Addressing Bioprinting Challenges in Tissue Engineering
Synthesis of Zinc Oxide Nanoflower using Egg Shell Membrane as Template
In Vitro and in Vivo Experiment of Antibacterial Silver Nanoparticle-Functionalized Bone Grafting Replacements
Biocompatibility in Orthopedic Implants: Advancements and Challenges
Contemporary Approaches towards Emerging Visual Prosthesis Technologies
An Investigation on Recent Trends in Metamaterial Types and its Applications
A Review on Plasma Ion Nitriding (PIN) Process
A Review on Friction and Wear Behaviors of Brake’s Friction Materials
Comparative Parabolic Rate Constant and Coating Properties of Nickel, Cobalt, Iron and Metal Oxide Based Coating: A Review
Electro-Chemical Discharge Machining- A review and Case study
Electrical Properties of Nanocomposite Polymer Gels based on PMMA-DMA/DMC-LiCLO2 -SiO2
Comparison Of Composite Proton Conducting Polymer Gel Electrolytes Containing Weak Aromatic Acids
Enhancement in Electrical Properties of PEO Based Nano-Composite Gel Electrolytes
Effect of Donor Number of Plasticizers on Conductivity of Polymer Electrolytes Containing NH4F
PMMA Based Polymer Gel Electrolyte Containing LiCF3SO3
This paper details an investigation into various advancements in plasma arc machining process. Characterization of the temperature of the plasma has always been a great challenge in plasma arc machining. In most of the investigations, surface temperatures due to plasma heating are systematically characterized through numerical modeling and experimental investigations are done using newer techniques such as infrared radiation thermometry. Furthermore, the characteristics of plasma cutting for thick steel ship plate have been discussed. The experimental investigations have revealed that the gas cutting speed is significantly lower than plasma cutting speed. The flow of molten metal is a governing factor in the process. This flow was found to be influenced by the cutting conditions during plasma cutting through experiments. Another prominent factor is the impact of the quality of the cut, by the shape of the cut and heat affected zone depth. In addition to the quality considerations, cost is also important. The removal rate is therefore, to be accurately estimated for evaluating the cost of production. Considering the plasma cutting machine as a system, i) power of the system, and ii) system process variables require supplementary considerations while optimizing the process outputs.
In this study, a finite element model and an artificial neural network model have been used to predict nugget size for resistance spot weld of AZ31 Mg alloy. The quality and strength of spot welds determine the integrity of the structure, which depends thoroughly on the nugget size. Different spot welding parameters such as the welding current, the welding time and electrode force were selected to be used for the FE (Finite Element) model. Although, the use of a finite-element analysis decreases the main costs associated with the nugget-size measurement tests; due to high complexity of a spot weld, its FE models are very time-consuming and requiring high-speed computers. So in this study, a FE model along with an Artificial Neural Network (ANN) has been adopted to predict the nugget size. The results obtained with the FE analysis were used to build up a back-propagation ANN model for the nugget-size prediction. The results revealed that a combination of these two developed models can accurately and rapidly predict the nugget size for a resistance spot weld of AZ31 Mg alloy.
Electrochemical assisted abrasive flow finishing is a newly developed hybrid finishing process which is used to finish the internal parts of work piece having complicated geometry to a large extent. In electrochemical assisted abrasive flow machining higher abrasion of the material was detected due to the combined effect of ECM(Electro Chemical Machining) and AFF (Abrasive Flow Finishing) processes. In Electrochemical aided abrasive flow machining, a electrolyte is added to the prepared media .This media consist of a kind of polymeric carrier and abrasive particles that are hydrocarbon gel, Al O , Silicon based polymer, and NaI (Sodium iodide) as electrolytic salt. In this experimental 2 3 research, different process parameters such as voltage, abrasive concentration, number of cycles, molal concentration and diameter of rod were considered at different levels for response characteristic of surface roughness (Ra) based on Taguchi method using standard L27 Orthogonal Array (OA) for the plan of experimentation. To determine the contribution of each parameter, analysis of variance was used.
Multiwalled Carbon Nanotubes (MWCNT) were melt-blended into ABS matrix using twin screw extrusion process. The percentage of MWCNT was varied from 0 to 15%. Tensile properties were measured using ASTM D638-10. At 10 wt.% these composites showed the highest modulus values of ~1600 MPa, which is nearly 40% higher compared to pure ABS. The ultimate tensile strength values of 15 wt.% MWCNT-ABS composite was 25% more than pure ABS. The failure strain of MWCNT-ABS composites drops linearly to 4% for a reinforcement of 15 wt.% MWCNT in ABS matrix. FESEM (Field Emission Scanning Electron Microscopy) examination of the specimens revealed a combination phase separated and exfoliated structure with polymer matrix over MWCNT. The experimental results were compared with theoretical iso-stress, iso-strain & Halpin-Tsai models. The experimental results lie between the theoretical values determined using the iso-stress and Halpin-Tsai models only if the 'effective l/d' ratio is considered in case of MWCNT. Microscopic analysis of the composites revealed the 'effective l/d' ratio to be in the range of 1 to 2.5. The experimental results of the ultimate strength values match well with the modified rule of mixture model, with strength efficiency and effective length factors. This paper has attempted to introduce two new factors 'effective l/d ratio' and 'effective length' to co-relate experimental and theoretical data.
This paper presents the time evolution of a quantum wave packet bound in the Morse potential. The quantum wave packet is the superposition of vibrational energy levels of a diatomic molecule in an anharmonic potential. The probability density function, auto-correlation function, and various time scales have been used to explore the revival pattern of this wave packet. The dynamics of the wave packet with respect to time shows a series of collapses and the subsequent revivals. The results are presented for CO molecule.