• Advances in nano research
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• v.10 no.1
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• pp.77-90
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• 2021

In the present study, novel chitosan coated magnetic magnetite (Fe3O4) nanoparticles were successfully biosynthesized from mushroom, Agaricus campestris, extract. The obtained bio-nanocomposite material was used to investigate ultra-fast and highly efficient for removal of Ni2+ ions in a fixed-bed column. Chitosan was treated as polyelectrolyte complex with Fe3O4 nanoparticles and a Fungal Bio-Nanocomposite Material (FBNM) was derived. The FBNM was characterized by using X-Ray Diffractometer (XRD), Scanning Electron Microscopy-Energy Dispersive X-Ray Spectroscopy (SEM-EDS), Fourier Transform Infrared spectra (FTIR) and Thermogravimetric Analysis (TGA) techniques and under varied experimental conditions. The influence of some important operating conditions including pH, flow rate and initial Ni2+ concentration on the uptake of Ni2+ solution was also optimized using a synthetic water sample. A Central Composite Design (CCD) combined with Response Surface Modeling (RSM) was carried out to maximize Ni2+ removal using FBNM for adsorption process. A regression model was derived using CCD to predict the responses and analysis of variance (ANOVA) and lack of fit test was used to check model adequacy. It was observed that the quadratic model, which was controlled and proposed, was originated from experimental design data. The FBNM maximum adsorption capacity was determined as 59.8 mg g-1. Finally, developed method was applied to soft drinks to determine Ni2+ levels. Reusability of FBNM was tested, and the adsorption and desorption capacities were not affected after eight cycles. The paper suggests that the FBNM is a promising recyclable nanoadsorbent for the removal of Ni2+ from various soft drinks.

• Advances in nano research
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• v.13 no.2
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• pp.187-197
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• 2022

The synthesis of organic and hybrid organic-inorganic perovskites directly from solution improves the cost- and energy-efficiency of processing. To date, numerous research efforts have been devoted to investigating the influence of the various solvent parameters for the synthesis of lead halide perovskites, focused on the effects of different single solvents on the efficiency of the resulting perovskites. In this work, we investigated the effect of solvent blends for the first time on the structure and phase of perovskites produced via the Lewis base vapor diffusion method to develop a new synthetic approach for water-stable CsPbBr₃ particles with nanometer-sized dimensions. Solvent blends prepared with DMF and water-miscible solvents with different Gutmann's donor numbers (D_N) affect the Pb ions differently, resulting in a variety of lead bromide species with various colors. The use of a DMF/isopropanol solvent mixture was found to induce the formation of the Ruddlesden-Popper perovskite based on lead bromide. This perovskite undergoes a blue color shift in the solvated state owing to the separation of nanoplatelets. In contrast, the replacement of isopropanol with DMSO, which has a high DN, induces the formation of spherical CsPbBr₃ perovskite nanoparticles that exhibit green emission. Finally, the integration of acetone in the solvent system leads to the formation of lead bromide complexes with a yellow-orange color and the perovskite CsPbBr₃.

• Advances in nano research
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• v.12 no.5
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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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• v.12 no.2
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• pp.213-221
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• 2022

Silicon carbide (SiC) is a binary carbon-silicon compound. In its two-dimensional form, monolayer SiC is composed of a monolayer carbon and silicon atoms constructed as a honeycomb lattice. SiC has recently been receiving increasing attention from researchers owing to its intriguing electronic properties. In this present work, SiC nanoribbons (SiCNRs) are modelled and simulated to obtain accurate electronic properties, which can further guide fabrication processes, through bandgap engineering. The primary objective of this work is to obtain the electronic properties of monolayer SiCNRs by applying numerical computation methods using nearest-neighbour tight-binding models. Hamiltonian operator discretization and approximation of plane wave are assumed for the models and simulation by applying the basis function. The computed electronic properties include the band structures and density of states of monolayer SiCNRs of varying width. Furthermore, the properties are compared with those of graphene nanoribbons. The bandgap of ASiCNR as a function of width are also benchmarked with published DFT-GW and DFT-GGA data. Our nearest neighbour tight-binding (NNTB) model predicted data closer to the calculations based on the standard DFT-GGA and underestimated the bandgap values projected from DFT-GW, which takes in account the exchange-correlation energy of many-body effects.

• Advances in nano research
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• v.14 no.1
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• pp.1-15
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• 2023

Driven by the scaling down of transistor node technology, graphene became of interest to many researchers following the success of its fabrication as graphene nanoribbons (GNRs). However, during the fabrication of GNRs, it is not uncommon to have defects within the GNR structures. Scaling down node technology also changes the modelling approach from the classical Boltzmann transport equation to the quantum transport theory because the quantum confinement effects become significant at sub-10 nanometer dimensions. The aim of this study is to examine the effect of Stone-Wales defects on the electronic properties of GNRs using a tight-binding model, based on Non-Equilibrium Green's Function (NEGF) via numeric computation methods using MATLAB. Armchair and zigzag edge defects are also implemented in the GNR structures to mimic the practical fabrication process. Electronic properties of pristine and defected GNRs of various lengths and widths were computed, including their band structure and density of states (DOS). The results show that Stone-Wales defects cause fluctuation in the band structure and increase the bandgap values for both armchair GNRs (AGNRs) and zigzag GNRs (ZGNRs) at every simulated width. In addition, Stone-Wales defects reduce the numerical computation DOS for both AGNRs and ZGNRs. However, when the lengths of the structures increase with fixed widths, the effect of the Stone-Wales defects become less significant.

• Advances in nano research
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• v.15 no.1
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• pp.59-65
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• 2023

In this present article, the mechanical behavior of single-walled black phosphorene nanotubes (SW-αPNTs) is simulated using molecular dynamics (MD). The proposed model is subjected to the axial loading and the effects of morphological parameters, such as the mono-vacancy defect and strain rate on the tensile behavior of the zigzag and armchair SW-αPNTs are studied as a pioneering work. In order to assess the accuracy of the MD simulations, the stress-strain response of the current MD model is successfully verified with the efficient quantum mechanical approach of the density functional theory (DFT). Along with reproducing the DFT results, the accurate MD simulations successfully anticipate a significant variation in the stress-strain curve of the zigzag SW-αPNTs, namely the knick point. Predicting such mechanical behavior of SW-αPNTs may be an important design factor for lithium-ion batteries, supercapacitors, and energy storage devices. The simulations show that the ultimate stress is increased by increasing the diameter of the pristine SW-αPNTs. The trend is identical for the ultimate strain and stress-strain slope as the diameter of the pristine zigzag SW-αPNTs enlarges. The obtained results denote that by increasing the strain rate, the ultimate stress/ultimate strain are respectively increased/declined. The stress-strain slope keeps increasing as the strain rate grows. It is worth noting that the existence of mono-atomic vacancy defects in the (12,0) zigzag and (0,10) armchair SW-αPNT structures leads to a drop in the tensile strength by amounts of 11.1% and 12.5%, respectively. Also, the ultimate strain is considerably altered by mono-atomic vacancy defects.

• Advances in nano research
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• v.15 no.1
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• pp.35-48
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• 2023

Nanoparticles are known for their outstanding properties such as particle size, surface area, optical and electrical properties. These properties have significantly boasted their applications in various surface phenomena. In this work, calcium oxide nanoparticles were synthesized from periwinkle shells as an approach towards waste management through resource recovery. The sol gel method was used for the synthesis. The nanoparticles were characterized using X-Ray diffractometer (XRD), Fourier Transformed Infra-Red Spectrophotometer (FTIR), Brunauer Emmett Teller (BET), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and ultra violet visible spectrophotometer (UV-visible). While DLS and SEM underestimate the particle diameter, the BET analysis reveals surface area of 138.998 m²/g, pore volume = 0.167 m³/g and pore diameter of 2.47 nm. The nanoparticles were also employed as an adsorbent for the purification of dye (methyl orange) contaminated water. The adsorbent showed excellent removal efficiency (up to 97 %) for the dye through the mechanism of physical adsorption. The adsorption of the dye fitted the Langmuir and Temkin models. Analysis of FTIR spectrum after adsorption complemented with computational chemistry modelling to reveal the imine nitrogen group as the site for the adsorption of the dye unto the nanomaterials. The synthesized nanomaterials have an average particle size of 24 nm, showed a unique XRD peak and is thermally and mechanically stable within the investigated temperature range (30 to 70 ℃).

• Advances in nano research
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• v.15 no.6
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• pp.521-531
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• 2023

Quantum-dot cellular automata (QCA) has shown great potential in the nanoscale regime as a replacement for CMOS technology. This work presents a specific approach to static random-access memory (SRAM) cell based on 2:1 multiplexer, 4-bit SRAM array, and 32-bit SRAM array in QCA. By utilizing the proposed SRAM array, a single-layer 16×32-bit SRAM with the read/write capability is presented using an optimized signal distribution network (SDN) crossover technique. In the present study, an extremely-optimized 2:1 multiplexer is proposed, which is used to implement an extremely-optimized SRAM cell. The results of simulation show the superiority of the proposed 2:1 multiplexer and SRAM cell. This study also provides a more efficient and accurate method for calculating QCA costs. The proposed extremely-optimized SRAM cell and SRAM arrays are advantageous in terms of complexity, delay, area, and QCA cost parameters in comparison with previous designs in QCA, CMOS, and FinFET technologies. Moreover, compared to previous designs in QCA and FinFET technologies, the proposed structure saves total energy consisting of overall energy consumption, switching energy dissipation, and leakage energy dissipation. The energy and structural analyses of the proposed scheme are performed in QCAPro and QCADesigner 2.0.3 tools. According to the simulation results and comparison with previous high-quality studies based on QCA and FinFET design approaches, the proposed SRAM reduces the overall energy consumption by 25%, occupies 33% smaller area, and requires 15% fewer cells. Moreover, the QCA cost is reduced by 35% compared to outstanding designs in the literature.

• Advances in nano research
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• v.15 no.5
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• pp.451-466
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• 2023

Gastrointestinal cancer (GC) is a prevalent malignant tumor of the digestive system that poses a severe health risk to humans. Due to the specific organ structure of the gastrointestinal system, both endoscopic and MRI diagnoses of GIC have limited sensitivity. The primary factors influencing curative efficacy in GIC patients are drug inefficacy and high recurrence rates in surgical and pharmacological therapy. Due to its unique optical features, good biocompatibility, surface effects, and small size effects, nanotechnology is a developing and advanced area of study for the detection and treatment of cancer. Because of its deep location and complex surgery, diagnosing and treating gastrointestinal cancer is very difficult. The early diagnosis and urgent treatment of gastrointestinal illness are enabled by nanotechnology. As diagnostic and therapeutic tools, nanoparticles directly target tumor cells, allowing their detection and removal. XGBoost was used as a classification method known for achieving numerous winning solutions in data analysis competitions, to capture nonlinear relations among many input variables and outcomes using the boosting approach to machine learning. The research sample included 300 GC patients, comprising 190 males (72.2% of the sample) and 110 women (27.8%). Using convolutional neural networks (CNN) and artificial neural networks (ANN)-EXtreme Gradient Boosting (XGBoost), the patients mean± SD age was 50.42 ± 13.06. High-risk behaviors (P = 0.070), age at diagnosis (P = 0.037), distant metastasis (P = 0.004), and tumor stage (P = 0.015) were shown to have a statistically significant link with GC patient survival. AUC was 0.92, sensitivity was 81.5%, specificity was 90.5%, and accuracy was 84.7 when analyzing stomach picture.

• Advances in nano research
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• v.15 no.5
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• pp.401-410
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• 2023

Vibration investigation of fluid-filled three layered cylindrical shells is studied here. A cylindrical shell is immersed in a fluid which is a non-viscous one. Shell motion equations are framed first order shell theory due to Love. These equations are partial differential equations which are usually solved by approximate technique. Robust and efficient techniques are favored to get precise results. Employment of the wave propagation approach procedure gives birth to the shell frequency equation. Use of acoustic wave equation is done to incorporate the sound pressure produced in a fluid. Hankel's functions of second kind designate the fluid influence. Mathematically the integral form of the Lagrange energy functional is converted into a set of three partial differential equations. It is also exhibited that the effect of frequencies is investigated by varying the different layers with constituent material. The coupled frequencies changes with these layers according to the material formation of fluid-filled FG-CSs. Throughout the computation, it is observed that the frequency behavior for the boundary conditions follow as; clamped-clamped (C-C), simply supported-simply supported (SS-SS) frequency curves are higher than that of clamped-simply (C-S) curves. Expressions for modal displacement functions, the three unknown functions are supposed in such way that the axial, circumferential and time variables are separated by the product method. Computer software MATLAB codes are used to solve the frequency equation for extracting vibrations of fluid-filled.