Analysis of Aluminum Inclusions Using Optical Emission Spectrometry

By AZoM

Table of Contents

Introduction

Optical emission spectrometry (OES) is a fast, simple and cost-effective analytical technique used for elemental analysis of solid aluminum samples. It is used in several fields ranging from production to recycling and from foundries to service laboratories. The Thermo Scientific ARL 4460 Metals Analyzer (Fig. 1) is a high-performances, high-precision and high-accuracy OES spectrometer for analysis of aluminum.

In addition, the Spark-DAT (Spark Data Acquisition and Treatment) considerably extends the capability of this spectrometer beyond the characterization of elemental concentrations by enabling as well ultra-fast inclusion analysis. In the steel industry, the ARL 4460 spectrometer with Spark-DAT option is used to obtain information about the inclusions during the steel elaboration process. Spark-DAT analysis offers interesting potentials, in particular for replacing or simplifying the traditional techniques of inclusion assessment.

Figure 1. Thermo Scientific ARL Spectrometer Series.

Benefits

The benefits of using the ARL 4460 spectrometer with park-DAT option are the following:

• Drastic reduction of investment costs for inclusion analysis.
• Extreme shortening of the time for inclusion analysis and related sample preparation.
• No additional cost and time for performing operations in comparison to the standard OES spectrometer.
• Capability of performing in parallel inclusion analysis and analysis of elemental concentrations at a rate of more than 30 samples/hour.
• Availability of the information on inclusions shortly after sample analysis.
• Easier detection of rare or large inclusions.

Principles

The ARL 4460 spectrometer with Spark-DAT option has different acquisition and treatment principles when compared to standard OES spectrometers. Its salient features are:

• The light intensity values of all single sparks are obtained separately and submitted to specific mathematical algorithms.
• The intensity of a Spark-DAT signal depends on the composition of the sample at the position struck by the corresponding single spark. If the concentration of an element in the ablated sample material is significantly higher than the concentration of its soluble form in the matrix, the outcome is an intensity peak. This is typically the case when a spark hits a sample area containing a Ti based inclusion (e.g. TiB₂), because the Ti concentration is much higher than in the metal matrix due to the contribution of the inclusion. This is better explained in the following example: the concentration of Ti in a TiB₂ particle is roughly 69% and if an inclusion with a size of 5 mm ESD (Equivalent Spherical Diameter) is ablated together with the sample material, this gives an apparent rise in the concentration of 0.136%. Graphically, this is illustrated in figure 2.

Figure 2. Example of Spark-DAT acquisition for Ti-related inclusions. The intensity of the flat, noisy baseline signal is proportional to the concentration of Ti atoms dissolved in the matrix and the intensity of a peak depends on the amount of Ti atoms contained in the inclusion(s) ablated by a single spark.

Analysis Time

The Spark-DAT analysis alone takes a standard of 7 s for a single measurement (including 2 s Ar flush). This mode is recommended only for quick counting and confirmation of inclusion types and for obtaining raw data for off-line interpretation. However, Spark-DAT analysis is more interesting when combined with the analysis in concentration. In this case, the analysis time for a single measurement is typically 25 s. This is longer than the duration of the elemental analysis alone (21 s) and makes analysis of inclusions possible in a number of contexts, specifically during aluminum production.

Figure 3. Step-by-step diagram of the operations performed during Spark-DAT analysis.

Sample Preparation

The standard OES sample preparation can be used for Spark-DAT inclusion analysis. Milling which is the recommended surfacing technique for OES analysis of aluminum and its alloys guarantees a clean and uncontaminated surface, which is ideal for inclusion analysis.

Contexts of Use of Spark-DAT Inclusion Analysis

Spark-DAT inclusion analysis offers tremendous potentials for:

• Inclusion control for quality purposes.
• Process control via on-line monitoring of inclusions.
• Samples screening.
• Replacement of long and costly analysis techniques.

Evaluation of Number and Type of Inclusions

The simplest Spark-DAT application consists in counting intensity peaks on the optical channel of a given element with the algorithm Peaks. In general, a peak is defined as the intensity signal (I_peak) higher than a threshold situated at the mean intensity (m) of the element dissolved in the matrix (I_matrix), plus three times its standard deviation (SD):

       I_peak > m + 3•SD_Imatrix

Counting intensity peaks allows to determine the number of inclusions containing this element. As shown in figure 4, clean and dirty aluminum samples can be easily distinguished by counting the number of peaks on the channels of the inclusion elements. The algorithm Composition allows counting coincidental peaks, i.e. peaks appearing on the channels of several elements concurrently during the same single spark. The coincidence of a peak on Na and Cl channels, for instance, means that these two elements are contained in the same inclusion (e.g. a sodium chloride (NaCl) inclusion).

Figure 4. Examples of Spark-DAT Peaks analysis for two samples of clean (Left) and dirty (Right) aluminum.

In this example, no NaCl coincidence was counted in the clean sample and 96 were counted in the dirty one. Coincidences of up to four channels can be counted with the algorithm Composition. This enables the formulation of various complex inclusions, inter-metallic phases or inclusion clusters, as demonstrated with NaKCaCl in the following spark intensity diagrams of several elements recorded in an AlSi sample with 7% Si (Fig. 5). Furthermore, the possibility to check for non-coincidences in addition to coincidences helps remove ambiguities on the inclusion type. Note that other algorithms delivered with the Spark-DAT option can be used in the park-DAT analysis of aluminum alloy samples. The Soluble algorithm evaluates the soluble fraction of an element and allows calculating the concentration of the soluble part of the element. Soluble is routinely used in steel samples analysis to evaluate the soluble part of Al, B, Ca and Ti.

Figure 5. Examples of Spark-DAT Peaks analysis for several AlSi samples.

Qualitative Size and Size Distribution

Knowing the size of the inclusions or their size distribution is essential. Large inclusions are normally the most detrimental to the metal quality. The two algorithms Peaks and Composition can also be used to count signals belonging to different intensity classes. Since the peak intensity is related to the volume of the inclusion, these classes can be qualitatively considered as size classes. Setting the threshold 3xSD above the intensity of the element in the matrix allows the counting of all visible peaks. Setting it higher, for example at 6x or 9xSD as in the following example (Fig. 6), allows counting only the inclusions of larger sizes. Determining the inclusions between the consecutive threshold values gives the number of inclusions in the intensity class that they delimit. In the example, the number of peaks and peak coincidences between 3x and 6xSD correspond to small size inclusions, between 6x and 9xSD to medium size inclusions and higher than 9x to large size inclusions. Such calculations enable generating qualitative inclusion size distributions. The algorithm QuIC (Quantification of Inclusion Content) recently developed for quantitative analysis of inclusions content and size in steel samples can also be extremely useful in aluminum characterization. In steel, it allows for the evaluation of the average equivalent spherical diameter (ESD) of inclusions in a size class for a given inclusion type (e.g. Al₂O₃-CaO).

Figure 6. Examples of Spark-DAT analysis using Peaks and Composition algorithms for identification of different intensity classes.

Inclusions Quantifiable with Spark-DAT Option

Different types of endogenous and exogenous inclusions and compounds may be observed directly or indirectly in aluminum and its alloys with the ARL 4460 spectrometer with Spark-DAT option: oxides (Al₂O₃, MgO, CaO, FeO, MnO, SiO₂, etc.), spinels (MgAl₂O4), carbides (TiC, Al₄C₃, etc.), borides (TiB₂, etc.), nitrides (AlN, etc.), salts (MgCl₂, NaCl, KCl, CaCl₂, etc.), graphite, intermetallic compounds (Cr-Mn-Fe, etc.) and various other compounds (AlP, Mg₃P₂, sulfides, AlB₂, Al₄C₄B, etc.).

The detection of an inclusion type is restricted mainly by the sensitivity of the analytical lines used, by the size and shape of the inclusion and by the concentration level of the inclusion elements as soluble elements in the matrix: higher line sensitivity and lower soluble content enable smaller inclusions to be detected. Low sensitivity of the oxygen line and Al being the matrix element explains the challenge to achieve direct observation of Al₂O₃.

On-line Analysis

The results of Spark-DAT analyses, such as number of peaks and coincidental peaks can be monitored simultaneously with the concentration values. These results can be processed like standard OES results, used in various types of calculations, displayed, transmitted and stored together (Fig. 7).

Figure 7. Example of Spark-DAT results display. 

Off-line Investigations

The Spark-DAT intensity data can be stored in standard text (.txt) or comma separated value (.csv) files. These files can then be used off-line for investigations on inclusions or for research and development of new methods or algorithms. They can be shown graphically with the Spark-DAT viewer integrated in OXSAS (Fig. 8), a very useful tool that shows the sparks diagrams and the intensity distributions and helps searching coincidental peaks, setting-up personalized inclusion analysis program and refining its parameters. They can also be used as input for third party programs.

Figure 8. Spark-DAT intensity data shown via the Spark-DAT viewer integrated in OXSAS.

Hardware and Technical Information

• Capacity of up to 32 Spark-DAT acquisition channels.
• OXSAS software version 1.4.1 and higher, in order to benefit from the latest developed algorithms and methods.
• New and improved algorithms available with OXSAS software upgrades.
• Output file for off-line data evaluation in .txt or .csv format.
• Spectrometer VUV configuration recommended to allow the analysis of very important inclusions elements, namely C, N, O and Cl.

Conclusions

The Spark-DAT option of the ARL 4460 metals analyzer increases the versatility of the OES spectrometer. From routine uses to research applications, Spark-DAT methods provide quick, simple and cost-effective solutions for inclusion analysis in the aluminum industry. Among all the inclusions analysis methods available today for the aluminum industry, the Spark-DAT based methods are the fastest. The Spark-DAT option permits ultra-fast on-line counting of inclusions, identification of their type and qualitative size determination in a time ranging from several seconds to a couple of minutes, making it highly effective for controlling inclusions during aluminum production. The inclusion analysis can be combined with the standard analysis of elemental concentrations. The sample and its surface preparation, as well as the instrument maintenance and consumables, are the same compared to a standard OES instrument. This means extremely low operation costs compared to the other inclusions analysis techniques that require dedicated instruments. In addition, the ability to obtain elemental analysis information and inclusion contents with a single OES instrument greatly reduces investment and operating costs.

About Thermo Fisher Scientific-Elemental Analysis

For over 75 years, Thermo Fisher Scientific has been a worldwide supplier of spectrochemical instrumentation to major industries including steel, transportation, cement, construction, food, pharmaceuticals, chemicals, academic research, petroleum and electronics. They offer unsurpassed capabilities in the areas of optical emission (OE), X-ray fluorescence (XRF), X-ray diffraction (XRD) and automation of spectrometers.

This information has been sourced, reviewed and adapted from materials provided by Thermo Fisher Scientific- Elemental Analysis.

For more information on this source, please visit Thermo Fisher Scientific- Elemental Analysis.