Murali Rangarajan

One-step synthesis of Pt-decorated graphene–carbon nanotubes for the electrochemical sensing of dopamine, uric acid and ascorbic acid

Platinum nanoparticle-decorated graphene and carbon nanotube (Pt–Gr–CNT) nanocomposites were synthesized by radio frequency chemical vapor deposition (RF-CVD) from ethanol, using a Pt/MgO catalyst. Morphological analysis showed Pt nanoparticles decorating graphene sheets and double-walled and multiwalled carbon nanotubes. It was observed that, upon encountering Pt nanoparticles, carbon nanotubes unravelled into graphene sheets. This may be due to graphitic carbon atoms from growing CNTs forming bonds with carbon atoms from other CNTs, particularly at the site of another Pt NP. The Pt–Gr–CNT-modified GCE showed high electrocatalytic activity towards the oxidation of ascorbic acid (AA), dopamine (DA) and uric acid (UA) in 0.1 M phosphate buffer solution (pH 7.0) in cyclic voltammetry (CV) and differential pulse voltammetry (DPV) studies. CV showed well-separated oxidation peaks of AA (−99 mV), DA (121 mV) and UA (261 mV). In DPV studies, the peak separation between AA–DA, DA–UA and AA–UA was 210 mV, 140 mV and 360 mV respectively. The simultaneous detection of AA, DA and UA using DPV, in respective concentration ranges of 200–900 μM, 0.2–30 μM, 0.1–50 μM, showed good linearity and sensitivities of 0.186 μA μM−1 cm−2 (AA), 9.199 μA μM−1 cm−2 (DA) and 9.386 μA μM−1 cm−2 (UA) respectively. The Pt–Gr–CNT/GCE was evaluated for the simultaneous detection of the three biomolecules in real sample solutions of a vitamin C tablet, human serum and urine. It showed recoveries in the range of 93–101%, indicating that it is a promising platform for further biosensor development.

Effect of different carbon fillers and dopant acids on electrical properties of polyaniline nanocomposites

Electrically conducting nanocomposites of polyaniline (PANI) with carbon-based fillers have evinced considerable interest for various applications such as rechargeable batteries, microelectronics, sensors, electrochromic displays and light-emitting and photovoltaic devices. The nature of both the carbon filler and the dopant acid can significantly influence the conductivity of these nanocomposites. This paper describes the effects of carbon fillers like carbon black (CB), graphite (GR) and muti-walled carbon nanotubes (MWCNT) and of dopant acids like methane sulfonic acid (MSA), camphor sulfonic acid (CSA), hydrochloric acid (HCl) and sulfuric acid (H2SO4) on the electrical conductivity of PANI. The morphological, structural and electrical properties of neat PANI and carbon–PANI nanocomposites were studied using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT–IR), UV–Vis spectroscopy and the four-point probe technique, respectively. Thermogravimetric analysis (TGA) and X-ray diffraction (XRD) studies were also conducted for different PANI composites. The results show that PANI and carbon–PANI composites with organic acid dopants show good thermal stability and higher electrical conductivity than those with inorganic acid dopants. Also, carbon–PANI composites generally show higher electrical conductivity than neat PANI, with highest conductivities for PANI–CNT composites. Thus, in essence, PANI–CNT composites prepared using organic acid dopants are most suitable for conducting applications.

Nano- and micro-hexagons of bismuth on polycrystalline copper: electrodeposition and heavy metal sensing

Hexagon-shaped bismuth nano- and micro-architectures have been electrodeposited onto polycrystalline copper electrodes from a nitrate bath at both constant current and constant potential conditions. Hexagonal geometries of varying sizes are obtained by tuning the deposition rate vis-a-vis that of a competing reaction, nitrate reduction. Nano-hexagons (100 nm to 1 μm) are obtained at 10 mA cm−2 when the HNO3 concentration is 0.2 M or less, and with 0.4 M HNO3, hexagons of sizes up to 20 μm are deposited. The obtained hexagons are polycrystalline. Further increase in nitric acid concentration results in fused sheet-like morphologies. Increasing bismuth concentration or reducing current density results in large crystallites. The ability of the obtained bismuth morphologies to detect ultratrace levels of lead has been studied. Only the nanohexagons and crystallites are able to detect lead at 1 ppb. The nanohexagons show good sensitivity to the detection of lead (LoD: 0.05 ppb or 0.24 nM; sensitivity: ~0.75 μA ppb−1) using Square-Wave Anodic Stripping Voltammetry (SWASV), and clearly distinct peaks for Pb2+, Zn2+, and Cd2+, indicating the potential for this morphology as an electrocatalytic material.

Synthesis of Carbon Nanotubes from Ethanol Using RF-CCVD and Fe–Mo Catalyst

Multiwalled carbon nanotubes (MWCNTs) were synthesized by RF (radio frequency) heating at 850°C using an MgO-supported bimetallic Fe–Mo catalyst. Ethanol was used as the carbon source. The MWCNTs were tested using Raman spectroscopy, high-resolution transmission electron microscopy (HRTEM), and thermogravimetric analysis (TGA). HRTEM studies show nanotubes with an average diameter of 16.0 ± 3.5 nm. In Raman spectroscopy, the ratios of intensities of the G and D band and the 2D and G bands were 0.90 and 0.47, respectively. These ratios are generally indicative of high crystallinity and purity of the MWCNTs. The purity of MWCNTs was calculated from TGA analysis.

G-Lets: A New Signal Processing Algorithm

Different signal processing transforms provide us with unique decomposition capabilities. Instead of using specific transformation for every type of signal, we propose in this paper a novel way of signal processing using a group of transformations within the limits of Group theory. For different types of signal different transformation combinations can be chosen. It is found that it is possible to process a signal at multiresolution and extend it to perform edge detection, denoising, face recognition, etc by filtering the local features. For a finite signal there should be a natural existence of basis in it’s vector space. Without any approximation using Group theory it is seen that one can get close to this finite basis from different viewpoints. Dihedral groups have been demonstrated for this purpose. General Terms signal processing, algorithm, group theory.

One-Step RF-CVD Method for the Synthesis of Graphene Decorated with Metal and Metal Oxide Nanoparticles.

Bilayer and few layer-graphene (Gr) with noble metal (Ag and Au) and TiO2 nanoparticles were synthesized using atmospheric pressure radio frequency chemical vapor deposition (APRF-CVD). The precursors for the formation of the respective nanoparticles were dissolved in ethanol and injected into the APRF-CVD containing a Cu foil catalyst at 1000 °C. The graphene obtained had a blistered morphology similar to bubble-wrap. The bubble-like protrusions on the graphene sheet were caused by large nanoparticle clusters (~220 nm) formed below the graphene sheets. Smaller nanoparticles (10-80 nm) were also observed on top of the graphene sheets. Encapsulation of the nanoparticles with graphene, to yield core-shell particles was observed. Similarly, secondary growth of carbon nanotubes (CNTs) from the Au nanoparticles was observed. The average full width half maxima (FWHM) of 2D bands in the Raman spectra indicate that the graphene formed was predominantly bilayer graphene for Gr-TiO2 (55 ± 1.72 cm-1), and few-layer graphene for Gr-Ag (76 ± 22 cm-1) and Gr-Au (88 ± 4.7 cm-1). Raman spectroscopy also showed evidence for the doping of graphene and surface-enhanced Raman sensitivity (SERS) in the materials. These electronic properties of graphene with nanoparticles are relevant to various applications such as optoelectronics, catalysis, chemical and biological sensing.

Edge detection using G-lets based on matrix factorization by group representations

Features of G-lets Edge Operator: Geometry of objects in the image are preserved.Edges are continuous.Tracking outlines of small objects in cluttered images are possible.Edges in noisy images without losing continuity is shown to be possible.Computations are light due to sparse operations. A new edge detection technique using transformation groups based G-lets filters is proposed in this paper. Discretizing gradients seem to produce discontinuity in classic edge detectors. No particular filter is capable of identifying meaningful edges at all scales and it increases computations with a multiscale approach. It is a challenge to get localized edges without spurious ones due to noise and integrate the obtained edges into meaningful object boundaries. Without breaking edge continuity and strictly localizing edges requires that filters do not blur the image during preprocessing. G-lets filters are found to be capable of performing well in most type of images including natural, noisy, low resolution and synthetic. In this paper, an edge detection algorithm using G-lets filters which are built by direct factorization of linear transformation matrices using irreducible representations is proposed. A multiresolution approach is shown to enhance the possibility of detecting faint edges. An edge tracing algorithm is presented to produce the edge image. The computational cost involved is comparatively lesser than existing filters. It is found that the geometries in the original image are preserved in the edge image. The edge tracing algorithm is capable of constructing object boundaries without the inner textures in a way that is not completely dependent on intensity thresholding. G-lets filters and the edge operator is found to be a promising algorithm for drastically bringing down the computations needed for realtime applications. The results are compared with BSDS500 boundary detection dataset using pb and global pb detectors.

Synthesis of multiwalled carbon nanotubes using RF-CCVD and a bimetallic catalyst

Multiwalled carbon nanotubes with high crystallinity and purity were synthesized with acetylene as the carbon source using radio frequency catalytic chemical vapor deposition method (RF-CCVD) and a bimetallic Fe-Co catalyst supported on CaO at 720°C. The sample obtained was tested using Raman spectroscopy, high resolution transition electron microscopy (HRTEM) and thermogravimetric analysis (TGA). The Raman spectra revealed G to D band and 2D to G band intensity ratios of 0.90 and 0.54 respectively. A purity of 90% was obtained from the TGA studies. HRTEM studies further showed that the nanotubes had an average diameter of 14.7 ± 4.76nm.

Critical evaluation of mechanism responsible for biomass abatement during electrochemical coagulation (EC) process: A critical review

This is a first review paper that delineates fundamental disinfection mechanism undergoes during the simple electrochemical coagulation (EC) process. The elucidation of detailed mechanistic phenomenon of EC process involved would help to enhance the disinfection efficiency. In this context, the biomass (bacteria, virus and algae) abatement mechanism by EC is critically reviewed and rationalized based on the experimental demonstration performed from the recent decade. Whereas, the effect of most significant abiotic operating parameters, dissolved contents and bacteria cell wall composition on biomass reduction are explored in detail. From these analyses, physical removal and chemical inactivation routes are identified for bacteria abatement mechanism during the EC process using sacrificial electrodes. Which includes (i) enmeshment of microbial contaminants by EC flocs, (ii) sweeping flocculation is preferentially for destabilization of negatively charged biomass, and (iii) inactivation/attenuation of micro-organism cell walls by electrochemically induced reactive oxygen species (ROS) or direct interaction of electric field. Perhaps, the overall abatement mechanism attributes due to the aforementioned phenomenon endures independently and/or synergistically during the EC process. Nonetheless, to obtain better understanding of virus and algae abatement mechanism, we require more experimental investigation on algae and virus removal. Eventually, more intensive research efforts on biomass attenuation by EC are most important to reinforce this claim.

Intelligent soil quality monitoring system for judicious irrigation

As the world population increases exponentially, it is mandatory that we adopt modern agricultural practices to meet food safety demands. Intelligent sensor networks acquire data about soil regarding moisture and nutrient deficiency. This data can be employed to automate irrigation and alert farmer about nutrient deficiency. The data obtained from soil is pushed to the cloud. Great processing capabilities makes cloud storage an important solution to store the vast amount of data generated by the wireless sensor network, which can also be viewed by the farmer through a Smartphone application. This paper proposes and evaluates on a real deployment of wireless sensor network based on an Internet of things platform.