Comparison of CVD and MOCVD-grown Al2O3 coatings in the performance of cemented carbide cutting tool inserts

Low-pressure MOCVD, with tris(2,4 pentanedionato)aluminum(III) as the precursor, was used in the present investigation to coat alumina on to cemented carbide cutting tools. To evaluate the MOCVD process, the efficiency in cutting operations of MOCVD-coated tools was compared with that of tools coated using the industry-standard CVD process.Three multilayer cemented carbide cutting tool inserts, viz., TiN/TiC/WC, CVD-coated Al2O3 on TiN/TiC/WC, and MOCVD-coated Al2O3 on TiN/TiC/WC, were compared in the dry turning of mild steel. Turning tests were conducted for cutting speeds ranging from 14 to 47 m/min, for a depth of cut from 0.25 to 1 mm, at the constant feed rate of 0.2 mm/min. The axial, tangential, and radial forces were measured using a lathe tool dynamometer for different cutting parameters, and the machined work pieces were tested for surface roughness. The results indicate that, in most of the cases examined, the MOCVD-coated inserts produced a smoother surface finish, while requiring lower cutting forces, indicating that MOCVD produces the best-performing insert, followed by the CVD-coated one. The superior performance of MOCVD-alumina is attributed to the co-deposition of carbon with the oxide, due to the very nature of the precursor used, leading to enhanced mechanical properties for cutting applications in harsh environment.

Synthesis of electrically conducting copolymers of o-/m-toluidines and o-/m-amino benzoic acid in an organic peroxide system and their characterization

Copolymers of o-lm-toluidine with o-lm-amino benzoic acid have been synthesized by chemical polymerization using inverse emulsion pathway and characterized by a number of techniques including UV-Vis, FT-IR, FT Raman, EPR and NMR spectroscopies, thermal analysis and conductivity. The solubility of the copolymers in organic solvents increases with increase in the amount of amino benzoic acid in the feed. The copolymers synthesized at room temperature show relatively higher conductivity and are obtained in higher yield compared to those synthesized at 0 and 60 degreesC. The spectral studies have revealed restricted conjugation along the polymer chain. The effect of -COOH substituent on the copolymer structure is discussed. (C) 2003 Elsevier Science B.V All rights reserved.

Volume Change behaviour in Calcitic Soil influenced with Sulphuric Acid using Artificial Neural Networks

This paper elucidates the methodology of applying artificial neural network model (ANNM) to predict the percent swell of calcitic soil in sulphuric acid solutions, a complex phenomenon involving many parameters. Swell data required for modelling is experimentally obtained using conventional oedometer tests under nominal surcharge. The phases in ANN include optimal design of architecture, operation and training of architecture. The designed optimal neural model (3-5-1) is a fully connected three layer feed forward network with symmetric sigmoid activation function and trained by the back propagation algorithm to minimize a quadratic error criterion.The used model requires parameters such as duration of interaction, calcite mineral content and acid concentration for prediction of swell. The observed strong correlation coefficient (R2 = 0.9979) between the values determined by the experiment and predicted using the developed model demonstrates that the network can provide answers to complex problems in geotechnical engineering.

A Mechanism for the Occurrence of Ions in Distilled Water

Solar distillation can be used to produce potable water from contaminated water. However, studies show that ions such as F(-) and NO(3)(-) occur in distillates from solar stills. In order to understand the reasons for this behavior, imaging and distillation experiments were conducted. White dots were seen in the vapor space above the interface of hot water poured into containers. The concentrations of various ions such as F(-) and SO(4)(2-) in the distillates from thermal and solar distillation experiments were roughly comparable when the feed consisted of deionized water and also solutions having fluoride concentrations of 100 and 10 000 mg/L. These observations suggest that aerosols enter the distillation setup through leaks and provide nuclei for the condensation of water vapor. The water-soluble component of aerosols dissolves in the drops formed, and some of the drops are transferred to the distillate by buoyancy-driven convection.

Novel algorithm for online voltage stability assessment based on feed forward neural network

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

Preferential oxidation of CO on Ni/CeO2 catalysts in the presence of excess H-2 and CO2

Preferential oxidation of CO (CO-PROX) was carried out over Ni supported on CeO2 prepared by the co-precipitation method. The influence of metal loadings (2.5, 5 and 10 wt.% Ni) and the reaction conditions such as reaction temperature and feed composition on CO oxidation and oxidation selectivity were evaluated by using dry reformate gas. No other reactions like CO or CO2 methanation, coking, reverse water gas shift (RWGS) reaction is observed in the temperature range of 100-200 A degrees C on these catalysts. Hydrogen oxidation dominates over CO oxidation above the temperature of 200 A degrees C. An increase in oxygen leads to an increase in CO conversion but a simultaneous decrease in the O-2 selectivity. It has been noticed that 5 and 10 % Ni/CeO2 show better catalytic activity towards CO-PROX reaction. These catalysts were characterized by S-BET, XRD, TEM, XPS and H-2-TPR.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Low temperature CO oxidation and water gas shift reaction over Pt/Pd substituted in Fe/TiO2 catalysts

We demonstrate the activity of Ti0.84Pt0.01Fe0.15O2-delta and Ti0.73Pd0.02Fe0.25O2-delta catalysts towards the CO oxidation and water gas shift (VMS) reaction. Both the catalysts were synthesized in the nano crystalline form by a low temperature sonochemical method and characterized by different techniques such as XRD, FT-Raman, TEM, FT-IR, XPS and BET surface analyzer. H-2-TPR results corroborate the intimate contact between noble metal and Fe ions in the both catalysts that facilitates the reducibility of the support. In the absence of feed CO2 and H-2, nearly 100% conversion of CO to CO2 with 100% H-2 selectivity was observed at 300 degrees C and 260 degrees C respectively, for Ti0.84Pt0.01Fe0.15O2-delta and Ti0.73Pd0.02Fe0.25O2-delta catalyst. However, the catalytic performance of Ti0.73Pd0.02Fe0.25O2-delta deteriorates in the presence of feed CO2 and H-2. The change in the support reducibility is the primary reason for the significant increase in the activity for CO oxidation and WGS reaction. The effect of Fe addition was more significant in Ti0.73Pd0.02Fe0.25O2-delta than Ti0.84Pt0.01Fe0.15O2-delta. Based on the spectroscopic evidences and surface phenomena, a hybrid reaction scheme utilizing both surface hydroxyl groups and the lattice oxygen was hypothesized over these catalysts for WGS reaction. The mechanisms based on the formate and redox pathway were used to fit the ldnetic data. The analysis of experimental data shows the redox mechanism is the dominant pathway over these catalysts. Copyright (C) 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Excellent performance of Pt-free cathode in alkaline direct methanol fuel cell at room temperature

We report the room temperature cell performance of alkaline direct methanol fuel cells (ADMFCs) with nitrogen-doped carbon nanotubes (NCNTs) as cathode materials. NCNTs show excellent oxygen reduction reaction activity and methanol tolerance in alkaline medium. The open-circuit-voltage (OCV) as well as the power density of ADMFCs first increases and then saturates with NCNT loading. Similarly, the OCV initially increases and reaches saturation with the increase in the concentration of methanol feed stock. Overall, NCNTs exhibit excellent catalytic activity and stability with respect to Pt based cathodes.

Influence of tool rotation speed and feed rate on the forming limit of friction stir welded AA6061-T6 sheets

In this study, the influence of tool rotation speed and feed rate on the forming limit of friction stir welded Al 6061-T651 sheets has been investigated. The forming limit curve was evaluated by limit dome height test performed on all the friction stir welded sheets. The welding trials were conducted at a tool rotation speed of 1300 and 1400 r/min and feed rate of 90 and 100 mm/min. A third trial of welding was performed at a rotational speed of 1500 r/min and feed rate 120 mm/min. It is found that with increase in the tool rotation speed, from 1300 to 1400 r/min, for a constant feed rate, the forming limit of friction stir welded blank has improved and with increase in feed rate, from 90 to 100 mm/min, for a constant tool rotation speed, it has decreased. The forming limit of friction stir welded sheets is better than unwelded sheets. The thickness gradient after forming is severe in the cases of friction stir welded blanks made at higher feed rate and lower rotation speed. The strain hardening exponent of weld (n) increases with increase in tool rotation speed and it decreases with increase in feed rate. It has been demonstrated that the change in the forming limit of friction stir welded sheets with respect to welding parameters is due to the thickness distribution severity and strain hardening exponent of the weld region during forming. There is not much variation in the dome height among the friction stir welded sheets tested. When compared with unwelded sheets, dome height of friction stir welded sheets is higher in near-plane-strain condition, but it is lesser in stretching strain paths.