• Advances in nano research
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• 제7권2호
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• pp.125-134
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• 2019

The Origanum vulgare L.-mediated synthesis of Ag nanoparticles was successfully realized within the present study. Various concentrations of the $AgNO_3$ used as a silver precursor (1, 2.5, 5, 10 and 100 mM) were used. Very rapid formation of Ag nanoparticles was observed, as only minutes were necessary for the completion of the reaction. With the increasing concentration, red shift of the surface plasmon resonance peak was observed in the Vis spectra. According to photon cross-correlation spectroscopy results, the finest grain size distribution was obtained for the 2.5 mM sample. The transmission electron microscopy analysis of this sample has shown bimodal size distribution with larger crystallites with 100 nm size and smaller around 10 nm. The antibacterial activity was also the best for this sample so the positive correlation between good grain size distribution and antibacterial activity was found. The in-depth discussion of antibacterial activity with related works from the materials science point of view is provided, namely emphasizing the role of effective nanoparticles distribution within the plant extract or matrix. The antibacterial activity seems to be governed by both content of Ag nanoparticles and their effective distribution. This work contributes to still expanding environmentally acceptable field of green synthesis of silver nanoparticles.

• Advances in nano research
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• 제10권2호
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• pp.191-210
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• 2021

To compare the antifungal effect of two nanomaterials (NMs), nanoparticles of zinc oxide were synthesized by a chemical route and zinc oxide-based nanobiohybrids were obtained using green synthesis in an extract of garlic (Allium sativum). The techniques of X-Ray Diffraction (XRD), Infrared (IR) and Ultraviolet Visible (UV-Vis) absorption spectroscopies and Scanning (SEM) and Transmission Electron Microscopies (TEM) were used to determine the characteristics of the nanomaterials synthesized. The results showed that the samples obtained were of nanometric size (< 100 nm). To compare their antifungal capacity, their effect on Cercospora sp. was evaluated. Test results showed that both nanomaterials had an antifungal capacity. The nanobiohybrids (green route) gave an inhibition of fungal growth of ~72.4% while with the ZnO-NPs (chemical route), inhibition was ~87.1%. Microstructural studies using High Resolution Optical Microscopy (HROM) and ultra-structural analysis using TEM carried out on the treated strains demonstrated the effect of the nanofungicides on the vegetative and reproductive structures, as well as on their cell wall. To account for the antifungal effect presented by ZnO-NPs and ZnO nanobiohybrids on the fungi tested, effects reported in the literature related to the action of nanomaterials on biological entities were considered. Specifically, we discuss the electrical interaction of the ZnO-NPs with the cell membrane and the biomolecules (proteins) present in the fungi, taking into account the n-type nature of the ZnO semiconductor and the electrical behavior of the fungal cell membrane and that of the proteins that make up the protein crown.

• Advances in nano research
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• 제13권3호
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• pp.259-267
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• 2022

Two-dimensional (2D) transition metal carbides/nitrides or "MXenes" belong to a diverse-class of layered compounds, which offer composition- and electric-field-tunable electrical and physical properties. Although the majority of the MXenes, including Ti₃C₂T_x, are metallic, they typically show semiconductor-like behaviour in their percolated thin-film structure; this is also the most common structure used for fundamental studies and prototype device development of MXene. Magnetoconductance studies of thin-film MXenes are central to understanding their electronic transport properties and charge carrier dynamics, and also to evaluate their potential for spin-tronics and magnetoelectronics. Since MXenes are produced through solution processing, it is desirable to develop deposition strategies such as inkjet-printing to enable scale-up production with intricate structures/networks. Here, we systematically investigate the extrinsic negative magnetoconductance of inkjetprinted Ti₃C₂T_x MXene thin-films and report a crossover from weak anti-localization (WAL) to weak localization (WL) near 2.5K. The crossover from WAL to WL is consistent with strong, extrinsic, spin-orbit coupling, a key property for active control of spin currents in spin-orbitronic devices. From WAL/WL magnetoconductance analysis, we estimate that the printed MXene thin-film has a spin orbit coupling field of up to 0.84 T at 1.9 K. Our results and analyses offer a deeper understanding into microscopic charge carrier transport in Ti₃C₂T_x, revealing promising properties for printed, flexible, electronic and spinorbitronic device applications.

• Advances in nano research
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• 제12권5호
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• pp.529-547
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• 2022

Graphene is one of the strongest, stiffest, and lightest nanoscale materials known to date, making it a potentially viable and attractive candidate for developing lightweight structural composites to prevent high-velocity ballistic impact, as commonly encountered in defense and space sectors. In-plane twist in bilayer graphene has recently revealed unprecedented electronic properties like superconductivity, which has now started attracting the attention for other multi-physical properties of such twisted structures. For example, the latest studies show that twisting can enhance the strength and stiffness of graphene by many folds, which in turn creates a strong rationale for their prospective exploitation in high-velocity impact. The present article investigates the ballistic performance of twisted bilayer graphene (tBLG) nanostructures. We have employed molecular dynamics (MD) simulations, augmented further by coupling gaussian process-based machine learning, for the nanoscale characterization of various tBLG structures with varying relative rotation angle (RRA). Spherical diamond impactors (with a diameter of 25Å) are enforced with high initial velocity (V_i) in the range of 1 km/s to 6.5 km/s to observe the ballistic performance of tBLG nanostructures. The specific penetration energy (E_p^*) of the impacted nanostructures and residual velocity (V_r) of the impactor are considered as the quantities of interest, wherein the effect of stochastic system parameters is computationally captured based on an efficient Gaussian process regression (GPR) based Monte Carlo simulation approach. A data-driven sensitivity analysis is carried out to quantify the relative importance of different critical system parameters. As an integral part of this study, we have deterministically investigated the resonant behaviour of graphene nanostructures, wherein the high-velocity impact is used as the initial actuation mechanism. The comprehensive dynamic investigation of bilayer graphene under the ballistic impact, as presented in this paper including the effect of twisting and random disorder for their prospective exploitation, would lead to the development of improved impact-resistant lightweight materials.

• Advances in nano research
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• 제12권2호
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• pp.185-195
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• 2022

Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.

• Advances in nano research
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• 제14권4호
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• pp.313-327
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• 2023

Zinc metal organic framework (MOF_Zn)-loaded goad nanoparticles (AuNPs) sol (Au@MOF_Zn), which was characterized by TEM, Mapping, FTIR, XRD, and molecular spectrum, was prepared conveniently by solvothermal method. The results indicated that Au@MOF_Zn had a very strong catalytic effect with the nanoreaction of AuNPs formation between sodium oxalate (SO) and HAuCl4. AuNPs in the new indicator reaction had a strong resonance Rayleigh scattering (RRS) signal at 370 nm. The indicator AuNPs generated by this reaction, which had the most intense surface enhanced Raman scattering (SERS) peak at 1621 cm -1. The new SERS/RRS indicator reaction in combination with specific aptamer (Apt) to fabricate a sensitive and selective Au@MOF_Zn catalytic amplification-aptamer SERS/RRS assay platform for carbendazim (CBZ), with SERS/RRS linear range of 0.025-0.5 ng/mL. The detection limit was 0.02 ng/mL. Similarly, this assay platform has been also utilized to detect oxytetracycline (OTC) and profenofos (PF).

• Advances in nano research
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• 제14권4호
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• pp.375-389
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• 2023

In this study, free vibration analysis of functionally graded (FG) porous truncated conical shell panels reinforced by graphene platelets (GPLs) has been investigated for the first time. Additionally, the effect of three different types of porosity distribution and five different types of GPLs patterns on dynamic response of the shell are also studied. Halpin-Tsai micromechanical model and Voigt's rule are used to determine Young modulus, shear modulus and Poisson's ratio with mass densities of the shell, respectively. The main novelties of present study are: applying 3D elasticity theory and the finite element method in conjunction with Rayleigh-Ritz method to give more accurate results unlike other simplified shell theories, and also presenting a general 3D solution in cylindrical coordinate system that can be used for analyses of different structures such as circular, annular and annular sector plates, cylindrical shells and panels, and conical shells and panels. A convergence study is performed to justify the correctness of the obtained solution and numerical results. The impact of porosity and GPLs patterns, the volume of voids, the weight fraction of graphene nanofillers, semi vertex and span angles of the cone, and various boundary conditions on natural frequencies of the functionally graded panel have been comprehensively studied and discussed. The results show that the most important parameter on dynamic response of FG porous truncated conical panel is the weight fraction of nanofiller and adding 1% weight fraction of nanofiller could increase 57% approximately the amounts of natural frequencies of the shell. Moreover, the porosity distribution has great effect on the value of natural frequency of structure rather than the porosity coefficient.

• Advances in nano research
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• 제13권4호
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• pp.325-339
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• 2022

Endophytes ascertain a symbiotic relationship with plants as promoters of growth, defense mechanism etc. This study is a first report to screen the endophytic population in Waltheria indica, a tropical medicinal plant. 5 bacterial and 3 fungal strains in leaves, 3 bacterial and 1 yeast species in stems were differentiated morphologically and identified by biochemical and molecular methods. The phylogenetic tree of the isolated endophytes was constructed using MEGA X. Silver nanoparticles were biosynthesized from a rare endophytic bacterium Cupriavidus metallidurans isolated from the leaf of W. indica. The formation of silver nanoparticles was confirmed by UV-Visible spectrophotometer that evidenced a strong absorption band at 408.5 nm of UV-Visible range with crystalline nature and average particle size of 16.4 nm by Particle size analyzer. The Fourier Transform Infra-Red spectrum displayed the presence of various functional groups that stabilized the nanoparticles. X-ray diffraction peaks were conferred to face centered cubic structure. Transmission Electron Microscope and Scanning Electron Microscope revealed the spherical-shaped, polycrystalline nature with the presence of elemental silver analyzed by Energy Dispersive of X-Ray spectrum. Selected area electron diffraction also confirmed the orientation of AgNPs at 111, 200, 220, 311 planes similar to X-ray diffraction analysis. The synthesized nanoparticles are evaluated for antimicrobial activity against 7 bacterial and 3 fungal pathogens. A good zone of inhibition was observed against pathogenic bacteria than fungal pathogens. Thus the study could hold a key aspect in drug discovery research and other pharmacological conducts of human clinical conditions.

• Advances in nano research
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• 제15권6호
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• pp.495-511
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• 2023

In this research, the impact of micro-silica, nano-silica, and polypropylene fibers on the fracture energy of self-compacting concrete was thoroughly examined. Enhancing the fracture energy is very important to increase the crack propagation resistance. The study focused on evaluating the self-compacting properties of the concrete through various tests, including J-ring, V-funnel, slump flow, and T50 tests. Additionally, the mechanical properties of the concrete, such as compressive and tensile strengths, modulus of elasticity, and fracture parameters were investigated on hardened specimens after 28 days. The results demonstrated that the incorporation of micro-silica and nano-silica not only decreased the rheological aspects of self-compacting concrete but also significantly enhanced its mechanical properties, particularly the compressive strength. On the other hand, the inclusion of polypropylene fibers had a positive impact on fracture parameters, tensile strength, and flexural strength of the specimens. Utilizing the response surface method, the relationship between micro-silica, nano-silica, and fibers was established. The optimal combination for achieving the highest compressive strength was found to be 5% micro-silica, 0.75% nano-silica, and 0.1% fibers. Furthermore, for obtaining the best mixture with superior tensile strength, flexural strength, modulus of elasticity, and fracture energy, the ideal proportion was determined as 5% micro-silica, 0.75% nano-silica, and 0.15% fibers. Compared to the control mixture, the aforementioned parameters showed significant improvements of 26.3%, 30.3%, 34.3%, and 34.3%, respectively. In order to accurately model the tensile cracking of concrete, the authors used softening curves derived from an inverse algorithm proposed by them. This method allowed for a precise and detailed analysis of the concrete under tensile stress. This study explores the effects of micro-silica, nano-silica, and polypropylene fibers on self-compacting concrete and shows their influences on the fracture energy and various mechanical properties of the concrete. The results offer valuable insights for optimizing the concrete mix to achieve desired strength and performance characteristics.

• Advances in nano research
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• 제16권5호
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• pp.473-487
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• 2024

The current study employs the nonlocal Timoshenko beam (NTB) theory and von-Kármán's geometric nonlinearity to develop a non-classic beam model for evaluating the nonlinear free vibration of bi-directional functionally-graded (BFG) nanobeams. In order to avoid the stretching-bending coupling in the equations of motion, the problem is formulated based on the physical middle surface. The governing equations of motion and the relevant boundary conditions have been determined using Hamilton's principle, followed by discretization using the differential quadrature method (DQM). To determine the frequencies of nonlinear vibrations in the BFG nanobeams, a direct iterative algorithm is used for solving the discretized underlying equations. The model verification is conducted by making a comparison between the obtained results and benchmark results reported in prior studies. In the present work, the effects of amplitude ratio, nanobeam length, material distribution, nonlocality, and boundary conditions are examined on the nonlinear frequency of BFG nanobeams through a parametric study. As a main result, it is observed that the nonlinear vibration frequencies are greater than the linear vibration frequencies for the same amplitude of the nonlinear oscillator. The study finds that the difference between the dimensionless linear frequency and the nonlinear frequency is smaller for CC nanobeams compared to SS nanobeams, particularly within the α range of 0 to 1.5, where the impact of geometric nonlinearity on CC nanobeams can be disregarded. Furthermore, the nonlinear frequency ratio exhibits an increasing trend as the parameter µ is incremented, with a diminishing dependency on nanobeam length (L). Additionally, it is established that as the nanobeam length increases, a critical point is reached at which a sharp rise in the nonlinear frequency ratio occurs, particularly within the nanobeam length range of 10 nm to 30 nm. These findings collectively contribute to a comprehensive understanding of the nonlinear vibration behavior of BFG nanobeams in relation to various parameters.