Density, Kinematic Viscosity, Speed of Sound, and Surface Tension of Hexyl, Octyl, and Decyl Trimethyl Ammonium Bromide Aqueous Solutions

2007 ◽  
Vol 52 (3) ◽  
pp. 889-891 ◽  
Author(s):  
Diego Gómez-Díaz ◽  
José M. Navaza ◽  
Begoña Sanjurjo
Keyword(s):  
Surface Tension ◽  
Aqueous Solutions ◽  
Speed Of Sound ◽  
Kinematic Viscosity ◽  
Ammonium Bromide

scholarly journals Modeling the Behavior of Amphiphilic Aqueous Solutions

2021 ◽  
Author(s):  
Gonzalo Astray Dopazo ◽  
Cecilia Martínez-Castillo ◽  
Manuel Alonso-Ferrer ◽  
Juan Carlos Mejuto
Keyword(s):  
Experimental Data ◽  
Molecular Weight ◽  
Aqueous Solutions ◽  
Predictive Models ◽  
Kinematic Viscosity ◽  
Ammonium Bromide ◽  
Quadratic Regression ◽  
Neural Models ◽  
Prediction Tools

Two types of predictive models based on artificial neural networks (ANN) and quadratic regression model developed in our laboratory will be summarized in this book chapter. Both models were developed to predict the density, speed of sound, kinematic viscosity and surface tension of amphiphilic aqueous solutions. These models were developed taking into account the concentration, the number of carbons and the molecular weight values. The experimental data were compiled from literature and included different surfactants: i) hexyl, ii) octyl, iii) decyl, iv) tetradecyl and v) octadecyl trimethyl ammonium bromide. Neural models present better adjustment values, with R2 values above 0.902 and AAPD values under 2.93% (for all data), than the quadratic regression models. Finally, it is concluded that the quadratic regression and the neural models can be powerful prediction tools for the physical properties of surfactants aqueous solutions.

Density, Speed of Sound, Surface Tension, and Electrical Conductivity of Sodium Dodecanoate Aqueous Solutions fromT= (293.15 to 323.15) K

2010 ◽  
Vol 55 (9) ◽  
pp. 4058-4061 ◽  
Author(s):  
E. Álvarez-Silva ◽  
A. García-Abuín ◽  
D. Gómez-Díaz ◽  
J. M. Navaza ◽  
I. Vidal-Tato
Keyword(s):  
Electrical Conductivity ◽  
Surface Tension ◽  
Aqueous Solutions ◽  
Speed Of Sound

scholarly journals Surface Thermodynamics, Viscosity, Activation Energy of N-Methyldiethanolamine Aqueous Solutions Promoted by Tetramethylammonium Arginate

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1337
Author(s):  
Xiangfeng Tian ◽  
Lemeng Wang ◽  
Pan Zhang ◽  
Dong Fu
Keyword(s):  
Activation Energy ◽  
Surface Tension ◽  
Diffusion Coefficient ◽  
Aqueous Solutions ◽  
Quantitative Relationship ◽  
Viscosity Data ◽  
Surface Thermodynamics ◽  
Surface Entropy ◽  
Operation Conditions ◽  
Surface Enthalpy

The surface tension and viscosity values of N-methyldiethanolamine (MDEA) aqueous solutions promoted by tetramethylammonium arginate ([N1111][Arg]) were measured and modeled. The experimental temperatures were 303.2 to 323.2 K. The mass fractions of MDEA (wMDEA) and [N1111][Arg] (w[N1111][Arg]) were 0.300 to 0.500 and 0.025 to 0.075, respectively. The measured surface tension and viscosity values were satisfactorily fitted to thermodynamic models. With the aid of experimentally viscosity data, the activation energy (Ea) and H2S diffusion coefficient (DH2S) of MDEA-[N1111][Arg] aqueous solution were deduced. The surface entropy and surface enthalpy of the solutions were calculated using the fitted model of the surface tension. The quantitative relationship between the calculated values (surface tension, surface entropy, surface enthalpy, viscosity, activation energy, and H2S diffusion coefficient) and the operation conditions (mass fraction and temperature) was demonstrated.

scholarly journals Spray adjuvant characteristics affecting agricultural spraying drift

2015 ◽  
Vol 35 (1) ◽  
pp. 109-116 ◽  
Author(s):  
RONE B. DE OLIVEIRA ◽  
ULISSES R. ANTUNIASSI ◽  
MARCO A. GANDOLFO
Keyword(s):  
Surface Tension ◽  
Wind Tunnel ◽  
Aqueous Solutions ◽  
Formation Process ◽  
Droplet Diameter ◽  
Brilliant Blue ◽  
Medium Size ◽  
Blue Dye ◽  
Methods Of Evaluation ◽  
Spray Adjuvants

This study defined the main adjuvant characteristics that may influence or help to understand drift formation process in the agricultural spraying. It was evaluated 33 aqueous solutions from combinations of various adjuvants and concentrations. Then, drifting was quantified by means of wind tunnel; and variables such as percentage of droplets smaller than 50 μm (V50), 100 μm (V100), diameter of mean volume (DMV), droplet diameter composing 10% of the sprayed volume (DV0.1), viscosity, density and surface tension. Assays were performed in triplicate, using Teejet XR8003 flat fan nozzles at 200 kPa (medium size droplets). Spray solutions were stained with Brilliant Blue Dye at 0.6% (m/ v). DMV, V100, viscosity cause most influence on drift hazardous. Adjuvant characteristics and respective methods of evaluation have applicability in drift risk by agricultural spray adjuvants.

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