradation of the material (polymer) as the filler content increases. This problem will increase the weight of the material and manufacturing cost. For this reason, experimentation on the electrical conductivities of the polymer-composites (PCs) is not enough to research their electrical properties; models have to be adopted to solve the encountered challenges. Hitherto, several models by previous researchers have been developed and proposed, with each utilizing different design parameters. It is imperative to carry out analysis on these models so that the suitable one is identified. This paper indeed carried out a comprehensive parametric analysis on the existing electrical conductivity models for polymer composites. The analysis involves identification of the parameters that best predict the electrical conductivity of polymer composites for energy storage, viz: (batteries and capacitor), sensors, electronic device components, fuel cell electrodes, automotive, medical instrumentation, cathode scanners, solar cell, and military surveillance gadgets applications. The analysis showed that the existing models lack sufficient parametric ability to determine accurately the electrical conductivity of polymer-composites.
