Thermophysical properties and thermal characteristics of phase change emulsion for thermal energy storage media

Kawanami, Tsuyoshi; Togashi, Kenichi; Fumoto, Koji; Hirano, Shigeki; Zhang, Peng; Shirai, Kohji; Hirasawa, Shigeki

doi:10.1016/j.energy.2016.04.021

Cited by 59 publications

(14 citation statements)

References 29 publications

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“…The increase in viscosity with a more dispersed phase concentration can lead to a reduced fluidity [146], as well as to a decreased heat transfer coefficient due to the reduced level of convection happening within the system. Many PCEs are newtonian fluids that start exhibiting non-newtonian behavior for larger concentrations of the dispersed phase (usually >30%) when the shear stress-shear rate dependence becomes nonlinear [58,139], finding sustained by several studies, as shown in Table 2. When the shear stress is increased over a high limit, some PCEs experience a decrease in their viscosity, possibly due to the breakage of formed aggregates at lower shear stresses and droplet reorientations [131].…”

Section: Influence Of Dispersed Phase Concentration On Viscositymentioning

confidence: 90%

“…In nanoemulsions, the variation in viscosity with temperature has been investigated by a number of authors [57,58,138]. The decrease in viscosity with the increase in temperature was found to become more accentuated the higher the concentration of nanodroplets was, probably due to the extra energy provided increasing the Brownian motion and thus resulting in a reduction in viscosity [131,138,139,147]. Relevant results, showing the physics behind the decrease, are shown in Figure 4 [58].…”

Section: Temperature Influence On Viscositymentioning

confidence: 99%

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TES Nanoemulsions: A Review of Thermophysical Properties and Their Impact on System Design

2021

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Thermal energy storage materials (TES) are considered promising for a large number of applications, including solar energy storage, waste heat recovery, and enhanced building thermal performance. Among these, nanoemulsions have received a huge amount of attention. Despite the many reviews published on nanoemulsions, an insufficient number concentrate on the particularities and requirements of the energy field. Therefore, we aim to provide a review of the measurement, theoretical computation and impact of the physical properties of nanoemulsions, with an integrated perspective on the design of thermal energy storage equipment. Properties such as density, which is integral to the calculation of the volume required for storage; viscosity, which is a decisive factor in pressure loss and for transport equipment power requirements; and thermal conductivity, which determines the heating/cooling rate of the system or the specific heat directly influencing the storage capacity, are thoroughly discussed. A comparative, critical approach to all these interconnected properties in pertinent characteristic groups, in close association with the practical use of TES systems, is included. This work aims to highlight unresolved issues from previous investigations as well as to provide a summary of the numerical simulation and/or application of advanced algorithms for the modeling, optimization, and streamlining of TES systems.

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Section: Influence Of Dispersed Phase Concentration On Viscositymentioning

confidence: 90%

Section: Temperature Influence On Viscositymentioning

confidence: 99%

TES Nanoemulsions: A Review of Thermophysical Properties and Their Impact on System Design

2021

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“…The gel is then diluted with water to produce a fine O/W nanoemulsion [ 194 ]. Compared to the other low-energy methods, DPE requires less surfactant, does not use solvent, and conserves more energy than PIC [ 195 ]. In a study by Yukuyama et al, an olive oil nanoemulsion was developed using a hydrophilic surfactant polyethylene glycol monooleyl ether.…”

Section: Formation Of Low-energy Nanoemulsionsmentioning

confidence: 99%

Nanoemulsions: A Review on the Conceptualization of Treatment for Psoriasis Using a ‘Green’ Surfactant with Low-Energy Emulsification Method

et al. 2021

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Psoriasis is a skin disease that is not lethal and does not spread through bodily contact. However, this seemingly harmless condition can lead to a loss of confidence and social stigmatization due to a persons’ flawed appearance. The conventional methods of psoriasis treatment include taking in systemic drugs to inhibit immunoresponses within the body or applying topical drugs onto the surface of the skin to inhibit cell proliferation. Topical methods are favored as they pose lesser side effects compared to the systemic methods. However, the side effects from systemic drugs and low bioavailability of topical drugs are the limitations to the treatment. The use of nanotechnology in this field has enhanced drug loading capacity and reduced dosage size. In this review, biosurfactants were introduced as a ‘greener’ alternative to their synthetic counterparts. Glycolipid biosurfactants are specifically suited for anti-psoriatic application due to their characteristic skin-enhancing qualities. The selection of a suitable oil phase can also contribute to the anti-psoriatic effect as some oils have skin-healing properties. The review covers the pathogenic pathway of psoriasis, conventional treatments, and prospective ingredients to be used as components in the nanoemulsion formulation. Furthermore, an insight into the state-of-the-art methods used in formulating nanoemulsions and their progression to low-energy methods are also elaborated in detail.

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“…(c) The PCMs nanocapsules in the slurry 18 . Thermophysical properties, such as viscosity and heat of fusion for emulsion consisting of organic PCM (RT10) and water, are described in a research paper by Shao et al 16 The thermophysical properties of nano‐sized particles of tetradecane, hexadecane, and octadecane as the dispersed PCM in water were the subject of the work of Kawanami et al 19 Paraffin flow properties in a laminar flow and the phenomenological model presented in Delgado et al 20 show that the measured heat transfer coefficient was about 3.5 to 5.5 times higher when a speed of 290 to 600 rpm was used in a PCM emulsion. The thermal and rheological properties of emulsion consisting of n‐octadecane as PCM nanoparticles with the mass ratios to water and surfactant of 10:90:2, 20:80:2, 30:70:2, 40:60:2 were measured by Zhang and Zhao, 21 while shear thinning behavior was clearly observed.…”

Section: Introductionmentioning

confidence: 99%

Intelligent modeling of rheological and thermophysical properties of nanoencapsulated PCM slurry

Jirandeh

Mohammadiun

et al. 2020

Heat Trans

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Nanoencapsulated phase change material slurries (NPCMS) combine properties of carried fluid and phase change material (PCM). Usage of NPCMS instead of water as a working fluid has a lot of advantages in many industrial fields. The costly and time-consuming determination of thermophysical properties of NPCMS through the experimental analysis led the current investigations to use soft computing methods like correlating, artificial neural network (ANN), and ant colony optimization (ACO R ). In this study, the application of ANN, empirical correlations, and ACO R for modeling the thermophysical properties of NPCM slurry, which has been synthesized through a facile and eco-friendly procedure, has been investigated. PCM nanocapsules have been synthesized using a miniemulsion polymerization method. Nancapsules consist of AP-25 as core and a Styrene shell, which is modified with graphene oxide nanosheets as an extra protective screen.The morphology and thermal properties of nanocapsules were characterized and analyzed, respectively. Results revealed that minimum average particle-size values result in a melting latent heat of 146.8 J/g. In case of NPCM slurry, the results showed that the thermal conductivity of MPCS decreased with particle concentration for the temperatures below the melting point. The NPCMS can be considered a Newtonian fluid within the test region (shear rate > 200/seconds and mass fraction < 0.25). The ANN-ACO R model consists of two neurons in the input layer, six neurons in the hidden layer, and two neurons in the output layer. The input layer consists of two nodes (PCM concentration and temperature) that correspond to parameters found essential and sufficient for thermophysical properties prediction. Upon comparison, the results show that the presented model, which is a combination of the ACO R algorithm and an artificial neural network, is compatible with experimental work. K E Y W O R D SANN modeling, ant colony, phase change material, slurry, thermophysical properties

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Thermophysical properties and thermal characteristics of phase change emulsion for thermal energy storage media

Cited by 59 publications

References 29 publications

TES Nanoemulsions: A Review of Thermophysical Properties and Their Impact on System Design

TES Nanoemulsions: A Review of Thermophysical Properties and Their Impact on System Design

Nanoemulsions: A Review on the Conceptualization of Treatment for Psoriasis Using a ‘Green’ Surfactant with Low-Energy Emulsification Method

Intelligent modeling of rheological and thermophysical properties of nanoencapsulated PCM slurry

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