Traditional Tuberculosis (TB) treatments and analgesic therapies are often associated with resistance and poor patient compliance, highlighting the need for improved delivery systems. SLNPs, with their lipid matrix encapsulation, offer promising solutions to these challenges, making them valuable tools for enhancing TB treatment and analgesic effects. The primary aim of this review was to assess and investigate the potential of SLNPs. This included evaluating their effectiveness in improving the Bioavailability (BA) and therapeutic results of anti-TB medications, along with their capacity to deliver prolonged analgesic effects. The formulation methods and applications of SLNPs have the potential to transform the treatment of tuberculosis and pain management. This review utilized multiple electronic databases, including PubMed, Scopus, official websites, Google Scholar, Google Patent, and ResearchGate, to gather original review articles. Publications from the last 15 years, from August 31, 2009 to August 31, 2024, were selected for data compilation. The initial two authors conducted the selection, extraction, and review of the articles to compile the complete dataset. Over 70 studies, along with an additional 30, were selected for the review. These findings underscore the ability of SLNPs to overcome the obstacle of conventional drug therapies, supporting their application in TB treatment and pain management. Most studies suggest that SLNPs represent a significant advancement in drug delivery, offering a modern formulation approach that can enhance TB treatment and provide effective analgesic relief. However, the extent of these benefits may be underreported.
Magnetic Nanoparticles (MNPs) have gained significant attention in biomedical applications due to their unique magnetic properties, biocompatibility, and ability to be externally controlled. Their roles in targeted drug delivery, hyperthermia, medical imaging, and biomolecule extraction position them as promising tools for advanced medical and technological applications. This review examines recent advancements in the biomedical applications of MNPs, emphasizing their potential in treating chronic diseases, improving drug delivery systems, and enhancing diagnostic techniques, such as electrochemical and optical-based immunoassays. A comprehensive literature review was conducted using relevant scientific databases to examine recent studies focusing on their structural and functional properties, biomedical applications, and technological innovations in targeted therapy and diagnostics. MNPs have demonstrated remarkable efficiency in controlled drug release, hyperthermia-based cancer treatment, and improved imaging contrast in MRI. Their integration into immunoassays has enhanced the accuracy of biosensing. However, challenges such as stability, toxicity, and scalability remain significant obstacles to clinical translation. Despite these limitations, MNPs hold immense potential to revolutionize biomedical applications. Ongoing research focuses on optimizing their performance, enhancing biocompatibility, and overcoming current barriers. Advancements in surface modification and synthesis techniques are expected to further improve their efficacy, solidifying their role in future diagnostic and therapeutic innovations.
Polymer composites are used extensively in the automotive, aviation, and sports sectors. Recently, researchers have replaced glass fiber with recyclable natural fibers. The present investigation examined the sliding wear performance of glass/sisal fibre (GF/SF)-reinforced hybrid polymer nanocomposite under various axial loads (AL) and sliding velocity (SV), with and without nSiC fillers. A novel GF/SF fiber-reinforced hybrid nanocomposite with and without nano-SiC that complied with ASTM specifications was developed using a vacuum infusion technique. The percentage of nSiC fillers varied among 1 wt.%, 2 wt.%, and 3 wt.%. The pin-on-disc tribometer was employed to assess the tribological performance, viz., coefficient of friction (CoF) and wear rate (WR), of the composites at various process conditions. The hybrid nanocomposite with 2 wt. % nSiC had the lowest CoF and WR of all the constructed composites. At 30N AL and an SV of 0.419 m/s, the GF/SF/2% nano-SiC composite exhibited wear resistance approximately 2.3 times more than that of the GF/SF composite without nanofibers, 1.5 times higher than that of the GF/SF/1% nSiC composite, and 1.46 times higher than that of the GF/SF/3%nSiC composite. The CoF for unreinforced and 2 wt.% nSiC reinforced composites under an AL of 30 N was 0.481 and 0.394, respectively. The better wear properties of the GF/SF/2%nSiC composite were found to be due to uniform dispersion of nanofillers and stronger bonding between the fibres and the matrix. The findings indicated the nSiC filler loadings to significantly improve the GF/SF fibre composite's wear properties.
Polymeric nanocomposites have gained significant attention due to their potential for enhanced properties and applications across diverse industries, including automotive, aerospace, electronics, biomedical, and environmental sectors. This review examines the advancements in polymeric nanocomposites made possible by nanofillers and highlights the transformative role of Artificial Intelligence (AI) in materials science. Using a detailed description of the methodology to select studies for inclusion and exclusion, key nanofillers such as carbon nanotubes, graphene, and metal-organic frameworks were examined for their ability to enhance the mechanical, thermal, electrical, and barrier properties of polymer matrices. Additionally, AI-based optimization approaches for synthesis and property prediction are discussed, along with a focus on green synthesis methods to align with sustainability goals. Nanofillers significantly improve polymer properties, enabling their use in various industries. AI has revolutionized nanocomposite synthesis, facilitating optimized processes and reliable property predictions. Green synthesis methods offer sustainable alternatives; however, challenges persist, including achieving uniform filler dispersion, ensuring biocompatibility for biomedical applications, and reducing the costs associated with large-scale synthesis. This review highlights the potential of polymeric nanocomposites, emphasizing the importance of establishing standard synthesis and characterization procedures to enhance reliability and promote sustainable development in materials science. Further research is essential to address current limitations and fully realize the potential of nanocomposites in advancing industrial applications.
Graphene Nano-Ribbon Tunnel Field-Effect Transistors (GNR TFETs) have emerged as a promising device structure for low-power and high-frequency applications due to their superior electrical properties. Gate engineering in GNR TFETs offers enhanced performance compared to conventional TFETs by optimizing carrier transport characteristics. The proposed model is formulated using Poisson’s Equation in a two-dimensional framework, solved analytically using the Parabolic Approximation method. The device structure incorporates two distinct gate metals (M1 and M2) and a high-k dielectric, Hafnium Di-Oxide (HfO2), to optimize bandgap narrowing. The analytical results are validated through simulations performed using the Technology Computer-Aided Design (TCAD) Silvaco tool, comparing Surface Potential, Electric Field, and Drain characteristics. The Double Material Double Gate (DM DG) GNR TFET optimizes the device performance with the help of material and gate engineering and increases surface potential, electric field, and drain current. Due to the higher ION/IOFF ratio and decreased subthreshold swing, the proposed device is suitable for high-frequency applications and improves the switching performance. The developed model demonstrates a sub-threshold swing of 24.49 mV/dec, an ION/IOFF ratio of 108, and a cut-off frequency of 28 GHz. These results align closely with TCAD simulations, confirming the model’s accuracy. The introduction of double-gate and double-material engineering significantly enhances device performance. The proposed DM DG GNR TFET exhibits superior electrical properties, making it a strong contender for low-power and high-frequency applications. Its improved ION/IOFF ratio and sub-threshold swing highlight its potential in next-generation electronic devices.
