Analysis of Aluminum Micro Inclusions

Optical emission spectrometry (OES) performs elemental analysis of solid aluminum samples rapidly and cost effectively with ease. The Thermo Scientific™ ARL iSpark™ Series metals analyzer (Figure 1) is an OES spectrometer platform delivering superior performance with unprecedented precision and accuracy to analyze aluminum, from trace to alloying element levels. With Spark-DAT (Spark Data Acquisition and Treatment) methods, the ARL iSpark can replace or simplify the conventional methods of inclusion assessment.

Figure 1. The Thermo Scientific™ ARL iSpark™ Series metals analyzer.

Advantages of Thermo Scientific™ ARL iSpark™ Series Metals Analyzer

The ARL iSpark 8860 or 8880 spectrometers coupled with Spark-DAT analysis yield the following benefits:

• The ability to perform inclusion analysis as well as elemental concentration analysis significantly reduces investment costs for inclusion analysis.
• The ability to provide data on inclusions shortly after sample taking offers key insights for in-process control of the metal elaboration.
• Conveniently detects randomly distributed exogeneous inclusions and rapidly analyzes very large surface areas.
• Requires very less time for inclusion analysis and associated sample preparation.
• Performs inclusion analysis simultaneously with the analysis of elemental concentrations for over 30 samples per hour.
• Can perform inclusion analysis on all samples analyzed by OES.
• Does not require additional cost and time for operations.

Treatment Principles

With the Spark-DAT methods, the ARL iSpark enables using different treatment principles compared to OES concentration analyses. The light intensity values for all the single sparks are presented to a special mathematical treatment rather than integrating and translating into concentration. The intensity of a single spark signal relies on the sample composition at the position struck by the corresponding single spark. An intensity peak will be the outcome if the concentration of an element in the ablated sample material is considerably greater than the concentration of its soluble form in the matrix.

Practical Aspects and Analysis Time

The Spark-DAT methods comprise software and specialized algorithms and are offered with PMTs only. The single spark intensities obtained with Single Spark Acquisition (SSA) are utilized for inclusion analysis and conventional elemental concentration analysis, thereby performing the two types of analyses simultaneously. Since the Spark-DAT raw dataset is very large and complex, the values pertaining to the data of interest are calculated using fast dedicated algorithms. The resulting values can then be processed like traditional OES results by the analytical software.

For a single measurement, the Spark-DAT analysis alone takes up to 7 seconds, which includes 2 seconds of Ar flush. This mode is appropriate only for rapid counting and confirmation of inclusion types, for acquiring raw data for off-line interpretation. Nonetheless, the Spark-DAT analysis together with concentration analysis holds more potential. In this case, the average analysis time taken is shown in the following table:

These analysis times (remained the same compared to standard elemental analysis) enable performing inclusion analysis in many contexts, especially in aluminum production.

Benefits of Spark-DAT Inclusion Analysis

Spark-DAT inclusion analysis provides great benefits for:

• Inclusion control for quality assurance
• Process control through on-line monitoring of inclusions
• Screening hundreds of samples for inclusions in a day
• Evaluation of number and type of inclusions
• Replacement of long or costly analysis techniques.

Estimation of Number and Type of Inclusions

Counting intensity peaks on the channel of a specific element using the algorithm Peaks is the simplest application of the Spark-DAT methods. Counting intensity peaks allows for estimating the number of inclusions having this element. As delineated in Figure 2, it is possible to easily determine clean and dirty aluminum samples through comparison of the number of peaks counted on the channels of the inclusion elements.

Figure 2. Comparison of the number of peaks counted on the channels of the inclusion elements helps identifying clean and dirty aluminum samples.

The algorithm Composition enables counting coincidental peaks appearing on the channels of different elements simultaneously during the same single spark. It is possible to count coincidences of up to four channels with the algorithm Composition, thereby enabling the chemical formulation of complicated inclusions inter-metallic phases or inclusion clusters (Figure 3). Moreover, the option to check for non-coincidences as well as coincidences eliminates ambiguities on the inclusion type.

Figure 3. Coincidences of up to four channels can be counted with the algorithm Composition.

Qualitative Size and Size Distribution

Since large inclusions normally affect the metal quality, it is essential to understand the size of the inclusions or their size distribution. It is possible to use the two algorithms Peaks and Composition to count signals pertaining to different intensity classes. Evaluating the inclusions between consecutive threshold values yields the count of inclusions in the size class that they delimit.

Figure 4 shows an example of the count of peaks and coincidences between 3 and 6-SD relative to small size inclusions, between 6 and 9-SD to medium size inclusions and, greater than 9 to larger size inclusions. Such evaluations enable producing qualitative inclusion size distributions.

Figure 4. Calculating the inclusions between consecutive threshold values provides the number of inclusions in the size class that they delimit.

On-Line Analysis and Off-Line Investigations

It is possible to simultaneously monitor the Spark-DAT results, count of intensity peaks and coincidental peaks with concentration values. It is also possible to process, display, transmit, and store the Spark-DAT results like any standard OES result. Figure 5 shows an OXSAS screen depicting partial results of an analysis including elemental determinations and inclusion related information (peak counts, qualitative size distribution).

Figure 5. An OXSAS screen depicting partial results of an analysis including elemental determinations and inclusion related information.

It is possible to store the Spark-DAT intensity data in standard text (.txt) or comma separated value (.csv) files, which can be utilized off-line for subsequent analysis on inclusions or for research and development of new techniques or algorithms. They can be graphically represented with the Spark-DAT viewer integrated in OXSAS. Thermo Scientific continues to improve existing algorithms or create new algorithms, which can be accessed by existing users together with OXSAS upgrades.

Conclusions

The ARL iSpark 8860 and ARL iSpark 8880 metals analyzer turns out to be a versatile tool with the optional Spark-DAT methods. In the aluminum industry, Spark-DAT methods offer rapid, convenient and economical solutions for inclusion analysis for routine use or research. The simplest Spark-DAT methods enable ultra-fast on-line counting of inclusions, determination of their composition and qualitative size classification within a few seconds to a couple of minutes. Hence, they effectively control inclusions during aluminum production.

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

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