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Study On The Material Properties Of Organic Pigments

Organic pigments have been widely used in latex paint and ink formulations. Because organic pigments are not only insoluble in organic solvents, but also have similar structures, it is challenging to analyze and explain their structures. In the past, all the organic pigment determination methods are based on solvent extraction, filtration and purification. These traditional techniques are very cumbersome, time-consuming and laborious, and the value of the data obtained is very limited due to different analysts.

Solutions to difficulties in data analysis

Frontier's py GC / MS provides a revolutionary solution for the analysis of organic pigments in the complex systems of paint, ink and coating industry. Direct analysis of samples without pretreatment, such as solvent extraction. The products were separated directly on high resolution chromatographic column and identified by spectral (MS) and retention (GC) values. This technique can be used for qualitative and quantitative analysis, and allows multiple and custom analysis of the same sample

"Method chart" of organic pigment analysis

We have developed a series of techniques called "method maps", which use multi-functional cracking furnace EGA / py-3030d combined with desktop GC / MS to characterize organic pigments by chemical methods. These technologies are applicable to almost all organic materials, from volatiles to polymers. In fact, the technology provides scientists with two simple steps to determine the composition of any unknown sample.

The first step in developing a test method using this technique is to drop the sample into a relatively low temperature furnace for escape gas analysis (EGA). Then set the furnace to a higher temperature. With the increase of temperature, the components of the sample "gradually escape". Then the response curve of the furnace with the change of temperature is obtained. The EGA example in Figure 1 contains two heat sensing regions.

The next step of the analysis method is determined by using the EGA thermal spectrum. In the above example, a sample can be introduced at 300 ° C to analyze the "volatiles" - only compounds in samples below 300 ° C can escape and be transported to the top of the column for analysis. If there is a response to both "Volatile" components and compounds with higher boiling points, the detection can be carried out in two steps, and a cold trap may need to be added. In order to make full use of the separation ability of the chromatographic column, the cold trap will refocus the responding volatile analytes on the column head. First, at 300 ° C, the sample was dripped into the furnace and thermally extracted the volatile compounds. The volatiles gathered at the top of the column and separated on the column. In the analysis of volatiles by gas chromatography, the sample is extracted from the furnace. After the completion of GC operation, the GC furnace was reset to raise the temperature of cracking furnace to 550 ° C, and then the samples were dropped into the furnace for pyrolysis. The pyrolysate is trapped at the top of the column and then separated.

Cracking furnace is widely used in coating and coating industry. This technical application description introduces in detail the methodology of "method diagram" of some organic pigments.


In this work, frontier py GC / MS method was used to analyze the samples with relatively large molecular weight (about 1000). The non-volatile pigments include condensed diazo pigments, azo pigments and phthalocyanine pigments with similar structures.

The first step to characterize organic pigments is EGA technology. Ega-ms completes the detection experiment by programming at a heating rate of 20 ° C / min in the temperature range of 100 ~ 600 ℃.

The second step is to analyze the response spectrum obtained from EGA thermal spectrum. The pyrolysis of 35 organic pigments at 600 ℃ was analyzed by py GC / MS. F-search (four unique function libraries of Frontier search engine) was used to establish organic pigment library, and MS was used to process sample data. The spectral information of Py GC / MS analysis was merged into a retrievable MS database by using frontier f-search engine. Then other organic pigments can be easily added to the database. Finally, when faced with unknown samples, the pigment database can be used to identify the pigments in them.

Results and discussion

The analysis results of pigment yellow 93 and pigment yellow 94 by ega-ms and py GC / MS are shown in Fig. 2 and Fig. 3. The molecular structures of the two pigments are similar. These data are used to build a database to identify unknown pigments with similar structures. Py GC / MS is very useful in the analysis of samples containing a variety of pigments, because the pyrolysis products of each pigment can be separated, identified and quantified. This technique can provide detailed information (name, structure and molecular weight of compounds) without sample preparation and solvent addition, making py-gcms a promising analytical tool. In this industry, the difficulty of sample analysis becomes relatively simple.


In the coating laboratory, the multi effect pyrolysis furnace provides many advantages and can make the product quality improve with the times. In fact, almost any material (liquid or solid) can be chemically characterized by this technique. This method ensures that every aspect of the detection system has repeatability and accuracy, so as to ensure the reliability and data quality of the system. All interfaces in contact with the sample are quartz or inactive stainless steel. No transmission lines, no cross contamination. The system also improves the productivity of the laboratory, such as sample pre-treatment time less than 5 minutes, then heating or cooling in a low-quality ceramic furnace within the recording time, followed by efficient and continuous sample analysis. This technology requires only a small number of samples, thus reducing the cost of sample transportation, treatment and disposal. In addition, no solvent is required for sample analysis.


Contact: Anita

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