Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (6/6 displayed)

  • 2023Experimental investigation to optimize machining parameters for super duplex stainless steel in spark EDM using die-sinking and MQL system2citations
  • 2023Experimental investigation on the mechanical performance of the Al<sub>2</sub>O<sub>3</sub> and ZrO<sub>2</sub> added Al-Mg-Si alloy for structural applications21citations
  • 2022Hot corrosion behaviour of constant and pulsed current welded Hastelloy X in Na<sub>2</sub>SO<sub>4</sub>, V<sub>2</sub>O<sub>5</sub>, and NaCl salt mixture at 900 °C5citations
  • 2020Numerical modelling and experimental validation of crater formation in WEDM hybrid turning of Ti-6Al-4V alloy15citations
  • 2015Tool Wear Analysis of Al 6061 Reinforced with 10 wt% Al<sub>2</sub>O<sub>3</sub> Using High Hardened Inserts5citations
  • 2015A Parametric Optimization on Cutting Force during Laser Assisted Machining of Inconel 718 Alloy8citations

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Chart of shared publication
Mathur, Ayush Bansi
1 / 1 shared
Chunamari, Omkar Vinay
1 / 1 shared
Kumar, Sampath
1 / 4 shared
Talabi, Henry
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Bhowmik, Abhijit
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Sivanraju, Rajkumar
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Sathishkumar, M.
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Arivazhagan, N.
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Manikandan, M.
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Balasubramanian, Arulmurugan
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2022
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2015

Co-Authors (by relevance)

  • Mathur, Ayush Bansi
  • Chunamari, Omkar Vinay
  • Kumar, Sampath
  • Talabi, Henry
  • Bhowmik, Abhijit
  • Sivanraju, Rajkumar
  • Sathishkumar, M.
  • Arivazhagan, N.
  • Manikandan, M.
  • Balasubramanian, Arulmurugan
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article

Experimental investigation to optimize machining parameters for super duplex stainless steel in spark EDM using die-sinking and MQL system

  • Mathur, Ayush Bansi
  • Chunamari, Omkar Vinay
  • Kumar, Sampath
  • M., Dr. Vignesh
Abstract

<jats:p> The current experimental work discusses the electric discharge machining (EDM) of super duplex stainless steel with conventional die-sinking and minimum quantity lubrication (MQL) approach. The dielectric used in the conventional die-sinking EDM process is kerosene, and sunflower oil with air mixture is used in MQL-type machining conditions. The solid-type alpha brass electrodes of diameter 10 mm were used for machining. The most prominent input variables like pulse time (OFF and ON) and discharge current (varied at 3 levels) were selected, and Taguchi's L9 orthogonal array design was selected for experimentation. The responses like electrode wear rate (EWR), hole circularity (HC), material removal rate (MRR), and surface roughness (SR) were analyzed. The output results obtained from the experimental trials were analyzed using S/N ratios and analysis of variance (ANOVA). The most contributing input parameter affecting the responses like SR, HC, MRR, and EWR outputs were analyzed. The results showed that the optimum machining conditions were obtained at L3 and L9 levels for conventional die-sinking and MQL-type machining conditions, respectively. Out of three varying input parameters, pulse time (OFF) is the most contributing factor in deciding various responses. The same has been confirmed by ANOVA analysis. The theoretical prediction of experimental data was made using the Fuzzy logic approach, and the best optimal level is found out individually for all four responses. </jats:p>

Topics
  • impedance spectroscopy
  • surface
  • stainless steel
  • brass