Electronic Journal of Polish Agricultural Universities (EJPAU) founded by all Polish Agriculture Universities presents original papers and review articles relevant to all aspects of agricultural sciences. It is target for persons working both in science and industry,regulatory agencies or teaching in agricultural sector. Covered by IFIS Publishing (Food Science and Technology Abstracts), ELSEVIER Science - Food Science and Technology Program, CAS USA (Chemical Abstracts), CABI Publishing UK and ALPSP (Association of Learned and Professional Society Publisher - full membership). Presented in the Master List of Thomson ISI.
Volume 10
Issue 2
Agricultural Engineering
Mazurkiewicz J. , Baranowska H. , Wojtasik M. , Tomasik P. 2007. MACROSTRUCTURE OF AQUEOUS SOLUTIONS OF ETHANOL AND ITS IMPLICATIONS, EJPAU 10(2), #17.
Available Online: http://www.ejpau.media.pl/volume10/issue2/art-17.html


Józef Mazurkiewicz1, Hanna M. Baranowska2, Michał Wojtasik3, Piotr Tomasik4
1 Department of Physics, University of Agriculture in Cracow, Poland
2 Department of Physics, University of Life Sciences in Poznań, Poland
3 Institute of Petroleum Technology, Cracow, Poland
4 Department of Chemistry, University of Agriculture in Cracow, Poland



Viscosity of aqueous solutions of ethanol changes non-linearly with concentration. There is a maximum viscosity of solution containing about 47 volume% ethanol. 1H NMR spin – lattice and spin – spin relaxation times of such solutions also change with concentration showing minimum at closely the same ethanol concentration. These results rationalized in terms of Einstein – Debye theory point to the link between the relaxation time and viscosity of solution and the latter with ordering of the components in solution. The MM+ Monte Carlo approach (HyperChem 7.0 software) indicated a maximum potential energy of the water – ethanol system at the same concentration of the solution. According to the mouthfeel theory, substances of ordered structure generate superior mouthfeel. That finding may, eventually, explain why commercial vodka has preferably about 45 volume% concentration. The approach might have more universal significance in determination of mouthfeel of various soft drinks, beverages, and other liquids.

Key words: alcohol, mouthfeel, relaxation time, solution dynamic structure, viscosity, vodka.


Extended studies [9] of the changes in viscosity, etha of aqueous binary mixtures of a series organic solvents commonly demonstrated a maxima on a bell-shaped etha- composition curves. For binary cyclohexane and alcohol blends with organic solvents corresponding curves either did not appear or they had a broad, shallow minimum. These results indicated diverse state of ordering of the solution macrostructure.

Based on the mouthfeel theory [2, 5, 6, 7, 13], taste is associated with a macrostructure of the substance generating that sensory impression. Thus, one might assume that more viscous liquids, that is, these with more ordered solution macrostructure might exhibit better taste. It implies, that superior mouthfeel of liquid blends could be non-linearly dependent on concentration. Vodka, seems to be an example for such liquid.

Commercial vodka, a common beverage in Central, East, and North Europe contains from 35 to 50 volume% ethanol. The classic vodka is 40% (80 proof) aqueous ethanol. Mendeleev, the Russian chemist from XIX century found that taste of vodka of the 38 volume% concentration was superior. Perhaps, because of taxes put that time on alcohol, its standard concentration was lifted to 40 volume% providing a simplicity of the tax computation [11]. As the ethanol concentration increases, taste of vodka changes from “watery” to “burning”.


Materials. 96% ethanol, analytical grade was purchased from POCh Gliwice, Poland. Water was redistilled.

Viscometric measurements. Measurements for aqueous solutions of ethanol in the concentration ranging from 0 to 96% by volume of ethanol were carried out at 20°±0.05°C with a fully computerised Zimm-Crothers rotary viscometer [8].

Relaxation time measurements. Relaxation spin-lattice, T1, and spin-spin, T2, times were recorded at 20°±1°C with 1H NMR pulse spectrometer NMR (WLElectronic-Poland) operating at 30 MHz. Samples (0.8 mL) of water, ethanol and their blends were packed into measured tubes closed with parafilm. A sequence of inversion – recovery impulses 180x-TI-90x-TR [3] was utilized in recording T1. Distance between TI impulses changed from 25 to 3300 ms, with the repetition time TR of 35 s. During recording T1, 32 signals of free induction decay, FID, and 110 points at each FID were collected. T1-values were computed with a CracSpin [15] software. Eq. (1) was used for describing magnetisation recovery


with Mz(TI) and M0 being a current and equilibrium magnetisation, respectively.

A sequence of CPMG impulses 90x-(TE/2-180y-TE)n [1, 10] was applied on recording T2. Distance between each spin echo, TE, was 5 ms at 100 amplitudes regularly collected throughout experiments. At the repetition time, TR, of 35 s, 3 signal accumulations were performed. Eq. (2) was applied for description of a decay of echo – spin amplitudes


with Mx,y and M0 being echo – spin amplitude recorded in the TE period and equilibrium magnetisation, respectively, and pi represents a proton fraction which cross-relaxated with the relaxation time, T2i.

Computations. Model for computations was arranged in the following manner. In consecutive calculations, a theoretical 20×20×20Å cells filled with 0, 10, 20, 30, 40, and 50 ethanol molecules. Water molecules were added to those cells to fill these cells completely. The MM+ Monte Carlo approach was applied (HyperChem 7.0 software). The total number of molecules in the cells varied from 265 in case of pure water up to 153 in case of the most concentrated, 33.3 mole/mole% aqueous ethanol. There were 500 calculating steps. In such manner, an average potential energy became available for the systems under study. Computations were performed with two-processor 2.5 GHZ computer.


Figure 1 presents changes in viscosity of aqueous ethanol solutions with changes of the composition of those solutions expressed in volume%.

Fig. 1. Relationship of the viscosity of aqueous solutions of ethanol on concentration of those solutions expressed in vol. %

It is common [12] that viscosity of solutions is associated with the state of ordering of the macrostructure of solution. Increase in the viscosity usually corresponds to ordering that macrostructure. Thus, approximately 47 volume% ethanol seems to have the most ordered macrostructure. The ordering could result either from an aggregation of ethanol hydrates or an increase in the density of that solution caused by possibly most perfect filling cavities of aqueous clathrate with ethanol molecules.

1H NMR relaxation times, T1 and T2, measurements nicely confirmed their nonlinear changes with the concentration of ethanol in solution. Monoexponential magnetisation recovery was found in each analysed sample what meant that the system relaxation proceeded with one longitudinal relaxation time involved. In water as the control sample, only one transverse -relaxation time was recorded whereas in aqueous ethanol solution two cross-relaxation times were observed.

Figure 2 presents changes of T1 with concentration of ethanol in the solution.

Fig. 2. Changes of T1 with concentration if ethanol in aqueous solution

The minimum of T1 located at 0.45 g/g ethanol well fitted concentration at which viscosity maximum was found (Fig. 1). Changes of T1 could point to a microscopic ordering of the structure of the solution.

T1 reflected the time required for the recovery equilibrium of the system after it was excited with an impulse of the magnetic field of variable frequency. The recovery was possible through passing excessive energy to the lattice. Observed changes of T1 should be associated with changes in their viscosity. Transitions between particular energetic states were forced by fluctuations of a local magnetic field resulting from modes of molecules possessing magnetic spin. Increase in viscosity accelerated strained relaxation transitions on the microscopic level. An increase in the viscosity fluctuation minimum of the local magnetic field was shifted towards lower frequency. When the fluctuation frequency of the local magnetic field was lower than the resonance frequency, straining of the spin – lattice transitions was gradually weakened resulting in a decrease in the relaxation rate, that is, in an increase of the spin – lattice relaxation time.

In the system under study, protons resided in the water molecules, the alcohol hydroxyl groups as well as in the methyl and methylene groups of ethanol. Because of the increase in the dipole intra- and inter-molecular interactions, T1 decreased as the concentration of ethanol increased. It was likely that interactions of the protons of the water molecules with the protons of the hydroxyl groups of ethanol predominated. An increase in T1 above the 0.45 g/g concentration of ethanol pointed to a domination of the intramolecular dipol interactions. In that system, increase in the number of the methyl and methylene groups was accompanied with decrease in the content of the water molecules.

The spin – spin relaxation offered another way of the transfer of excessive energy absorbed. Changes of T2 with the ethanol concentration in the solutions are presented in Figure 3.

Table 1 provides relaxation time values, T1 and T2 recorded in aqueous solutions of ethanol.

Fig. 3. Changes of T2 with concentration of ethanol in aqueous solutions. Solid and broken lines present changes of short, T21 and long T22 components of the spin-spin relaxation time T2, respectively

Table 1. Relaxation times T1 and T2 recorded in aqueous solutions of ethanol

c [g/g]

T1 [ms]

T21 [ms]

T22 [ms]


2320 ± 9

1667 ± 4

1670 ± 4


1817 ± 9

998 ± 7

1350 ± 10


1433 ± 4

544 ± 15

1158 ± 30


1312 ± 6

115 ± 18

819 ± 36


1237 ± 6

57 ± 10

567 ± 25


1207 ± 4

27 ± 5

437 ± 15


1262 ± 5

40 ± 4

472 ± 8


1326 ± 6

42 ± 4

490 ± 9


1431 ± 6

48 ± 3

480 ± 7


1526 ± 5

82 ± 3

661 ± 7


1552 ± 6

64 ± 4

720 ± 9


1755 ± 3

97 ± 4

846 ± 8

Both curves exhibited minimum localized in the sector between 0.45 and 0.50 g/g, that is, in the same sector in which minimum of T1 appeared. As the viscosity of solutions increased, the rate of the spin – spin relaxation increased, that is, the time of that relaxation decreased.

Presence of two components of T2 suggested scalar and dipol interactions between components of the solutions. Observed two spin – spin relaxation times are, perhaps, associated with concentration dependent interactions of the protons of the water molecules with the protons of the hydroxyl group of ethanol (T22) and with, almost independent of concentration, interactions of the water molecule proton with the protons of the methyl and methylene groups of ethanol (T21).

Viscosity parameters which are macroscopic parameters of solution could be compared with spin – lattice relaxation time. The latter are microscopic parameters in frames of the Einstein – Debye theory [4] assuming proportionality (Eq. 3) between viscosity of the medium etha and the correlation time tauc, associated with the rotation of a molecule possessing a magnetic momentum.


where a, k, and T are: a radius of rotating molecule, Boltzmann constant and temperature in kelvins, respectively.

When tauc<<1 Eq. (4) is followed:


However, when tauc>>1, Eq. (5) is valid


where b, , gamma and omega are: distance between interacting spins, Planck constant divided by 2pi magnetogiric factor specific for a given nucleus, and a constant, respectively.

Thus, changes of the relaxation times could be related to changes in the correlation time of the rotation of molecule. The latter were dependent on ordering of the structure of solutions. Collected results verify results of computer simulations of dynamic properties of aqueous ethanol solutions by van der Spoel et al. [16].

Simulation performed with involvement of the Monte Carlo approach, provided maximum potential energy of the water – ethanol system at the concentration of approximately 20 mole% ethanol (Fig. 4) what corresponded to formerly estimated concentration in volume% providing maximum viscosity of the solution.

Fig. 4. Average potential energy depending on the composition of aqueous ethanol expressed in mole%. Simulation performed with Monte Carlo (HyperChem 7.0, at 400 run steps

Minimum distance between solvent and solute atoms was 2.3Å.

Using equation 6 [14]

cri = 0.0024xi3 – 0.5805xi2+ 16.493xi + 4174.2     (6)

where xi was mole% of ethanol in water, composition dependent specific heat of the aqueous solution of aqueous ethanol, cri, was found. Also in that case maximum was observed at the same concentration (Fig. 5).

Fig. 5. Specific heat of aqueous ethanol depending on composition of the solution expressed in mole%

The maximum of specific heat at that composition provided an evidence for the formation in solution of higher molecular weight aggregates in solution and/or higher number of degree of freedom.

Since an increase in the structure ordering provides a higher mouthfeel satisfaction, about 45 v/v% (22 mole/mole%) aqueous solutions of ethanol with its most ordered structure could offer a superior mouthfeel. The approach presented above might have more universal significance in determination of mouthfeel of various soft drinks, beverages and other liquids.

The approach might be suitable for monitoring relevant parameters which may govern mouthfeel of liquids. Potentially, it provides a possibility of tailoring mouthfeel by computation.


As shown by thorough rheological and proton magnetic resonance studies, about 45 v/v% (22 mole/mole%) aqueous solutions of ethanol with its most ordered structure can offer a superior mouthfeel.


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Accepted for print: 13.04.2007

Józef Mazurkiewicz
Department of Physics,
University of Agriculture in Cracow, Poland
Mickiewicz Ave. 31-120 Cracow, Poland

Hanna M. Baranowska
Department of Physics,
University of Life Sciences in Poznań, Poland
Wojska Polskiego Street 38/42, 60-637 Poznań, Poland

Michał Wojtasik
Institute of Petroleum Technology, Cracow, Poland
Łukasiewicza Street 1, 31-429 Cracow, Poland

Piotr Tomasik
Department of Chemistry,
University of Agriculture in Cracow, Poland
Balicka Street 121, 30-149 Cracow, Poland
phone/fax: (+48 12) 662 43 35
email: rrtomasi@cyf-kr.edu.pl

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