Journal of Forensic Science and Medicine

ORIGINAL ARTICLE
Year
: 2015  |  Volume : 1  |  Issue : 1  |  Page : 43--47

Discrimination of Car Headlight Plastic by Gel Permeation Chromatography


Bo Wang1, Yangke Quan2, Hongling Guo2,  
1 China University of Political Science and Law, Beijing, China
2 Institute of Forensic Science, Ministry of public Security, Beijing, China

Correspondence Address:
Yangke Quan
Beijing citiy Muxidi Nanli No.17, Beijing 100038
China

Abstract

Car headlight plastic as a kind of evidence often can be seen in traffic accidents and some other cases. We tested 20 brands of car headlight plastic using gel chromatography. The data were processed using the Statistical Package for the Social Sciences (SPSS) one-way analysis of variance (ANOVA) and the discrimination rate was 97.14%. This indicated that we could discriminate between different headlights by the molecular weight of their headlight plastic. Gel permeation chromatography is an effective method of discriminating between headlights, particularly in the case of a traffic accident.



How to cite this article:
Wang B, Quan Y, Guo H. Discrimination of Car Headlight Plastic by Gel Permeation Chromatography.J Forensic Sci Med 2015;1:43-47


How to cite this URL:
Wang B, Quan Y, Guo H. Discrimination of Car Headlight Plastic by Gel Permeation Chromatography. J Forensic Sci Med [serial online] 2015 [cited 2023 Feb 3 ];1:43-47
Available from: https://www.jfsmonline.com/text.asp?2015/1/1/43/157909


Full Text

 Introduction



In traffic accidents the vehicle headlight is the part that is most likely to collide and break. Therefore, the inspection of lightshade pieces can yield very important evidence when investigating accidents or detecting a hit-and-run. Early vehicle lightshades were composed of glass; however, recently glass lightshades have been replaced by plastic lightshades. There are many vehicle types, models, and manufacturers. However, lightshade materials mainly consist of polycarbonate (PC) and poly (methyl methacrylate) (PMMA). [1] Currently, in forensic analysis in China, plastic is typically identified using infrared spectroscopy to determine the plastic type and elemental analysis is used to determine any additive elements. [2] The purity requirements are very high because of the optical characteristics of lightshades; therefore, most of the lightshade contains no additives, and additives are generally organic. Thus, it is difficult to identify lightshade plastic. We require a new identification method that uses a small amount of the sample and has a high identification rate.

Plastic is a polymer material, and during its synthesis, differences between monomer properties and production processes result in different average molecular weights among manufacturers. Gel permeation chromatography (GPC) can be used to test the average molecular weight of polymers and determine their molecular weight distribution. A gel permeation chromatography system equipped with a refractive index detector and right- and small-angle light scattering detectors can determine the composition of plastic samples, including their average molecular weight (M w ), number average molecular weight (M n ), and molecular weight distribution to provide a basis for distinguishing between them. Herein, we determined the molecular weight and molecular weight distribution of automotive lightshade plastic using GPC. We hope that this provides a new effective method for plastic material identification.

 Materials and Apparatus



Materials

We collected 20 different automobile headlight shade samples. Fifteen samples were composed of PC, and five samples were composed of PMMA. These are detailed in [Table 1] and [Table 2].{Table 1}{Table 2}

Instrumentation

GPC is also called gel diffusion chromatography, exclusion chromatography, or restricted diffusion chromatography. In this method, a sample mixture passes through a gel stationary phase with a certain aperture. Components with different molecular weights can be separated because of their differences in flow through the volume of the gel. The basic principle is to load the gel into the column, then to add a liquid mixture of a material of different molecular weight. Small solutes can penetrate into the gel, whereas high molecular weight molecules cannot and they flow with the solvent outside of the gel, and therefore elute earlier. The result of chromatographic separation is different molecular masses can be separated, and higher molecular weight molecules elute first. [3]

This study used a Viscotek GPC gel chromatography system (Malvern, United Kingdom), consisting of a degassing device (VE 7510 GPC DEGASSER), solvent delivery system (VE 1122 SOLVENT DELIVERY SYSTEM), GPC column (T6000M), refractive index detector (VE 3580 RI DETECTOR), UV detector (UV DETECTOR 2500), and a multifunction detector (270 DUAL DETECTOR). [4] Malvern's proprietary OmniSEC software was used for the data analysis.

 Experimental



Chromatography conditions

The T6000M column (300 mm Χ 8 mm) was used as the stationary phase. The mobile phases were tetrahydrofuran (THF) and N, N-dimethylformamide (DMF) containing LiBr for the analysis of PC and PMMA, respectively. The flow rate was 1 ml/min and the column temperature was 35°C. The detector system consisted of a combination of refractive index and light scattering detectors.

Determination method

After the instrument constants became stable, a sample solution was prepared in the mobile phase solvent with a concentration between 3-5 mg/mL. The samples were subjected to GPC and the data were recorded and graphed. The molecular weight calculation principle is as follows:

[INLINE:1]

The following parameters were involved in this experiment:

RI =

The refractive index detector response, which indicates a change in the solution;

K RI = The instrument constant of the refractive index detector;

dn/dc =

The increment of the refractive index ratio, which depends upon the chemical nature of the analyte;

c i = The sample concentration;

LS = The light scattering detector response;

K LS = The increment of the light scattering detector

M = The sample molecular weight

According to equations 1 and 2, the molecular weight of the sample M = LS/(K LS * RI i 2 /(K RI* c i ) 2 *c). RI and LS were determined by their respective detectors. The instrumental constants K RI and K LS were determined using a standard.

The molecular weight was calculated using Malvern's proprietary OmniSEC software. The instrumental constants K RI and K LS were determined using a polystyrene standard. There were two polystyrene standards: one with a narrow molecular weight distribution at 9,9284 g/mol, and another with a wide molecular weight distribution at 23,2763 g/mol. First, the narrow distribution polystyrene was measured and the equipment constants K RI and K LS were calculated using the molecular weight to establish a method of integral operation. Then we used the wide distribution polystyrene standard to verify the method. If the result and the known molecular weight deviation were within 5%, the instrument constants could be regarded as stable and the established method could be applied to the samples. We configured the solutions and used their concentrations and GPC results to calculate the M of samples. In this process, the method was established by the Omni SEC software, and the instrument constants KRI and K LS were not revealed as they were directly used by the system method. Once we chose the integral domain and baseline, the Omni SEC software automatically calculated the sample chromatogram integral data to determine the sample molecular weight and molecular weight distribution.

 Results and Discussion



The standard curve

The narrow- and wide-distribution polystyrene standard solutions were measured using the above chromatographic conditions. In [Figure 1], the red curve corresponds to the refractive index, whereas the green and black curves correspond to the right- and small-angle light scattering, respectively. The refractive index curve represents the variation of analyte concentration, and the light scattering curves represent high molecular weight materials passing through the detector, which was what we were testing for.{Figure 1}

Determination results of samples

Since the polymer molecules in plastic are not uniform, and are a mixture of congeners, it is called dispersion. Therefore, the molecular weight essentially refers to an average molecular weight, which differs according to the statistical methods used to calculate it. GPC obtains two types of average molecular weight: the weight and number average molecular weights, M w and M n , are determined by regarding the polymer molecular weight and polymer number as the statistical units, respectively. The ratio between these is called the "distribution coefficient." The two molecular weight calculation principles are as follows: [INSIDE:1] and [INSIDE:2], where D= Mw / M n. The molecular weights and molecular weight distributions of 15 PC samples were determined using GPC and the results are in [Table 3]. [Figure 2] and [Figure 3] show the GPC and molecular weight distribution graphs of PC sample No. 6, respectively.

[Figure 2] shows the GPC chromatogram of PC sample No. 6, which corresponds to the New Sagitar. It shows that the chromatographic peak appeared between 8-12 min. The red refractive index curve shows that during this time the analyte concentration was increasing, and the green and black light scattering curves show that when these peaks appear there were large molecular weight polycarbonates in the detector. Therefore, the light scattering peak was used as the selection criteria used to determine the integral domain and baseline position for the integral computation.{Table 3}{Figure 2}{Figure 3}

In [Figure 3], the horizontal axis is the retention volume, the left vertical axis is the refractive index, and the right vertical axis is the molecular weight of the polycarbonate. The molecular weight of polycarbonate in the outflow solution became smaller over time.

The molecular weight and molecular weight distribution of 5 PMMA samples were determined using GPC and the results are in [Table 4]. [Figure 4] and [Figure 5] show the GPC and molecular weight distribution graphs of PMMA sample No. 1.{Table 4}{Figure 4}{Figure 5}

Data processing

[Table 3] shows that of the 15 PC plastic lightshades, the minimum M w value was 24,651, the maximum value was 36055, and the values of samples numbers 1, 3, 8, and 11 were similar. In [Table 4], the differences in M w values of the 5 samples are clear.

To calculate the ability to distinguish the samples based on their M w , we chose a single parameter variance analysis, which is also called a one-way analysis of variance (ANOVA). [5] It tests whether there is a statistical significance between the averages of groups that are differentiated by one affecting factor. This analysis can reveal whether there is a significant difference between every two groups.

Our experiment used three test results for each sample correspond to a group, i.e., the M w level was the grouping factor. A single factor analysis of variance was the statistical inference method used to calculate the F statistic, which is the ratio between the sum of average squares between and within groups, respectively. It uses the following formula:

[INLINE:2]

where SSA and SSE and the sum of average squares between and within groups, respectively, and k and n are the number of samples and subjects, respectively.

In this experiment, the fifteen PC plastic samples were each measured three times; therefore k = 15 and n = 15 * 3 = 45. F obeys the F distribution of (14, 30) degrees of freedom. SPSS software based on the F distribution lists the corresponding concomitant probability.

If the associated probability value is less than the significance level, α, the null hypothesis that there exist significant differences of the control variables under different levels for each group is rejected; however, it is that there is no significant difference between the control variable under different levels of groups. The significance level, α, was 0.05 when using the method of single-factor analysis of variance n SPSS to analyze the experimental data.

The results obtained are shown in [Table 5].{Table 5}

The results of the PMMA data processing are in [Table 6].{Table 6}

 Analysis and Conclusion



Testing 20 plastic lightshade samples using gel chromatography showed that plastic samples that cannot be distinguished using the infrared spectrometry and scanning electron microscope energy dispersive spectra could be distinguished at a high rate. Due to the time required, experimental conditions, and other factors, we only tested two categories of lightshade plastic, and the sample quantity was small. However, the results showed that the discrimination ability of this method was very high. This research has a broad application prospects in the field of forensic science.

References

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3Niu Y, Zhang J, Wu Y, Shao B. Simultaneous determination of bisphenol A and alkylphenol in plant oil by gel permeation chromatography and isotopic dilution liquid chromatography-tandem mass spectrometry. J Chromatogr A 2011;1218:5248-53.
4Malvern Instruments Led. Analysis of Carbon-Filled Polyethylene by Advanced Triple Detection HighTenfiperature Gel Permeation Chromatography (HT-GPC). The Applications Book. 2013.
5De-cun Zhang. Statistics[M]. Science Press 2004;238-53.