In this section we briefly report on the results of two most important findings of this thesis, namely excess permittivity and imaginary excess permittivity.
6.4.1 Excess permittivity
The refractive index values for samples A, B and C (both authentic and adulterated) are presented in Table 1 (chapter 4). These values were utilized for calculating the excess permittivity using Eqs. (3.15) and (3.16). The results for excess permittivity are presented in Table 4.
Table 4: Excess permittivity of adulterated fuel samples A-C.
Sample Volume fraction
Of Kerosene
Excess permittivity (10-3)
A 5% -0.30
10% 2.63
15% 2.06
B 5% 4.25
10% 4.13
15% 2.83
C 5% 3.14
10% 3.17
15% 3.20
From (Table 4) the magnitude of excess permittivity (at 589 nm) for all the samples is small, this implies the existence of less chemical interactions. There is negative sign in the value of excess permittivity for sample A which is very different from all the other samples. Moreover, there is a unique behaviour regarding the value for sample A, namely 10% sample has highest value of excess permittivity in comparison to the values for 5% and 15%. (Paper III) This seemingly strange behaviour agrees with the behaviour of the time dependent back scattered signal measured by the new meas-urement mode of the prototype in (Paper I). The dynamic signal behaviour depicted in (section 6.1) shows a rather constant signal for 10% contrary to the plateau type signal of 5% and 15%. For the case of samples B and C only positive values for excess permittivity are observed. The values for sample B are interesting, namely 5% sample has the highest value while 15% has the lowest value, moreover, the values for 5%
43 and 10% are almost same whereas the value for 15% is very low. On the other hand, sample C has constant excess permittivity value, this might partly be due to the close-ness of its refractive index value with that of kerosene. Therefore, it is difficult to differentiate adulterated samples originating from sample C based on the single point (589 nm) excess permittivity value.
The wavelength dependent excess permittivity is important for exploring the op-tical behavior of different authentic and adulterated samples across a broader Vis-NIR spectral range. For this purpose, sample C is considered because according to Table 4 it is the most difficult case which gives almost constant value for different adulteration percentages. The wavelength dependent extinction coefficient was cal-culated using Eqs. (3.9) and (3.11). The results were utilized for calculating the wave-length dependent refractive index using Eqs. (3.12) and (3.13), transmittance values from Figs. 4.1 and 4.4, and refractive index values from Table 1. The results of Fig 6.5(c) were utilized for calculating the wavelength dependent excess permittivity by making use of Eqs. (3.15) and (3.16), and the results were applied to determine per-mittivity as a function of wavelength using Eq. (3.14). Fig. 6.6 shows the results of excess permittivity for two samples, namely 5% and 15%, there are clear nice over-lapping fingerprints at ca. 1200 nm and 1400 nm which are indicators of adulteration in the measured samples. Therefore, it is possible to discern the presence of kerosene in diesel oils based on excess permittivity curves. This is a novel finding thanks to this thesis.
Figure 6.6. Excess permittivity for mixtures of samples C and kerosene (D) (Paper II).
6.4.2 Imaginary Excess permittivity
The other interesting part of this thesis is the imaginary excess permittivity as a func-tion of wavelength, for different adulterated samples. These were calculated using
44
Eq. (3.17), and by utilizing the wavelength dependent refractive index data depicted in Fig 6.5 (a) and (b). In Fig. 6.7(a) the curves for imaginary excess permittivity of adulterated versions of sample A are shown. The order of the curves corresponds to the percentage of adulteration, namely the excess permittivity curve for 5% is the lowest while that for 15% is the highest. It is possible to clearly and with confidence separate and discriminate the samples based on these curves.
The results for sample B are presented in Fig. 6.7(b) where similar trend regarding the location and separation is observed. However, unlike the case of sample A where the curves for 5% and 10% are somewhat close to each other (Fig. 6.7(a)), here the curves for 5% and 10% are more clearly distinct from one another. The interesting results around 1400 nm are promising and open doors for the development of meas-urement methods, which operate in the small spectral range. This will greatly serve analysis time and will enable timely measurements to detect adulteration.
The current state of the art technologies applied for fuel adulteration studies, is based on spectroscopic measurements coupled with multivariate analysis (Bassbasi M., 2013; Marcio J. C. P., 2011; Fazal M., 2017). These methods rely on a broader spec-tral range and require commercial multivariate analytical software packages such as Unscrambler X, and PLS toolbox for Matlab, for data analysis. These are usually ex-pensive and requires long time (spectroscopic measurements and analysis), and spe-cial training, therefore usually suited for laboratory applications. One of the quests of this thesis is to come up with methods that will enable the development of field condition measurement devices. Therefore, both novel methods, namely excess per-mittivity and imaginary excess perper-mittivity are potential candidates for such a pur-pose. We infer that, these results can lead to more promising twofold solutions.
Firstly, the spectral region around 1200 nm and 1400 nm have been identified as the most important regions for identifying the presence of kerosene in diesel oils. There-fore, it is possible to utilize this narrow band and reduce the processing time for com-mercial software packages. Secondly, thanks to the novel results at 1400 nm, more doors are open for devices that exploit the concept of imaginary excess permittivity at a very narrow wavelength around 1400 nm.
45 a
b
Figure 6.7. The zoomed imaginary excess permittivity for samples adulterated by kerosene in the vicinity of 1390 nm to 1427 nm (a) Sample A (b) Sample B (Paper III).
6.4.3 Summary
The real and imaginary excess permittivity of diesel oils adulterated by kerosene were studied. This was achieved by combining data measured by spectrophotometer and Abbe refractometer, and thereafter utilizing the SSKK analysis to calculate
wave-46
length dependent refractive index, excess permittivity and imaginary excess permit-tivity. The excess permittivity reveals nice spectral fingerprints at ca. 1200 nm and 1400 nm, which indicates the presence of kerosene in diesel oils. The fingerprints are unavailable if refractive index or transmittance data are considered independently.
The imaginary excess permittivity method provides nicely ordered curves around 1400 nm, which clearly separate diesel oils adulterated by different volume fractions of kerosene.
This is the first time in applied optics that the model-independent SSKK analysis is utilized and proposed for excess permittivity and imaginary excess permittivity studies of any binary or multi-mixture liquids. The proposed methods in the present form are laboratory based. Nevertheless, due to availability of portable NIR spectro-photometers and small digital handheld refractometers, it is possible to design a measurement unit which is equipped with a laptop for field measurements by fuel regulatory authorities. The disadvantage of the system is requirement of well trained personnel, with background in data analysis packages such as Matlab, to carry out the measurements and analysis.