Vol. 2 No. 2 (2024)

  • Open Access

    Article

    Article ID: 1902

    Polymer nanocomposites doped with nanocarbon

    by Gregory S. Bocharov, Alexander V. Eletskii, Sergey D. Fedorovich, Andrey K. Sarychev, Artem O. Vagin, Michail A. Zverev

    Nano Carbons, Vol.2, No.2, 2024;

    Possibilities of usage of polymer materials are expanded considerably as a result of the addition of nanocarbon particles (carbon nanotubes, graphene, graphene oxide, and nanostructured graphite). The article contains the consideration of several examples of producing and practical applications of polymer-based composites doped with nanocarbon particles. Such particles possess high electric and thermal conductivity; therefore, the usage of nanocarbon additives permits one to obtain polymer-based composite materials with enhanced transport characteristics. Polymers doped with carbon nanoparticles exhibit percolation conduction so that the charge transport proceeds by a limited number of percolation paths formed by contacting particles. Imperfection of contacts determines the non-linear character of the conduction of such composites: the resistance decreases with the applied voltage increase. The thermal conductivity of nanocarbon particles exceeds that for polymers by 4–5 orders of magnitude; therefore, even a small additive of nanocarbon (on the level of several percent) permits one to get a polymer material with enhanced thermal conductivity. Nanocarbon-doped composites find application particularly as phase change materials, which are able to accumulate and release considerable thermal energy as a result of the phase transition. One more direction of the usage of nanocarbon-doped composites relates to the development of the optical sensor on the basis of carbon nanoparticles. In this device, amplification of the Raman signal, bringing information on the chemical composition and structural characteristics of an object, is reached as a result of the interaction of electromagnetic radiation with plasmon oscillations of conducting nanoparticles.

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  • Open Access

    Review

    Article ID: 1254

    Recent progress in Nanomaterial based biosensors for the detection of cancer biomarkers in human fluids

    by Razu Shahazi, Amirul Islam Saddam, Md Rakibul Islam, Mohammed Muzibur Rahman, Giti Paimard, Ajoy Kumer, Md. Mahmud Alam, Md. Kawsar Mahamud

    Nano Carbons, Vol.2, No.2, 2024;

    Cancer is a global health challenge, and early detection is crucial for effective treatment to improve patient outcomes. In recent years, nanomaterial-based biosensors have emerged as powerful tools for the detection of cancer biomarkers in human fluids. This article highlights the recent progress in biosensor technology for the detection of cancer biomarkers, focusing on advancements in sensitivity, selectivity, multiplexed detection, liquid biopsies, point-of-care testing, wearable biosensors, and integration with artificial intelligence (AI). Recent advancements have significantly improved the sensitivity and selectivity of biosensors, allowing for the detection of low concentrations of cancer biomarkers in complex biological samples. Novel sensing technologies, such as nanomaterial-based sensors and aptamer-based sensors, have played a crucial role in enhancing biosensor performance. Multiplexed biosensors have the ability to simultaneously detect multiple cancer biomarkers, providing comprehensive diagnostic information. This capability is particularly valuable for accurate cancer diagnosis and prognosis. Liquid biopsies, which involve the detection of cancer biomarkers in circulating tumor cells, cell-free DNA, or exosomes present in body fluids, have gained considerable attention. Biosensors have played a pivotal role in the development of liquid biopsy technologies, offering non-invasive and real-time monitoring of cancer progression, treatment response, and the emergence of drug resistance. The integration of biosensors with AI algorithms has shown great potential. AI can analyze and interpret biosensor data, identifying patterns, correlations, and biomarker signatures that may be difficult to detect with traditional methods.

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