scholarly journals Bubble-Point Measurements ofn-Propane +n-Decane Binary Mixtures with Comparisons of Binary Mixture Interaction Parameters for Linear Alkanes

2016 ◽  
Vol 61 (7) ◽  
pp. 2573-2579 ◽  
Author(s):  
Elisabeth Mansfield ◽  
Ian H. Bell ◽  
Stephanie L. Outcalt
Keyword(s):  
Binary Mixture ◽  
Binary Mixtures ◽  
Interaction Parameters ◽  
Bubble Point ◽  
Linear Alkanes

scholarly journals Perception of Aqueous Ethanol Binary Mixtures Containing Alcohol-Relevant Taste and Chemesthetic Stimuli

Beverages ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 23
Author(s):  
Margaret Thibodeau ◽  
Gary Pickering
Keyword(s):  
Binary Mixture ◽  
Binary Mixtures ◽  
Aqueous Ethanol ◽  
Ethanol Concentration ◽  
Alcoholic Beverages ◽  
Complex Stimulus ◽  
Aluminium Sulphate ◽  
Binary Solutions ◽  
Wide Range ◽  
Thermal Taste

Ethanol is a complex stimulus that elicits multiple gustatory and chemesthetic sensations. Alcoholic beverages also contain other tastants that impact flavour. Here, we sought to characterize the binary interactions between ethanol and four stimuli representing the dominant orosensations elicited in alcoholic beverages: fructose (sweet), quinine (bitter), tartaric acid (sour) and aluminium sulphate (astringent). Female participants were screened for thermal taste status to determine whether the heightened orosensory responsiveness of thermal tasters (n = 21–22) compared to thermal non-tasters (n = 13–15) extends to these binary mixtures. Participants rated the intensity of five orosensations in binary solutions of ethanol (5%, 13%, 23%) and a tastant (low, medium, high). For each tastant, 3-way ANOVAs determined which factors impacted orosensory ratings. Burning/tingling increased as ethanol concentration increased in all four binary mixture types and was not impacted by the concentration of other stimuli. In contrast, bitterness increased with ethanol concentration, and decreased with increasing fructose concentration. Sourness tended to be reduced as ethanol concentration increased, although astringency intensity decreased with increasing concentration of fructose. Overall, thermal tasters tended to be more responsive than thermal non-tasters. These results provide insights into how the taste and chemesthetic profiles of alcoholic beverages across a wide range of ethanol concentrations can be manipulated by changing their composition.

scholarly journals Practical data correlation of flashpoints of binary mixtures by a reciprocal function: The concept and numerical examples

2011 ◽  
Vol 15 (3) ◽  
pp. 905-910 ◽  
Author(s):  
Mariana Hristova ◽  
Dimitar Damgaliev ◽  
Jordan Hristov
Keyword(s):  
Binary Mixture ◽  
Binary Mixtures ◽  
Alcohol Solution ◽  
Aqueous Alcohol ◽  
Thermodynamic Models ◽  
Data Correlation ◽  
Numerical Examples ◽  
Aqueous Alcohol Solution ◽  
Better Than

Simple data correlation of flashpoint data of binary mixture has been developed on a basic of rational reciprocal function. The new approximation requires has only two coefficients and needs the flashpoint temperature of the pure flammable component to be known. The approximation has been tested by literature data concerning aqueous-alcohol solution and compared to calculations performed by several thermodynamic models predicting flashpoint temperatures. The suggested approximation provides accuracy comparable and to some extent better than that of the thermodynamic methods.

Bubble-Point Measurements of n-Butane + n-Octane and n-Butane + n-Nonane Binary Mixtures

2015 ◽  
Vol 60 (8) ◽  
pp. 2447-2453 ◽  
Author(s):  
Elisabeth Mansfield ◽  
Stephanie L. Outcalt
Keyword(s):  
Binary Mixtures ◽  
Bubble Point

Highly Efficient and Accurate Gas-Alkane Binary Mixture Interfacial Tension Equations for a Broad Range of Temperatures, Pressures, and Compositions

SPE Journal ◽  
2021 ◽  
pp. 1-19
Author(s):  
Yingnan Wang ◽  
Nadia Shardt ◽  
Janet A. W. Elliott ◽  
Zhehui Jin
Keyword(s):  
Experimental Data ◽  
Binary Mixture ◽  
Interfacial Tension ◽  
Binary Mixtures ◽  
Oil Recovery ◽  
Computational Cost ◽  
Petroleum Engineering ◽  
Pure Species ◽  
Highly Efficient ◽  
Wide Range

Summary Gas-alkane interfacial tension (IFT) is an important parameter in the enhanced oil recovery (EOR) process. Thus, it is imperative to obtain an accurate gas-alkane mixture IFT for both chemical and petroleum engineering applications. Various empirical correlations have been developed in the past several decades. Although these models are often easy to implement, their accuracy is inconsistent over a wide range of temperatures, pressures, and compositions. Although statistical mechanics-based models and molecular simulations can accurately predict gas-alkane IFT, they usually come with an extensive computational cost. The Shardt-Elliott (SE) model is a highly accurate IFT model that for subcritical fluids is analytic in terms of temperature T and composition x. In applications, it is desirable to obtain IFT in terms of temperature T and pressure P, which requires time-consuming flash calculations, and for mixtures that contain a gas component greater than its pure species critical point, additional critical composition calculations are required. In this work, the SE model is combined with a machine learning (ML) approach to obtain highly efficient and highly accurate gas-alkane binary mixture IFT equations directly in terms of temperature, pressure, and alkane molar weights. The SE model is used to build an IFT database (more than 36,000 points) for ML training to obtain IFT equations. The ML-based IFT equations are evaluated in comparison with the available experimental data (888 points) and with the SE model, as well as with the less accurate parachor model. Overall, the ML-based IFT equations show excellent agreement with experimental data for gas-alkane binary mixtures over a wide range of T and P, and they outperform the widely used parachor model. The developed highly efficient and highly accurate IFT functions can serve as a basis for modeling gas-alkane binary mixtures for a broad range of T, P, and x.

scholarly journals Mixing and demixing of binary mixtures of polar chiral active particles

Soft Matter ◽  
2018 ◽  
Vol 14 (21) ◽  
pp. 4388-4395 ◽  
Author(s):  
Bao-quan Ai ◽  
Zhi-gang Shao ◽  
Wei-rong Zhong
Keyword(s):  
Binary Mixture ◽  
Boundary Conditions ◽  
Binary Mixtures ◽  
Periodic Boundary ◽  
Periodic Boundary Conditions ◽  
Two Dimensional ◽  
Active Particles

We study a binary mixture of polar chiral (counterclockwise or clockwise) active particles in a two-dimensional box with periodic boundary conditions.

scholarly journals Transport properties and intermolecular interactions in binary mixtures based on the protic ionic liquid ethylimidazolium triflate and ethylene glycol

2018 ◽  
Vol 20 (35) ◽  
pp. 22980-22986 ◽  
Author(s):  
Negin Yaghini ◽  
Iqbaal Abdurrokhman ◽  
Mohammad Hasani ◽  
Anna Martinelli
Keyword(s):  
Ionic Liquid ◽  
Binary Mixture ◽  
Ethylene Glycol ◽  
Transport Properties ◽  
Binary Mixtures ◽  
Intermolecular Interactions ◽  
Composition Range ◽  
Protic Ionic Liquid

The binary mixture based on the protic ionic liquid (PIL) ethylimidazolium triflate (C2HImTfO) and the diol compound ethylene glycol (EG) has been investigated in the whole composition range from pure PIL to pure EG.

scholarly journals Mixing Characteristics of Binary Mixture with Biomass in a Gas-Solid Rectangular Fluidized Bed

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 2011
Author(s):  
Guiying Wu ◽  
Bangting Yu ◽  
Yanjun Guan ◽  
Xuehui Wu ◽  
Kai Zhang ◽  
...  
Keyword(s):  
Binary Mixture ◽  
Fluidized Bed ◽  
Binary Mixtures ◽  
Silica Sand ◽  
Mixture Composition ◽  
Inert Material ◽  
Gas Velocity ◽  
Mixing Characteristics ◽  
Superficial Gas Velocity ◽  
Initial Packing

Aiming to better understand the biomass pyrolysis and gasification processes, a detailed experimental study of the mixing characteristics is conducted in a fluidized bed with binary mixtures. Rapeseed is used as biomass, and silica sand or resin as inert material. The effect of mixture composition, initial packing manner, and superficial gas velocity on the concentration distribution is investigated in a rectangular fluidized bed by means of photography and sampling methods. The results show that the mixture composition plays an important role in the axial solids profile of binary mixtures. The mixing behavior of binary mixture is dominated by the bubble movement. The axial distribution of binary mixtures becomes uniform with increasing superficial gas velocity, whilst no obvious effect of initial packing manner is observed in this study.

scholarly journals Odourant dominance in olfactory mixture processing: what makes a strong odourant?

2015 ◽  
Vol 282 (1802) ◽  
pp. 20142562 ◽  
Author(s):  
Marco Schubert ◽  
Jean-Christophe Sandoz ◽  
Giovanni Galizia ◽  
Martin Giurfa
Keyword(s):  
Nervous System ◽  
Binary Mixture ◽  
Binary Mixtures ◽  
Neural Activity ◽  
The Other ◽  
Insect Nervous System ◽  
Learning Success ◽  
Widespread Phenomenon ◽  
Central Level

The question of how animals process stimulus mixtures remains controversial as opposing views propose that mixtures are processed analytically, as the sum of their elements, or holistically, as unique entities different from their elements. Overshadowing is a widespread phenomenon that can help decide between these alternatives. In overshadowing, an individual trained with a binary mixture learns one element better at the expense of the other. Although element salience (learning success) has been suggested as a main explanation for overshadowing, the mechanisms underlying this phenomenon remain unclear. We studied olfactory overshadowing in honeybees to uncover the mechanisms underlying olfactory-mixture processing. We provide, to our knowledge, the most comprehensive dataset on overshadowing to date based on 90 experimental groups involving more than 2700 bees trained either with six odourants or with their resulting 15 binary mixtures. We found that bees process olfactory mixtures analytically and that salience alone cannot predict overshadowing. After normalizing learning success, we found that an unexpected feature, the generalization profile of an odourant, was determinant for overshadowing. Odourants that induced less generalization enhanced their distinctiveness and became dominant in the mixture. Our study thus uncovers features that determine odourant dominance within olfactory mixtures and allows the referring of this phenomenon to differences in neural activity both at the receptor and the central level in the insect nervous system.

scholarly journals Measurement and prediction of binary mixture flash point

2013 ◽  
Vol 11 (1) ◽  
pp. 57-62 ◽  
Author(s):  
Mariana Hristova
Keyword(s):  
Experimental Data ◽  
Binary Mixture ◽  
Binary Mixtures ◽  
Qualitative Agreement ◽  
Flash Point ◽  
Wilson Equation ◽  
Good Qualitative Agreement ◽  
Raoult’S Law ◽  
Raoult's Law

AbstractThe flash points of three binary mixtures, containing n-heptane, o-xylene, m-xylene and ethylbenzene, were measured by Pensky-Martens closed cup tester. The experimental data were compared with the calculated values using Liaw’s Model with the application of Raoult’s Law and Wilson equation. These equations were in good qualitative agreement.

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