MACROSTRUCTURE OF AQUEOUS SOLUTIONS OF ETHANOL AND ITS IMPLICATIONS

Józef Mazurkiewicz¹, Hanna M. Baranowska², Michał Wojtasik³, Piotr Tomasik^4
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 Nantes Nanotechnological Systems, Bolesławiec, Poland

ABSTRACT

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.

INTRODUCTION

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”.

MATERIAL AND METHODS

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

(1)

with M_z(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

(2)

with M_x,y and M₀ being echo – spin amplitude recorded in the TE period and equilibrium magnetisation, respectively, and p_i represents a proton fraction which cross-relaxated with the relaxation time, T_2i.

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.

RESULTS AND DISCUSSION

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

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.

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.

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 tau_c, associated with the rotation of a molecule possessing a magnetic momentum.

(3)

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

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

(4)

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

(5)

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.

Minimum distance between solvent and solute atoms was 2.3Å.

Using equation 6 [14]

c_ri = 0.0024x_i³ – 0.5805x_i²+ 16.493x_i + 4174.2     (6)

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

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.

CONCLUSIONS

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.

REFERENCES

1. Carr H.Y., Purcell E.M., 1954. Effects of diffusion on free precession in nuclear magnetic resonance experiments. Phys. Rev. 94, 630-638.

2. Ferry A.-L., Hort, J., Mitchell J.R., Valles Pamies B., Lagarrigue S., 2006. Viscosity and flavour perception. Why is starch different from hydrocolloids. Food Hydrocoll. 20, 855-862.

3. Fukushima E., Roeder S.B.W., 1981. Experimental Pulse NMR. A Nuts and Bolts Approach. London, Addison-Wesley Publishing Company.

4. Hennel J.W., Klinowski J., 1993. Fundamentals of nuclear magnetic resonance. Harlow, Longman Scientific and Technical.

5. Hill M.A., Mitchell J.R., Sherman P., 1996. The relationship between the rheological and sensory properties of a lemon pie filling. J Text. Stud. 26, 457-470.

6. Kokini J.L., Kadane J.B., Cussler E.L., 1977. Liquid texture perceived in the mouth. J. Text. Stud. 8, 195-218.

7. Lai V.M.-F., Lii, C.Y., 2004. Role of saccharides in texturization and functional properties of foodstuffs. [in] P. Tomasik (Ed.), Chemical and functional properties of food saccharide. Boca Raton, CRC Press, 159-179.

8. Mazurkiewicz J., Tomasik P., 1990. Viscosimetric studies of aqueous and nonaqueous binary mixtures. J. Phys. Org. Chem. 3, 493-502.

9. Mazurkiewicz J., Tomasik P., 1996. Perestroika effect. A novel example of electroviscosity. Bull. Chem. Soc. Belg. 105, 173-180.

10. Meiboom S., Gill D., 1958. Modified spin-echo method for measuring nuclear relaxation times. Rev. Sci. Instr. 29, 688-691.

11. Pokhlebkin V.V., 1991. History of vodka, Moscow, Inter-Verso [in Russian].

12. Steffe J.M., 1996. Rheological methods in food process engineering. East Lansing, MI, USA Freeman Press, 2nd ed.

13. Szczesniak A., Farkas E., 1962. Objective characterization of the mouthfeel of gum solutions. J. Food Sci. 27, 381-385.

14. Timmermans J., 1960. The Physico-chemical Constants of Binary Systems of Concentrated Solutions. Vol. 4, p. 205, Interscience Publishers, New York.

15. Węglarz W.P., Harańczyk H., 2000. Two-dimensional analysis of the nuclear relaxation function in the time domain: The CracSpin program. J. Phys. D, Appl. Phys. 33, 1909-1920.

16. Wensink E.J.W., Hoffmann A.C., Van Maaren P.J., van der Spoel D., 2003. Dynamic properties of water/alcohol mixtures studied by computer simulation. J. Chem. Phys. 119, 7308-7317.

Accepted for print: 13.04.2007

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