scholarly journals Speed of sound of ionic liquids: Database, estimation, and its application for thermal conductivity prediction

AIChE Journal ◽  
2014 ◽  
Vol 60 (3) ◽  
pp. 1120-1131 ◽  
Author(s):  
Ke-Jun Wu ◽  
Qiao-Li Chen ◽  
Chao-Hong He
Keyword(s):  
Thermal Conductivity ◽  
Ionic Liquids ◽  
Speed Of Sound

Density and speed of sound measurements of imidazolium-based ionic liquids with acetonitrile at various temperatures

2014 ◽  
Vol 200 ◽  
pp. 160-167 ◽  
Author(s):  
S. Singh ◽  
I. Bahadur ◽  
Gan G. Redhi ◽  
D. Ramjugernath ◽  
Eno E. Ebenso
Keyword(s):  
Ionic Liquids ◽  
Speed Of Sound

scholarly journals Thermal Conductivity of Ionic Liquids and IoNanofluids. Can Molecular Theory Help?

Fluids ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 116
Author(s):  
Xavier Paredes ◽  
Maria José Lourenço ◽  
Carlos Nieto de Castro ◽  
William Wakeham
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Ionic Liquids ◽  
Imaging Techniques ◽  
Interfacial Area ◽  
Thermal Conductivity Enhancement ◽  
Molecular Theory ◽  
Estimation Methods ◽  
Diphenyl Oxide ◽  
Conductivity Enhancement

Ionic liquids have been suggested as new engineering fluids, specifically in the area of heat transfer, and as alternatives to current biphenyl and diphenyl oxide, alkylated aromatics and dimethyl polysiloxane oils, which degrade above 200 °C, posing some environmental problems. Addition of nanoparticles to produce stable dispersions/gels of ionic liquids has proved to increase the thermal conductivity of the base ionic liquid, potentially contributing to better efficiency of heat transfer fluids. It is the purpose of this paper to analyze the prediction and estimation of the thermal conductivity of ionic liquids and IoNanofluids as a function of temperature, using the molecular theory of Bridgman and estimation methods previously developed for the base fluid. In addition, we consider methods that emphasize the importance of the interfacial area IL-NM in modelling the thermal conductivity enhancement. Results obtained show that it is not currently possible to predict or estimate the thermal conductivity of ionic liquids with an uncertainty commensurate with the best experimental values. The models of Maxwell and Hamilton are not capable of estimating the thermal conductivity enhancement of IoNanofluids, and it is clear that the Murshed, Leong and Yang model is not practical, if no additional information, either using imaging techniques at nanoscale or molecular dynamics simulations, is available.

Speed of sound in ionic liquids with a common ion as a function of pressure and temperature

2018 ◽  
Vol 116 ◽  
pp. 235-240 ◽  
Author(s):  
Francisco Yebra ◽  
Katerina Zemánková ◽  
Jacobo Troncoso
Keyword(s):  
Ionic Liquids ◽  
Speed Of Sound ◽  
Common Ion

Thermal Conductivity Enhancement of Room Temperature Ionic Liquids (RTILs) With Various Magnetic Nanoparticles

2012 ◽  
Author(s):  
N. Y. Jagath B. Nikapitiya ◽  
Hyejin Moon
Keyword(s):  
Thermal Conductivity ◽  
Ionic Liquids ◽  
Magnetic Nanoparticles ◽  
Magnetic Fields ◽  
Room Temperature ◽  
Particle Concentration ◽  
Thermal Conductivity Enhancement ◽  
Room Temperature Ionic Liquids ◽  
Conductivity Enhancement ◽  
Magnetic Nanofluids

This paper reports an experimental study of thermal conductivity of room temperature ionic liquids (RTILs) based magnetic nanofluids. Various magnetic nanoparticles of metal oxides with high thermal conductivity, such as CuO, Al2O3, Fe3O4 and Carbon Nano Tubes (CNTs), were used to prepare magnetic nanofluids, while RTIL, trihexyl (tetradecyl) posphonium dicyanamide was used as the base fluid. Two major parameters that affect to the thermal conductivity enhancement of fluids were investigated. The effect of particle concentration and external magnetic fields were tested. It was observed that the magnetic nanofluids thermal conductivities increase with increment of particle concentration and external magnetic field parallel to the temperature gradient. Besides, it was observed that under higher magnetic fields, thermal conductivity enhancement tends to approach a saturation state. Surfactant was used to disperse magnetic nanoparticles within the RTILs. The transient hot wire method was used for this investigation.

scholarly journals Prediction of Density and Speed of Sound of Binary Ionic Liquid and Ketone Mixtures Using Artificial Neural Network

2019 ◽  
Vol 120 ◽  
pp. 01003
Author(s):  
Redden Rose Rivera ◽  
Allan Soriano
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Ionic Liquid ◽  
Ionic Liquids ◽  
Speed Of Sound ◽  
Negative Impact ◽  
Green Energy ◽  
Percentage Error ◽  
Average Percentage ◽  
Artificial Neural

The applications of ionic liquids solve a lot of major problems regarding green energy production and environment. Ionic liquids are solvents used as alternative to unfriendly traditional and hazardous solvents which reduces the negative impact to environment to a great extent. This study produced models to predict two of the basic physical properties of binary ionic liquid and ketone mixtures: density and speed of sound. The artificial neural network algorithm was used to predict these properties by varying the temperature, mole fraction, atom count in cation, methyl group count in cation, atom count in anion, hydrogen atom count in anion of ionic liquid and atom count in ketone. Total experimental data points of 2517 for density and 947 for speed of sound were used to train the algorithm and to test the network obtained. The optimum neural network structure determined for density and speed of sound of binary ionic liquid and ketone mixtures were 7-9-9-1 and 7-7-4-1 respectively; overall average percentage error of 2.45% and 2.17% respectively; and mean absolute error of 28.21 kg/m3 and 33.91 m/s respectively. The said algorithm was found applicable for the prediction of density and speed of sound of binary ionic liquid and ketone mixtures.

scholarly journals Towards the Correct Measurement of Thermal Conductivity of Ionic Melts and Nanofluids

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 99 ◽  
Author(s):  
Carlos A. Nieto de Castro ◽  
Maria José V. Lourenço
Keyword(s):  
Thermal Conductivity ◽  
Ionic Liquids ◽  
Molten Salts ◽  
Alternative Fuels ◽  
The United States ◽  
Design Parameters ◽  
Physical Situation ◽  
The Sustainable Development ◽  
Best Available Techniques ◽  
Energy Field

Thermophysical properties of engineering fluids have proven in the past to be essential for the design of physical and chemical processing and reaction equipment in the chemical, metallurgical, and allied industries, as they influence directly the design parameters and performance of plant units in the of, for example, heat exchangers, distillation columns, phase separation, and reactors. In the energy field, the search for the optimization of existing and alternative fuels, either using neutral or ionic fluids, is an actual research and application topic, both for new applications and the sustainable development of old technologies. One of the most important drawbacks in the industrial use of thermophysical property data is the common discrepancies in available data, measured with different methods, different samples, and questionable quality assessment. Measuring accurately the thermal conductivity of fluids has been a very successful task since the late 1970s due to the efforts of several schools in Europe, Japan, and the United States. However, the application of the most accurate techniques to several systems with technological importance, like ionic liquids, nanofluids, and molten salts, has not been made in the last ten years in a correct fashion, generating highly inaccurate data, which do not reflect the real physical situation. It is the purpose of this paper to review critically the best available techniques for the measurement of thermal conductivity of fluids, with special emphasis on transient methods and their application to ionic liquids, nanofluids, and molten salts.

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