A critical review on the contributions of chemical and physical factors toward the nucleation and growth of large-area graphene

Since the first isolation of graphene over a decade ago, research into graphene has exponentially increased due to its excellent electrical, optical, mechanical and chemical properties. Graphene has been shown to enhance the performance of various electronic devices. In addition, graphene can be simply produced through chemical vapor deposition (CVD). Although the synthesis of graphene has been widely researched, especially the CVD growth method, the lack of understanding of various synthetic parameters still limits the fabrication of large-area and defect-free graphene films. This report critically reviews various parameters affecting the quality of CVD grown graphene to understand the relationship between these parameters and thechoice of metal substrates and to provide a point of reference for future studies of large-area, CVD-grown graphene

Synthesis and Biological Evaluation of some Novel 2-Mercaptobenzothiazoles Carrying 1,3,4-Oxadiazole, 1,3,4-Thiadiazole and 1,2,4-Triazole Moieties

Several 2-mercaptobenzothiazole derivatives containing 1,3,4-oxadiazoles, 1,2,4-triazoles and 1,3,4-thiadiazoles at the second position were synthesized. Some of these synthesized compounds were evaluated for their in vivo analgesic, anti-inflammatory, acute toxicity and ulcerogenic actions. Some of the tested compounds showed significant analgesic and anti-inflammatory activities. Two of the compounds showed significant gastrointestinal protection compared to the standard drug diclofenac sodium. The compounds were also tested for their in vitro antimicrobial activity with most displaying selective activity against the Gram-negative bacteria Pseudomonas aeruginosa. In the present investigation the tested compounds did not possess antifungal activity.Keywords: 2-Mercaptobenzothiazoles, 1,3,4-oxadiazoles, 1,3,4-thiadiazoles, Antimicrobial Activity, Anti-inflammatory Activit

Synthesis, Analgesic, Anti-inflammatory and Antimicrobial Activities of Some Novel Pyrazoline Derivatives

Purpose: Microbial infections often produce pain and inflammation. Chemotherapeutic, analgesic and anti-inflammatory drugs are prescribed simultaneously in normal practice. The compound possessing all three activities is not common.The purpose of the present study was to examine whether molecular modification might result in detection of new potential antirheumatic drugs having antimicrobial activities. Method: A series of novel 4-(5′-substituted aryl-4′, 5′-dihydropyrazole-3′-yl-amino) phenols 2a-f have been synthesized by treating substituted aryl-N-chalconyl amino phenols 1a-f with hydrazine hydrate. The starting materials were synthesized from p-aminoacetophenone. Their structures were confirmed by IR, 1H NMR spectral data. The synthesized compounds were investigated for analgesic, ant-inflammatory and antimicrobial activities. Result: The data reported in Tables 2, 3 & 4 shows that effect of variation in chemical structure on activity was rather unpredictable. Seldom did a particular structural modification lead to uniform alteration in activity in all tests. The substitution which appeared to be most important for high order of activity in the greatest number of test was the p-choloroaryl group. The introduction of p-nitro and p-hydroxy group in aryl moiety of the pyrazole analogs 2c and 2e produce compounds with potent analgesic, anti-inflamatory and, in a few cases, antimicrobial properties. Conclusion: The observed increase in analgesic, anti-inflammatory and antimicrobial activities are attributed to the presence of 4-NO2, 2-OH and 4-Cl in phenyl ring at 5-position of pyrazoline ring of synthesized compounds. In some cases their activities are equal or more potent than the standard drugs. Keywords: Pyrazole, Analgesic, Anti-inflammatory, Antibacterial activity Tropical Journal of Pharmaceutical Research Vol. 7 (2) 2008: pp. 961-96

Bayesian optimisation of hexagonal honeycomb metamaterial

Periodic mechanical metamaterials, such as hexagonal honeycombs, have traditionally been designed with uniform cell walls to simplify manufacturing and modelling. However, recent research has suggested that varying strut thickness within the lattice could improve its mechanical properties. To fully explore this design space, we developed a computational framework that leverages Bayesian optimisation to identify configurations with increased uniaxial effective elastic stiffness and plastic or buckling strength. The best topologies found, representative of relative densities with distinct failure modes, were additively manufactured and tested, resulting in a 54% increase in stiffness without compromising the buckling strength for slender architectures, and a 63% increase in elastic modulus and a 88% increase in plastic strength for higher volume fractions. Our results demonstrate the potential of Bayesian optimisation and solid material redistribution to enhance the performance of mechanical metamaterials

Magnesiothermic Reduction of Silica: A Machine Learning Study

undamental studies have been carried out experimentally and theoretically on the magnesiothermic reduction of silica with different Mg/SiO2 molar ratios (1–4) in the temperature range of 1073 to 1373 K with different reaction times (10–240 min). Due to the kinetic barriers occurring in metallothermic reductions, the equilibrium relations calculated by the well-known thermochemical software FactSage (version 8.2) and its databanks are not adequate to describe the experimental observations. The unreacted silica core encapsulated by the reduction products can be found in some parts of laboratory samples. However, other parts of samples show that the metallothermic reduction disappears almost completely. Some quartz particles are broken into fine pieces and form many tiny cracks. Magnesium reactants are able to infiltrate the core of silica particles via tiny fracture pathways, thereby enabling the reaction to occur almost completely. The traditional unreacted core model is thus inadequate to represent such complicated reaction schemes. In the present work, an attempt is made to apply a machine learning approach using hybrid datasets in order to describe complex magnesiothermic reductions. In addition to the experimental laboratory data, equilibrium relations calculated by the thermochemical database are also introduced as boundary conditions for the magnesiothermic reductions, assuming a sufficiently long reaction time. The physics-informed Gaussian process machine (GPM) is then developed and used to describe hybrid data, given its advantages when describing small datasets. A composite kernel for the GPM is specifically developed to mitigate the overfitting problems commonly encountered when using generic kernels. Training the physics-informed Gaussian process machine (GPM) with the hybrid dataset results in a regression score of 0.9665. The trained GPM is thus used to predict the effects of Mg-SiO2 mixtures, temperatures, and reaction times on the products of a magnesiothermic reduction, that have not been covered by experiments. Additional experimental validation indicates that the GPM works well for the interpolates of the observations.publishedVersio

Directly Printable Organic ASK Based Chipless RFID Tag for IoT Applications

A chipless RFID tag with unique ASK encoding technique is presented in this paper. The coding efficiency is enhanced regarding tag capacity. The amplitude variations of the backscattered RFID signal is used for encoding data instead of OOK Strips of different widths are used to have amplitude variations. The ASK technique is applied using three different substrates of Kapton (R) HN, PET, and paper. To incorporate ASK technique, dual polarized rhombic shaped resonators are designed. These tags operate in the frequency range of 3.1-10.6 GHz with size of 70 x 42 mm(2). The presented tags are flexible and offer easy printability. The paper-based decomposable organic tag appears as an ultra low-cost solution for wide scale tracking. This feature enables them to secure a prominent position in the emerging fields of IoT and green electronics

Array atomic force microscopy for real-time multiparametric analysis.

Nanoscale multipoint structure-function analysis is essential for deciphering the complexity of multiscale biological and physical systems. Atomic force microscopy (AFM) allows nanoscale structure-function imaging in various operating environments and can be integrated seamlessly with disparate probe-based sensing and manipulation technologies. Conventional AFMs only permit sequential single-point analysis; widespread adoption of array AFMs for simultaneous multipoint study is challenging owing to the intrinsic limitations of existing technological approaches. Here, we describe a prototype dispersive optics-based array AFM capable of simultaneously monitoring multiple probe-sample interactions. A single supercontinuum laser beam is utilized to spatially and spectrally map multiple cantilevers, to isolate and record beam deflection from individual cantilevers using distinct wavelength selection. This design provides a remarkably simplified yet effective solution to overcome the optical cross-talk while maintaining subnanometer sensitivity and compatibility with probe-based sensors. We demonstrate the versatility and robustness of our system on parallel multiparametric imaging at multiscale levels ranging from surface morphology to hydrophobicity and electric potential mapping in both air and liquid, mechanical wave propagation in polymeric films, and the dynamics of living cells. This multiparametric, multiscale approach provides opportunities for studying the emergent properties of atomic-scale mechanical and physicochemical interactions in a wide range of physical and biological networks

Compact RFID Enabled Moisture Sensor

This research proposes a novel, low-cost RFID tag sensor antenna implemented using commercially available Kodak photo-paper. The aim of this paper is to investigate the possibility of stable, RFID centric communication under varying moisture levels. Variation in the frequency response of the RFID tag in presence of moisture is used to detect different moisture levels. Combination of unique jaw shaped contours and T-matching network is used for impedance matching which results in compact size and minimal ink consumption. Proposed tag is 1.4x9.4 cm(2) in size and shows optimum results for various moisture levels upto 45 % in FCC band with a bore sight read range of 12.1 m