Viscosity of Ar-Cu nanofluids by molecular dynamics simulations: Effects of nanoparticle content, temperature and potential interaction

Zeroual, Soukaina; Loulijat, Hamid; Achehal, E.; Estellé, Patrice; Hasnaoui, A.; Ouaskit, S.

doi:10.1016/j.molliq.2018.07.090

Cited by 46 publications

(7 citation statements)

References 32 publications

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“…To validate the application of the interatomic potential and the G-K method to MDS, the viscosity of nanofluids with pure Ar was calculated. In the simulations, the viscosity of pure Ar was found to be 2.78 3 10 -4 Pa s, which was in agreement with Zerouala et al 46 This proves the reliability of the numerical methods. To investigate the effect of nanoparticle size on the viscosity of nanofluids, three different nanoparticle sizes (9.17, 11.55 and 14.55 Å ) were chosen in simulations at the particle volume concentration of 1.29%.…”

Section: Viscosities Of Nanofluidssupporting

confidence: 88%

The effect of nanoparticle size and nanoparticle aggregation on the flow characteristics of nanofluids by molecular dynamics simulation

Bao

Zhong

Jie

et al. 2019

Advances in Mechanical Engineering

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Molecular dynamics simulation is used to investigate the flow characteristics of Cu–Ar nanofluids considering the influence of nanoparticle size and nanoparticle aggregation. Nanofluids viscosity is calculated by equilibrium molecular dynamics based on Green–Kubo equation. Results demonstrate that the viscosity of nanofluids decreases with the increase of nanoparticle size. In addition, nanoparticle aggregation results in the increase of the nanofluids viscosity. Compared with nanoparticle size, nanoparticle aggregation has a larger impact on viscosity. Nanofluids flowing in parallel-plate nanochannels are simulated. The velocity profiles are studied through three nanoparticle sizes (11.55, 14.55, and 18.33 Å) and four nanoparticle aggregate configurations. Results show that the velocity profile of 14.55 Å nanoparticle size is larger than that of other two nanoparticle sizes. As for four nanoparticles, the nanoparticles clustering as a line leads to the maximum velocity profile, while the nanoparticles clustering as a cube causes the minimum velocity profile. Compared with viscosity, nanoparticle aggregation has a greater effect on the velocity profile. When the nanoparticles are evenly distributed, the influence of viscosity on velocity profiles is dominant. Otherwise, the aggregation, aggregate configuration, and distribution of nanoparticles have a dominant impact on the flow characteristics of nanofluids.

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Section: Viscosities Of Nanofluidssupporting

confidence: 88%

The effect of nanoparticle size and nanoparticle aggregation on the flow characteristics of nanofluids by molecular dynamics simulation

Bao

Zhong

Jie

et al. 2019

Advances in Mechanical Engineering

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“…16(a) that, viscosity increases with increasing nanofluid volume fraction ϕ, and decreases with the increase of temperature T. In both cases, the trend is almost linear. This result is consistent with previous studies [41][42][43] on nanofluids. Therefore, this MPINN, despite having been trained with very few high-fidelity data points, as shown by the red dots on Fig.…”

Section: Predictive Performance Of Mpinn For Nanofluid Viscositysupporting

confidence: 94%

“…On the other hand, at high temperatures, ϕ affects the relative viscosity more significantly. Zeroual et al [41] reported similar effects at higher temperatures in their study. It is observed from Fig.…”

Section: Predictive Performance Of Mpinn For Nanofluid Viscositysupporting

confidence: 66%

Extraction of material properties through multi-fidelity deep learning from molecular dynamics simulation

Islam

Thakur

Mojumder

et al. 2021

Computational Materials Science

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“…The extraordinary properties of nanofluids compared to conventional fluids have recently led to a significant increase in the volume of studies performed on nanofluids [15][16][17][18]. These features can include improved heat transfer and reduced pressure drop, which are the main parameters in the design of electrical and mechanical equipment [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Effect of water/carbon interaction strength on interfacial thermal resistance and the surrounding molecular nanolayer of CNT and graphene flake

Jabbari

Rajabpour

Saedodin

2019

Journal of Molecular Liquids

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Heat transfer at the liquid/solid interface, especially at the nanoscale, has enormous importance in nanofluids. This study investigates liquid/solid interfacial thermal resistance and structure of the formed molecular nanolayer around a carbon-based nanoparticle. Employing non-equilibrium molecular dynamics simulation and thermal relaxation method, the nanofluid systems with different nanoparticle diameters and different surface wettability were investigated. Simulation results show that carbon nanotubes (CNTs) with a smaller diameter attract more value of the base fluid and lead to a reduced Kapitza resistance. It was found that the thickness of the nanolayer around the nanoparticle is independent of the water/carbon interaction strength. Also, the value of the Kapitza resistance decreases with increasing the interaction strength. Ultimately, a correlation was proposed for the thermal resistance of CNT/water and graphene/water nanofluids in terms of wettability intensity of nanoparticle surface.The proposed correlation in addition to fitting to simulation results can cover the physical conditions of the system.Corresponding authors: * Rajabpour@eng.ikiu.ac.ir † s_sadodin@semnan.ac.ir

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Viscosity of Ar-Cu nanofluids by molecular dynamics simulations: Effects of nanoparticle content, temperature and potential interaction

Cited by 46 publications

References 32 publications

The effect of nanoparticle size and nanoparticle aggregation on the flow characteristics of nanofluids by molecular dynamics simulation

The effect of nanoparticle size and nanoparticle aggregation on the flow characteristics of nanofluids by molecular dynamics simulation

Extraction of material properties through multi-fidelity deep learning from molecular dynamics simulation

Effect of water/carbon interaction strength on interfacial thermal resistance and the surrounding molecular nanolayer of CNT and graphene flake

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