scholarly journals Influence of Tableting on Enzymatic Activity of Papain along with Determination of Its Percolation Threshold with Microcrystalline Cellulose

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Manu Sharma ◽  
Vinay Sharma ◽  
Dipak K. Majumdar
Keyword(s):  
Enzyme Activity ◽  
Binary Mixture ◽  
Percolation Threshold ◽  
Binary Mixtures ◽  
Microcrystalline Cellulose ◽  
Critical Density ◽  
Stability Study ◽  
Mixture Composition ◽  
Brittle Behavior ◽  
Robust Formulation

The binary mixture tablets of papain and microcrystalline cellulose (MCC), dicalcium phosphate dihydrate (DCP), carrageenan, tragacanth, and agar were prepared by direct compression. Carrageenan, tragacanth, and agar provided maximum protection to enzyme activity compared to MCC and DCP. However, stability studies indicated highest loss of enzyme activity with carrageenan, tragacanth, and agar. Therefore, compression behaviour of different binary mixtures of papain with MCC at different compaction pressures, that is, 40–280 MPa, was studied according to Heckel equation. The compressibility studies of binary mixtures indicated brittle behavior of papain. The application of percolation theory on the relationship between critical density as a function of enzyme activity and mixture composition revealed the presence of percolation threshold for binary mixture. Papain-MCC mixture composition showed significant percolation threshold at 18.48% (w/w) papain loading. Microcrystalline cellulose provided higher protection during stability study. However, higher concentrations of microcrystalline cellulose, probably as dominant particles, do not protect the enzyme with their plastic deformation. Below the percolation threshold, that is, 18.48% (w/w) papain amount in mixture with plastic excipient, activity loss increases strongly because of higher shearing forces during compaction due to system dominance of plastic particles. This mixture range should therefore be avoided to get robust formulation of papain.

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 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.

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.

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