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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Materials Map under construction

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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1.080 Topics available

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (6/6 displayed)

  • 2023FRICTION STIR PROCESSING AND CLADDING: AN INNOVATIVE SURFACE ENGINEERING TECHNIQUE TO TAILOR MAGNESIUM-BASED ALLOYS FOR BIOMEDICAL IMPLANTS17citations
  • 2023EXPERIMENTAL STUDY ON THE SURFACE ROUGHNESS AND OPTIMIZATION OF CUTTING PARAMETERS IN THE HARD TURNING USING BIOCOMPATIBLE TiAlN-COATED AND UNCOATED CARBIDE INSERTS8citations
  • 2023FABRICATION AND CHARACTERIZATION OF MAGNESIUM-BASED Mg-TITANIA SURFACE COMPOSITE FOR BIOIMPLANTS9citations
  • 2022Energy-efficient method for developing in-situ Al-Cu metal matrix composites using microwave sintering and friction stir processing17citations
  • 2022Modeling and Prediction of Grain Size and Hardness of ZE41/ZrO$$_2$$ Nano-surface Composite Using Multiple Regression, Power Law and Artificial Intelligence Techniques2citations
  • 2020Investigations on friction stir joining of 3D printed parts to overcome bed size limitation and enhance joint quality for unmanned aircraft systems29citations

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Chart of shared publication
Agrawal, Manoj Kumar
1 / 3 shared
Bhojak, Vishal
1 / 1 shared
Jain, Jinesh Kumar
1 / 1 shared
Saxena, Kuldeep Kumar
2 / 4 shared
Singhal, Tejendra Singh
1 / 1 shared
Prakash, Chander
1 / 12 shared
Dikshit, Mithilesh K.
1 / 1 shared
Pathak, Vimal K.
1 / 1 shared
Agrawal, Reeya
1 / 1 shared
Buddhi, Dharam
1 / 1 shared
Saxena, Kuldeep K.
1 / 7 shared
Singh, Rajesh
1 / 6 shared
Lade, Jayahari
1 / 1 shared
Jain, Jinesh K.
1 / 1 shared
Sonia, Pankaj
1 / 1 shared
Bajakke, Padmakumar A.
1 / 2 shared
Deshpande, Anand S.
1 / 2 shared
Lakshmikanthan, Avinash
1 / 6 shared
Chart of publication period
2023
2022
2020

Co-Authors (by relevance)

  • Agrawal, Manoj Kumar
  • Bhojak, Vishal
  • Jain, Jinesh Kumar
  • Saxena, Kuldeep Kumar
  • Singhal, Tejendra Singh
  • Prakash, Chander
  • Dikshit, Mithilesh K.
  • Pathak, Vimal K.
  • Agrawal, Reeya
  • Buddhi, Dharam
  • Saxena, Kuldeep K.
  • Singh, Rajesh
  • Lade, Jayahari
  • Jain, Jinesh K.
  • Sonia, Pankaj
  • Bajakke, Padmakumar A.
  • Deshpande, Anand S.
  • Lakshmikanthan, Avinash
OrganizationsLocationPeople

article

EXPERIMENTAL STUDY ON THE SURFACE ROUGHNESS AND OPTIMIZATION OF CUTTING PARAMETERS IN THE HARD TURNING USING BIOCOMPATIBLE TiAlN-COATED AND UNCOATED CARBIDE INSERTS

  • Dikshit, Mithilesh K.
  • Pathak, Vimal K.
  • Agrawal, Reeya
  • Buddhi, Dharam
  • Malik, Vinayak
  • Saxena, Kuldeep K.
Abstract

<jats:p> Machining of difficult-to-cut materials has always been a focus of research. In terms of surface roughness, it is one of the most important machinability indicators used to evaluate the performance of machining processes. This research aims to investigate the effect of biocompatible TiAlN-coated and uncoated carbide inserts, as well as the effect of cutting parameters such as feed, rotational speed, and depth of cut on surface roughness in the hard turning of M2 tool steel at 64 HRC. The central composite design is used to create the experimental layout. Surface roughness values are measured using separate experiments for coated and uncoated inserts. A quadratic model is selected, and an analysis of variance (ANOVA) is performed to test the adequacy of the developed model. From the ANOVA, it is found that feed and rotational speed are the most significant parameter while hard turning with TiAlN-coated and uncoated inserts, respectively. Cutting parameters are ranked according to their importance using the Pareto chart. The composite desirability function is employed to determine the optimal setting of cutting parameters to minimize the surface roughness and a confirmation experiment is conducted to validate the optimization results. Confirmation results are very close to the predicted value and the error between experimental and predicted results are 7.93% and 9.36% with TiAlN-coated and uncoated carbide inserts, respectively. TiAlN-coated carbide insert gives better surface roughness compared to an uncoated carbide insert. </jats:p>

Topics
  • impedance spectroscopy
  • surface
  • experiment
  • carbide
  • composite
  • tool steel