Materials Map

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

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

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.

×

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.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Sariffudin, Norshahida

  • Google
  • 2
  • 6
  • 4

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2022Prediction and Optimization on Tribological Behaviour of Kenaf/Carbon Fiber Reinforced Epoxy Matrix Hybrid Composites4citations
  • 2020Effect of Stacking Sequences on Mechanical Properties of Kenaf Hybrid Compositescitations

Places of action

Chart of shared publication
Badari, Siti Norbahiyah Mohamad
1 / 1 shared
Sharuhil, Nurul Atikah Hamdan
1 / 1 shared
Ali, Afifah
1 / 1 shared
Ali, Afifah Mohd
1 / 1 shared
Ismail, Hanafi
1 / 4 shared
Norbahiyah, S.
1 / 4 shared
Chart of publication period
2022
2020

Co-Authors (by relevance)

  • Badari, Siti Norbahiyah Mohamad
  • Sharuhil, Nurul Atikah Hamdan
  • Ali, Afifah
  • Ali, Afifah Mohd
  • Ismail, Hanafi
  • Norbahiyah, S.
OrganizationsLocationPeople

article

Prediction and Optimization on Tribological Behaviour of Kenaf/Carbon Fiber Reinforced Epoxy Matrix Hybrid Composites

  • Badari, Siti Norbahiyah Mohamad
  • Sariffudin, Norshahida
  • Sharuhil, Nurul Atikah Hamdan
  • Ali, Afifah
Abstract

<jats:p>The awareness on sustainability of the environment among the researchers leads to the exploration of natural fiber composite materials. Hybridization of synthetic fiber and natural fiber is one of the potential strategies to enhance the mechanical properties as well as the degradability of such composite materials. However, less information concerning the optimization of tribological properties of this hybrid composite is available in literature. The aim of this study is to propose a statistical model to predict and optimize wear and coefficient of friction of kenaf/carbon reinforced epoxy composite. The value of parameters; load and sliding velocity ranges from 10 to 30 N and 20.9 to 52.3 m/s, respectively, are used to assess wear and coefficient of friction (COF) of different stacking sequences using the Analysis of Variance (ANOVA). The tribological test was conducted using a pin-on-disc tribometer. Multifactorial design analysis was employed to optimize the test control variables. It was found that, the optimized factors that affects the coefficient of friction and wear is at load 30 N and sliding velocity of 52.36 m/s. The proposed statistical models for wear and COF have 99.5% and 97.6% reliability, respectively. The generated equation models are bounded within the wear test control factors and ranges. The outcome from this study will be very useful for main parameter prediction for an optimized wear and COF.</jats:p>

Topics
  • impedance spectroscopy
  • Carbon
  • laser emission spectroscopy
  • wear test
  • composite
  • coefficient of friction