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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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (5/5 displayed)

  • 2024Influence of Grinding Aids on the Grinding Performance and Rheological Properties of Cementitious Systems1citations
  • 2024Effect of Silica Fume Utilization on Structural Build-Up, Mechanical and Dimensional Stability Performance of Fiber-Reinforced 3D Printable Concrete10citations
  • 2020Synthesis and characterization of additive graphene oxide nanoparticles dispersed in water: Experimental and theoretical viscosity prediction of non‐Newtonian nanofluid41citations
  • 2020EFFECT OF POLYMER/CEMENT RATIO AND CURING REGIME ON POLYMER MODIFIED MORTAR PROPERTIES2citations
  • 2020Thermal conductivity enhancement of nanofluid by adding multiwalled carbon nanotubes: Characterization and numerical modeling patterns44citations

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Kaya, Yahya
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Şahin, Hatice Gizem
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Mardani, Naz
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Şahi̇n, Hati̇ce Gi̇zem
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Beytekin, Hatice Elif
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Li, Zhixiong
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Xu, Yang
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Bach, Quangvu
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Karimipour, Arash
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Ranjbarzadeh, Ramin
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Babadi, Elmira
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2020

Co-Authors (by relevance)

  • Kaya, Yahya
  • Şahin, Hatice Gizem
  • Mardani, Naz
  • Şahi̇n, Hati̇ce Gi̇zem
  • Beytekin, Hatice Elif
  • Li, Zhixiong
  • Xu, Yang
  • Bach, Quangvu
  • Karimipour, Arash
  • Malekahmadi, Omid
  • Nguyen, Quyen
  • Hadi, Ramin
  • Ranjbarzadeh, Ramin
  • Jokar, Zahra
  • Du, Congcong
  • Dorazio, Annunziata
  • Babadi, Elmira
OrganizationsLocationPeople

article

Thermal conductivity enhancement of nanofluid by adding multiwalled carbon nanotubes: Characterization and numerical modeling patterns

  • Bach, Quangvu
  • Karimipour, Arash
  • Malekahmadi, Omid
  • Nguyen, Quyen
  • Du, Congcong
  • Mardani, Ali
  • Jokar, Zahra
  • Dorazio, Annunziata
  • Babadi, Elmira
Abstract

<jats:p>Nanofluid is divided in two major section, mono nanofluid (MN) and hybrid nanofluid (HN). MN is created when a solid nanoparticle disperses in a fluid, whereas HN has more than one solid nanomaterial. In this research, iron (III) oxide (Fe<jats:sub>3</jats:sub>O<jats:sub>4</jats:sub>) is MN, and Fe<jats:sub>3</jats:sub>O<jats:sub>4</jats:sub> plus multiwalled carbon nanotube (MWCNT) is HN, whereas both are mixed and dispersed into the water basefluid. Thermal conductivity (TC) of Fe<jats:sub>3</jats:sub>O<jats:sub>4</jats:sub>/water and MWCNT/Fe<jats:sub>3</jats:sub>O<jats:sub>4</jats:sub>/water was measured after preparation and numerical model performed on the resulted data. After that, field emission scanning electron microscope (FESEM) was studied for microstructural observation of nanoparticles. MN and HN TC were studied at temperature ranges of 25 to 50°C and volume fractions of 0.2% to 1.0%. For MN and HN, thermal conductivity enhancement (TCE) of 32.76% and 33.23% was measured at 50°C temperature—1.0% volume fraction, individually. Different correlations have been calculated for numerical modeling, with <jats:italic>R</jats:italic><jats:sup>2</jats:sup> = 0.9. Deviation of 0.6007% and 0.6096% was calculated for given correlations for MN and HN individually. Deviation of 0.5862% and 0.6057% was calculated for trained models, for MN and HN individually. Thus, by adding MWCNT to Fe<jats:sub>3</jats:sub>O<jats:sub>4</jats:sub>‐H<jats:sub>2</jats:sub>O nanofluid, TC is enhanced 0.47%, and this HN has agreeable heat transfer potential.</jats:p>

Topics
  • nanoparticle
  • impedance spectroscopy
  • Carbon
  • nanotube
  • iron
  • thermal conductivity