CNT is known to undergo electrical breakdown on exposure to gases. This unique property has been used in designing CNT-based gas sensors. The electrical resistance of large-diameter MWCNTs was found to decrease in the presence of air after experiencing electrical breakdown, while pristine MWCNTs were not found to be appreciably sensitive. The deformation and the corresponding mechano electric effects of CNT were well predicted.

Composite electric field guided assembly (CEGA) method was used to locate a single MWCNT between electrodes. The electrical characteristics of the deposited MWCNTs were observed using I-V-curves. The large-diameter MWCNTs showed better sensitivity as they possess more distorted shells that can create more adsorption sites for oxygen molecules.

The oxidation of CNT begins in the defective or distorted region of the tube separated from the electrodes. The removal of complete shells including the contacts with the electrodes is observed as spikes in the I-V Graph plotted from experimental results. This observation can be due to the presence of two barriers for conductivity along the partially burnt or oxidized MWCNT, the Schottky barrier for carrier injection from the electrodes to the nanotubes and the barrier caused due to the hopping process.

Nanofluids are nanotechnology-based heat transfer fluids obtained by suspending nanometersized particles in conventional heat transfer fluids in a stable manner. In many of the physical phenomena such as boiling, there is significant change in the properties such as latent heat, thermal conductivity and heat transfer coefficient on addition of nanoparticles. These exceptional qualities of nanofluids mainly depend on the atomic level mechanisms, which in turn, govern all mechanical properties like strength, Young’s modulus, Poisson’s ratio, compressibility etc. Control over the fundamental thermo physical properties of the working medium will help to understand these unique phenomena of nanofluids to a great extent.

Macroscopic modeling approaches based on conventional relations of thermodynamics have proved to be incompetent to explain this difference. Hence atomistic ‘modeling and simulation’ has emerged as an efficient alternative for this. The enhancement of thermal conductivity of water by suspending nanoparticle inclusions has been experimented with and proved to be an effective method of enhancing convective heat dissipation.

This work mainly deals with thermal properties of nanofluids. Nano particle sized aluminium oxide, copper oxide and titanium dioxide have been taken in this work for the analysis of thermal conductivity. The effect of thermal conductivity on parameters like volume concentration of the fluid, nature of particle material, size and shape of the particle, nature of base fluid material and temperature has been computationally formulated and experimentally evaluated.

It has been found that there is an increase in effective thermal conductivity of the fluid by the addition of nanomaterials ascertaining an improvement in the heat transfer behavior of nanofluids. This facilitates the reduction in size of such heat transfer systems (radiators) and leads to increased energy and fuel efficiency, lower pollution and improved reliability.

The design of artificial gene regulatory networks has paved way for the construction of therapeutic gene circuits that would find application in next-generation gene therapy approaches.

The main challenge in such designs is in selecting the appropriate genetic components to make up the circuit in order to produce the anticipated or desired behavior. To eliminate this complexity, computational simulation tools are used to guide circuit design. This involves selection and genetic modification of components, till the required system behavior is achieved.

In this work, we have designed a model for a synthetic nano gene network. The gene expression involved in diseases caused by mutation, like cancer, Alzheimer’s disease (AD), etc. can be effectively controlled by nano gene silencing genetic switch.

Here, we have considered the case of Alzheimer’s disease. The dynamic behavior analysis of the individual genetic components and their combinations has been carried out by analyzing the computational results of electrochemical, thermodynamic and molecular simulation.

Genes that are responsible for genetic AD are APP, PSEN1 and PSEN2. Seventy five repressor proteins for AD have been identified. The interaction analysis of these proteins with each of the 3 genes has been carried out using Monte Carlo simulation. Voltage-driven and concentration-driven translocation dynamics of ions through a bio-nanopore have been investigated making use of continuum models based on the drift-diffusion theory.

Similarly, study of interaction between the repressor proteins and three different inducer proteins identified for AD has been carried out and the influence of this on the repressor protein-gene interaction has been studied. The designed genetic switch comprises mainly of repressor and inducer proteins. This technique is a type of gene therapy leading into silencing of the mutated part of the gene.

Magnetic nanoparticles (MNPs) can be used in a wide variety of biomedical applications like contrast agents for magnetic resonance imaging, magnetic labeling, controlled drug release, hyperthermia and in cell isolation. Most of these applications require well-defined and controllable interactions between the MNPs and living cells and can be made possible by a proper functionalization technique.

This paper describes a computational approach for the identification of magnetic nanoparticles for the development, design and demonstration of a novel, integrated system for selective and rapid removal of biological, chemical and radioactive biohazards from human body.

The attraction between an external magnet field and the MNPs enables separation of a wide variety of biological materials. This principle can be used for the isolation and aggregation of stray cancer cells from the blood or the bone marrow to make a proper and early diagnosis of leukemia. Similarly toxins, stones and other unwanted particles in the human body can be easily diagnosed and removed using the same technique.

Nano-particle sized gold and iron oxides have been studied in this work by quantum mechanical modeling and molecular dynamic (MD) simulation techniques. Structural, thermodynamic and magnetic properties have been formulated. Nano particles of size varying from 2nm to 20nm have been analyzed. Cell isolation ability of the nanoparticles has been compared based on the computational results.

MNPs are biologically activated and allowed to bind with the targeted cells via various pathways and thereby allowing certain cellular compartments to be specifically addressed. Once the cells are identified, the desired cellular compartments can be magnetically isolated and removed with the help of an external magnetic field.

Highly ordered and vertically aligned TiO2 nanotube arrays were synthesized by anodisation, modified with gold nanoparticles by cyclic voltammetry (CV) and used for the selective detection of ascorbic acid (AA) in the presence of uric acid and glucose.

Morphology of the sensor was analysed using FESEM and it was found that the diameter of the nanotubes and size of the gold nanoparticles were 40 and 20 nm respectively.

The electrocatalytic activity towards the oxidation of AA was determined using CV, differential pulse voltammetry and amperometry. The sensor showed a very good performance with a sensitivity of 46.8 μA mM−1 cm−2, response time below 2 seconds and linearity in the range of 1 μM to 5 mM with a detection limit of 0.1 μM. The sensor was tested for the AA concentration in pharmaceutical preparations.

A non-enzymatic glucose sensor was fabricated by electrochemical anodisation of copper electrode in potassium oxalate solution. Energy dispersive X-ray spectroscopy (EDS) and FTIR spectroscopy confirmed the presence of copper oxide (CuO) and copper oxalate (CuOx) on the modified electrode.

The fabricated electrode was nanoporous and highly rough. Linear sweep voltammetry (LSV) and amperometric studies proved that CuO/CuOx modified electrode has excellent electrocatalytic activity towards the oxidation of glucose.

The best performance of the sensor was obtained at 0.7 V and in 0.1 M sodium hydroxide (NaOH). At this optimum potential, the sensor was highly selective to glucose in the presence of ascorbic acid (AA) and uric acid (UA) which are common interfering species in biological fluids. The sensitivity was found to be very high (1890 µA mM-1 cm-2) with excellent linearity (R=0.9999) upto 15 mM having a low detection limit of 0.05 µM (S/N = 3). The modified electrode was tested for glucose level in blood serum.