Individual multi-walled carbon nanotubes (MWCNTs) were exposed to the electron beam of 200 kV energy and high resolution transmission electron micrographs were recorded at several time intervals. Interestingly, the nucleation of diamond nanoparticles with in the highly disordered MWCNT matrix upon electron-irradiation is observed. This happens without any assistance of high pressures and temperatures. High pressure X-ray diffraction experiments were performed on core/shell structures which suggest that even the closed structures of carbon resist any inward pressure, thereby ruling out the possibility of a hypothetical internal pressure under the electron irradiation conditions. Our experiments suggest that the transformation of graphitic carbon into diamond in the size window of a few nanometers is possible due to the stability of the diamond and a selective dissolution effect of 200 kV electrons on graphite. A mechanism for the same is proposed.

The team has studied the relationship between the ability of the coals to be dissolved in crude anthracene oil and their composition. The coal samples taken from different deposits in Russia and Mongolia were characterized by different stages of metamorphism and tested by the Fourier transform infrared spectroscopy and Carbon-13 nuclear magnetic resonance. The data of a correlation analysis enabled us to find out that an amount of aromatic structures in coal macromolecules provided the main influence on the thermal dissolution of the coals. The middle-rank coals had the highest rates of coal organic matter transfer to liquid products. The data showed that the dissolution process was accompanied by destruction of weak bonds among aliphatic groups. The amount of methylene groups in the aliphatic part of coal macromolecules had a direct impact on conversion of the coal organic matter into soluble products.

Due to its capacity to manufacture low-cost 3D-printed structures, 3D-printing technology offers a unique opportunity for the fast epitome of various applications. Using a typical fused deposition modeling 3D printer along with a Discovery extruder, a graphene-ink can be 3D printed to produce an interdigitated electrode (IDE) arrangement. This work fabricated a 3D-printed planar supercapacitor from pristine graphene-ink without using high-temperature processing or functional additives. The printable ink (89%) is formulated from pristine graphene without the addition of any functional additives. The symmetric flexible supercapacitor is demonstrated with an excellent specific capacitance of 137.50 F/g at 0.5 A/g and an energy density of 12.23 Wh/kg. The obtained gravimetric energy density beats reported earlier carbon-based supercapacitors that are 3D or inkjet printed. The flexibility and robustness of 3D-printed devices are achieved up to 150° folding angles. This work demonstrates an efficient and easy method for fabricating practical energy storage devices featuring a customizable shape and excellent flexibility.

In this present investigation, machinability studies on novel aluminum composite with hybrid reinforcements of copper-coated 4% carbon fibers (CFs) and 3% nanoclay in AA6026 matrix fabricated by compocasting method is performed. Step drill bit and multifaceted drill bit are used by adopting central composite design (CCD) in response surface methodology (RSM). The outcomes show that, with a rise in rotational speed surface irregularities, resultant force and material removal rate (MRR) intensifies, and with the additional rise in rotational speed, all the outputs decrease considerably. High MRR, resultant cutting force, and surface roughness are obtained with multifaceted carbide drills, compared with a step drill. Desirability function is used to maximize the MRR and minimize the resultant cutting forces considering the constant surface roughness of 3 μm. The optimal values are rotational speed of 1285 rpm, feed rate of 60 mm/min with the step drill bit, producing an MRR of 0.0439 kg/sec and a resultant cutting force of 185.818 N. The second-order empirical models are developed for outputs, which are fed into the non-traditional metaheuristic Evaporation Rate-based Water Cycle Algorithm (ER-WCA) therefore the lower objective value is achieved with step drill of 51.7421. It is found that using a step drill the machinability performance of this hybrid nanocomposite is well improved than the machining with other drill bits. This composite fulfills the norms of 2000/53/CE-ELV European environmental directives.

NiMoS2 is a promising material for various functional applications and highly compatible with GO to make hybrid nanocomposites with excellent characteristics for supercapacitor electrode material. Deposition of NiMoS2 was achieved on the rGO(reduced Graphene Oxide) surface to form a NiMoS2− rGO nanocomposite by the method of the facile hydrothermal synthesis process. XRD pattern shows the crystalline nature of composites. Raman and EPMA result interpreting the composites formation and elements compositions, respectively. The sheet-like morphology of rGO was found in the composites by FESEM images. Particles distribution was confirmed by HR-TEM. The electrochemical properties of the pure NiMoS2 and NiMoS2– rGO composites have been studied by cyclic voltammetry analysis. The results revealed that the NiMoS2/ 5% rGO nanocomposites exhibit high specific capacitance compared to pure NiMoS2 due to the synergistic effects of NiMoS2 and rGO in the composite material. The photocatalytic behavior of the prepared nanocomposites for dye degradation was tested. The quantity of rGO has significantly improved the photocatalytic behavior of NiMoS2/ rGO composites. The studies on degradation mechanism, the N2 adsorption/desorption isotherms, pore size distribution behavior and % of removal of MB reveal the enhanced photocatalytic performance of sysnthesised composites.

The bituminous coal was extracted with different industrial solvents like coal tar (CT), heavy cycle oil (HCO) and with their blends to determine the influence of solvent type on the extract yield, composition, thermal behavior, properties such as solubility to toluene and quinoline. The extracts obtained at 380 °C represented pitch-like solid matter with the softening points of 72–127 °C depending on the solvent used. They were characterized using the elemental and group analysis, FTIR spectroscopy, TG-DTG thermogravimetry and liquid chromatography for benzo(a)pyrene concentration. Also, maltene fractions of some extracts were studied by GC–MS. The results showed coal dissolution and the properties of the extracts to differ greatly depending on the solvent used. Coal tar was more favorable solvent for coal dissolution than HCO. Good correlation between the extract aromaticity and the content of the toluene insolubles was observed. The maltene fractions of the extracts obtained with CT and CT blended with HCO consisted mainly of polycyclic aromatics, and that obtained with the HCO contained also large amount of aliphatic compounds. It was found that the amount of the carcinogenic benzo(a) pyrene (BaP) in the toluene soluble fractions of the extracts were different depending on the solvents used for extraction. The remarkable result was that the BaP concentrations in all extracts were much lower than in the solvents used.

Namnabat et al. (cf., [Carbon Letters, https://doi.org/10.1007/s42823-020-00194-2]) employ the classical approach of Li and Chou (cf., [Int J Solids Struct 40: 2487–2499]) to the implementation of the molecular structural mechanics method using the Bernoulli–Euler beam elements for nonlinear buckling analysis of double-layered graphene nanoribbons. However, more recent studies by Eberhardt and Wallmersperger (cf., [Carbon 95: 166–180]) and others (see, e.g., [Int J Eng Sci 133: 109–131]) have shown that the classical approach of Li and Chou poorly reproduces both in-plane and out-of-plane mechanical moduli of graphene. We have shown that the 2D beam-based hexagonal material used by Namnabat et al. poorly simulates the mechanical moduli of graphene, especially the bending rigidity modulus, and this material cannot be used for the buckling simulation of graphene sheets (or nanoribbons). In addition, it is noted that in Int J Eng Sci 133: 109–131, a modification of the classical approach of Li and Chou is given which exactly reproduces both in-plane (2D Young’s modulus and Poisson’s ratio) and out-of-plane (bending rigidity modulus) mechanical moduli of graphene using beam elements.

Preparation of activated carbon from biomass residue with conventional steam activation was conducted to find the alternative raw materials for meeting the high demand for low-cost porous material in the desiccant application. In this study, activated carbons were produced from dead camphor leaves using two-step methods at different preparation temperatures. The characterization results revealed that the prepared activated carbons have a surface area of 700 m2/g, with 75% of microporosity. The water vapor sorption study reported that the water uptake of camphor leaf-based activated carbons was strongly affected by the pore properties of the materials. Moreover, from the water adsorption kinetics, it was observed that the rate constant of adsorption was varied at each relative pressure, which can be assumed that the water adsorption mechanism is different at each relative pressure. From these results, it was revealed that the prepared camphor leaf-based activated carbons have a promising ability to adsorb water vapor from humid air.

We report the rapid single-step flame synthesis of hydrophobic carbon layers (C-layers) on the surface of stainless-steel (SS) substrates using vaporized biodiesel as the fuel. A co-flow canola methyl ester/air diffusion flame is used to generate a hydrophobic monolayer on the surface of the metal substrate upon its insertion into the reaction zone. Carbon deposition on the surface of the SS substrates varies by changing the SS disk’s position in the post-flame, and by varying its exposure time. The thickness and mass of the flame-formed monolayer varied depending on the substrate’s insertion point into the flame. However, the variation of mass did not significantly impact the C-layer’s uniformity or hydrophobicity. We hypothesize that a small “inner-cone” of the biodiesel flame along with a high soot propensity can result in an ideal medium to form uniform hydrophobic C-layers of unique hierarchical surface structure. This is supported by introducing SS substrates in methane/air flames formed using the same co-flow burner. The hydrophobic property of the carbon deposits was quantified by measuring the contact angle of water droplets placed on the film’s surface. A water droplet drop test was conducted on the flame-formed hydrophobic layers to study their wettability property.

In the following years, technology has progressed in so many ways that it has provided the cyber society with a resource that only computers can excel at, such as the art of counterfeit of media, which was before unavailable. Deepfakes are a term used to describe this kind of deception. The majority of well-documented Deep Fakes are produced using Generative Adversarial Network (GAN) Models, which are essentially two distinct Machine Learning Models that perform the roles of attack and defence. These models create and identify deepfakes until they reach a point where the morphing no longer detects the deepfakes anymore. Using this algorithm/model, it is possible to discover and create new media that has a similar demographic to the training set, resulting in the development of the ideal Deep Fake media. Because the alterations are carried out utilising advanced characteristics, they cannot be seen with the human eye. However, it is completely feasible to develop an algorithm that can automatically identify this kind of tampering carried out via the internet. This not only enables us to broaden the scope of our search beyond a single media item, but also beyond a large library of mixed media. The more it learns, the better it becomes as artificial intelligence takes over in full force with automation. In order to create better deep fakes, new models are being developed all the time, making it more difficult to distinguish between genuine and morphing material.

Gravitational lensing of point sources located inside the lens caustic is known to produce four images in a conguration closely related to the source position. We study this relation in the particular case of a sample of quadruply-imaged quasars observed by the Hubble Space Telescope. Strong correlations between the parameters dening the image conguration are revealed. The relation between the image conguration and the source position is studied. Some simple features of the selected data sample are exposed and commented upon. In particular, evidence is found for the selected sample to be biased in favor of large magnication systems. While having no direct impact on practical analyses of specic systems, our results have pedagogical value and deepen our understanding of the mechanism of gravitational lensing.

Predicting the quality of materials after they are subjected to plasma sintering is a challenging task because of the non-linear relationships between the process variables and mechanical properties. Furthermore, the variables governing the sintering process affect the microstructure and the mechanical properties of the final product. Therefore, an artificial neural network modeling was carried out to correlate the parameters of the spark plasma sintering process with the densification and hardness values of Ti-6Al-4V alloys dispersed with nano-sized TiN particles. The relative density (%), effective density (g/cm3), and hardness (HV) were estimated as functions of sintering temperature (oC), time (min), and composition (change in % TiN). A total of 20 datasets were collected from the open literature to develop the model. The high-level accuracy in model predictions (>80%) discloses the complex relationships among the sintering process variables, product quality, and mechanical performance. Further, the effect of sintering temperature, time, and TiN percentage on the density and hardness values were quantitatively estimated with the help of the developed model.