Developing a new correlation to estimate the thermal conductivity of MWCNT-CuO/water hybrid nanofluid via an experimental investigation

By masoud Zadkhast, Davood Toghraie, Arash Karimipour. Journal of Thermal Analysis and Calorimetry, 2017

214 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Materials Chemistry, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/7843ba4785e42c0a53cc91a5edd5602585c949da

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Arash Karimipour
2. Mohammad Reza Safaei
3. Seyed Amin Bagherzadeh
4. A. Abdollahi
5. A. Taghipour
6. Davood Toghraie
7. Marjan Goodarzi
8. Omid Ali Akbari

In Materials Chemistry

1. Arash Karimipour
2. Mohammad Reza Safaei

In Renewable Energy, Sustainability and the Environment

1. Arash Karimipour
2. Mohammad Reza Safaei

Citations in the corpus

• A novel nonlinear regression model of SVR as a substitute for ANN to predict conductivity of MWCNT-CuO/water hybrid nanofluid based on empirical data (2019, background): “Table 1 The input-target dataset, k ( W mK ) [14].”