Effect of Ozone Pretreatment on Biodegradability Enhancement and Biogas Generation Potential From Biomethanated Distillery Effluent

The study evaluates the effect of ozone pretreatment on biodegradability enhancement of biomethanated distillery effluent. Results revealed that ozone pretreatment led to biodegradability index (BI = BOD/COD) enhancement up to 0.58 along with COD, color and toxicity reduction of up to 33%, 25% and 40%, respectively. Anaerobic digestion of pretreated effluent resulted in favorable biogas generation with methane content, yield and COD reduction of up to 62%, 39 mL/g COD and 57%, respectively. Kinetics of biogas generation determined by modified Gompertz model indicated methane production potential and production rate of 48.08 mL/g COD and 8.085 mL/g COD.day respectively under optimal conditions.     

Influence of transverse vibrations on convective heat transfer in parallel flow tube-in-tube heat exchanger

Tube-in-tube heat exchangers are widely used in food processing industries and wastewater treatment for both heating and cooling. Enhancement techniques namely active, passive, and compound are developed to reduce the thermal resistance in heat exchangers by improving convective heat transfer with or without increase in surface area. The present experimental study is aimed at analyzing the influence of vibrations on the convective heat transfer of a parallel flow tube-in-tube heat exchanger. The heat exchanger is placed in horizontal position and is subjected to transverse vibrations under turbulent fluid flow conditions. Experiments were performed at four frequencies (20, 40, 60, and 100 Hz), three amplitudes (1, 2, and 3 m/s²), and three vibration generator positions along its length, in the Reynolds number range of 10 710 to 21 420. An enhancement in Nusselt number is found with vibration than without vibration throughout the entire range of Reynolds numbers. A maximum enhancement of 33% at 40 Hz frequency, 3 m/s² amplitude, and vibration generator position at three-fourth of the tube length was observed. Empirical correlations are developed for Nusselt number to determine the heat transfer coefficient with vibration with an error of $\pm$10%.     

A general model-based approach to two-dimensional infrared correlation spectroscopy incorporating the global phase angle

We describe a theoretical framework for a model-based approach to two-dimensional correlation spectroscopy that is generally applicable to any arbitrary model function. The method is based on the correlation between spectral data and a set of model waveforms with a varying correlation index, the global phase angle Theta. When experimental spectral intensity variations are expressed as sinusoidal, exponential, Lorentzian, or quadratic functions, the proposed approach allows us to estimate the quantitative values of the target parameters in those expressions. In addition, this method enables us to assess the sequential order in a series of bands undergoing non-identical intensity changes in a dynamic data set. We present both simulated and experimentally obtained data that illustrate that the deviations from linearity of the absorption band intensity waveforms are clearly detected and can be quantitatively estimated using quadratic functions.     

Impact of surface modifications on hydrogen uptake by Fe@f-MWCNTs and Cu@f-MWCNTs at non-cryogenic temperatures

A comprehensive study has been conducted to evaluate the hydrogen uptake capacity of carboxylate functionalized multi-walled carbon nanotubes (f-MWCNTs) after strategic incorporation of Fe and Cu nanoparticles on the surface. Metal decorated multi-walled carbon nanotubes (Fe@f-MWCNTs and Cu@f-MWCNTs) were prepared by refluxing various concentrations of metal precursor and f-MWCNTs in different reaction medium such as water, amine and DMF. The prepared materials were characterized by FT-IR, powder XRD, SEM, TEM and BET analyzer. The adsorption isotherms revealed that the hydrogen storage capacity of Fe@f-MWCNTs and Cu@f-MWCNTs was 0.55 and 0.68 wt%, respectively, at 253 K and 70 bar. Similarly, both compounds showed 0.39 and 0.5 wt% adsorption at 298 K and 70 bar, respectively. The uptake of hydrogen by metal decorated multi-walled carbon nanotubes was remarkably enhanced by a factor of 2 and 5 times that of Pristine MWCNT at 253 K and 298 K, respectively.     

Ozone-Induced Biodegradability Enhancement and Color Reduction of a Complex Pharmaceutical Effluent

The treatment of a complex pharmaceutical effluent using a combination of ozonation and biological treatment is reported with the use of ozonation as a pre- and posttreatment. Pretreatment facilitated biodegradability index (BI = BOD/COD) enhancement of up to 0.44 along with COD and color reduction of up to 42% and 33%, respectively. Subsequent anaerobic biodegradation of effluent indicated negligible biogas generation; however, aerobic biodegradation of pretreated effluent resulted in COD reduction (73%) and color reduction (62%), which was also indicated by the biokinetic parameters. Further, ozonation as a posttreatment led to higher overall COD (87%) and color (93%) removal.     

Designing nanostructures for sensor applications

Nanostructured materials have shown great potential in improving the sensitivity and reliability of chemical and biological sensors. The ability to control the geometric shape (size, separation, orientation, alignment, etc.) of nanostructures and to integrate nanostructures from different materials becomes one of the great challenges for sensor fabrication. Glancing angle deposition techniques can fabricate well-aligned three-dimensional nanostructures through computer programming. By rotating the substrate in both polar and azimuthal directions, one can fabricate desired nanostructures, such as nanorod arrays with different shapes, nanospring arrays, and even multilayer nanostructures. This method offers full three-dimensional control of the nanostructure with the additional capability of self-alignment and can be easily integrated into microdevices and optical devices. With the high surface area and high aspect ratio of those nanostructures, different sensors such as enzyme-based biosensors and optical sensors with higher sensitivity have been demonstrated.     

Estimating probabilistic confidence for mixture components identified using a spectral search algorithm

Providing a confidence measure associated with the substance(s) identified in an unknown mixture by a spectral search technique is critical for non-expert users of devices and techniques based on spectroscopy. In this work, a technique for estimating probabilities associated with substances identified by spectral searching is described. In the proposed approach, a mixture analysis algorithm processes the spectrum of an unknown sample using a spectral library to generate a list of substances that may be present in the sample. The partial correlation of each of the substances in the list is then computed. The estimation of the probability is accomplished through a generalized linear model that converts the partial correlation values to a probability measure for each of the mixture components. The statistical properties of partial correlation allow probability estimation irrespective of whether a substance is present in a pure form or within a mixture. The technique was evaluated using both simulated and real Raman spectra of multi-component mixtures, and adequate performance was demonstrated.     

Generalised scheme for optimal learning in recurrent neuralnetworks

A new learning scheme is proposed for neural network architectures like the Hopfield network and bidirectional associative memory. This scheme, which replaces the commonly used learning rules, follows from the proof of the result that learning in these connectivity architectures is equivalent to learning in the 2-state perceptron. Consequently, optimal learning algorithms for the perceptron can be directly applied to learning in these connectivity architectures. Similar results are established for learning in the multistate perceptron, thereby leading to an optimal learning algorithm. Experimental results are provided to show the superiority of the proposed method     

Rapid and sensitive detection of respiratory virus molecular signatures using a silver nanorod array SERS substrate

A spectroscopic assay based on surface enhanced Raman scattering (SERS) using silver nanorod array substrates has been developed that allows for rapid detection of trace levels of viruses with a high degree of sensitivity and specificity. This novel SERS assay can detect spectral differences between viruses, viral strains, and viruses with gene deletions in biological media. The method provides rapid diagnostics for detection and characterization of viruses generating reproducible spectra without viral manipulation.