CO2 Hydrogenation over Ru-NPs Supported Amine-Functionalized SBA-15 Catalyst: Structure–Reactivity Relationship Study

Catalysis Letters - We gave an effective protocol to support Ru NPs on amine-functionalized SBA-15 mesoporous silica to catalyze the CO2 hydrogenation reaction. The amine groups present in the...     

Surface Integrity Assessment Upon Electric Discharge Machining of Die Steel Using Non-Destructive Magnetic Barkhausen Noise Technique

Surface integrity characterization of manufactured component is very important as it significantly affects the in-service performance of the component. Till now, surface integrity was evaluated using conventional measurement technique like microhardness tester, X-ray diffraction, optical microscopy and surface roughness tester. But, this technique being laboratory based cannot be used for in-service monitoring of the surface integrity. The present study focuses on the characterization of surface integrity upon electric discharge machined sample using non-destructive magnetic Barkhausen noise technique. Electric discharge machining was performed in die-sinking mode on die steel using copper–tungsten electrode (negative polarity). Experiment was performed by selecting different levels of peak current, gap voltage and pulse on time. Surface integrity characteristics like microhardness change, residual stress, microstructural alteration and surface roughness were analysed using microhardness tester, X-ray diffraction, optical microscopy and surface roughness tester, respectively, and were then correlated with magnetic parameter like root mean square value and peak value obtained from Barkhausen noise signal. The results show a good correlation between magnetic parameter (RMS and Peak value) of Barkhausen noise with the microhardness and surface roughness of the machined sample.

     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.     

Study of Compatibilized Liquid Crystalline Polymer/Cyclic Olefin Copolymer Blends

The technology to produce compatibilized blends of liquid crystalline polymer and highly amorphous cyclic olefin copolymers through two novel approaches were studied. The first approach was to use silane-functionalized halloysite nanotube as nonspecific compatibilizer and the second method was reactive compatibilization. The study of blends and their resulting microstructure; their thermal, mechanical, and viscoelastic properties were investigated. The kinetic study of blends compatibilized through both routes was performed.