HOW ON-LINE NIR SENSOR ENHANCE ORE PROCESSING AUTOMATION

Critical components of any ore processing automation strategy are the sensors that provide compositional, mineralogical, and ore property information that are essential for process optimization decisions. On-line over-the-conveyor sensors provide real-time information that is then available for feed-forward control of a wide range of ore processing operations.

Near-infrared (NIR) reflectance spectroscopy is widely used to provide mineralogic and ore property information required for ore transport, sorting, and processing decision making. The advantage of the NIR technique is the speed of measurement and the need for minimal or no sample preparation. Many of our customers have developed quantitative calibrations for a wide range of gangue minerals and ore properties; these include swelling clays, total clays, kaolinite, calcite, talc, hornblende, moisture, acid consumption, and hardness.  Analysis of geolocated blast hole chip samples using high-throughput NIR analyzers currently provides information essential for heap leach optimization and, for accurate short-term loading and hauling planning at many operating mines.

With the availability of the QualitySpec 7000 over-the-conveyor NIR sensor, these calibrations are now able to provide the real-time information necessary to implement feed-forward control of ore processing. This presentation provides an overview of the NIR method, current usage examples in operational mines, and an overview of how the QualitySpec 7000 over-the-conveyor NIR sensor enables ore processing automation.

Near-infrared (NIR) reflectance spectroscopy is widely used to provide mineralogic and ore property information required for ore processing decision making.

 

Written by: Brian Curtiss, Posted by: Malvern Panaltyical (www.materials-talks.com)

3 Things to Consider Before Analyzing a Sample

  1. Is your instrument optimized?

In a recent blog we explored the importance of instrument optimization for ICP-OES and ICP-MS, but all instruments should be frequently checked to confirm they are operating as expected. Preventive maintenance and appropriate start up and shut down SOPs are key to the integrity of analysis.

  1. How should you calibrate your instrument?

If you are following a standard method, calibration points might be recommended, however, you must also consider the expected levels of your specific samples when designing your calibration curve. Other best practices to consider include:

  • Don’t bracket your calibration curve too tightly around your samples expected levels
  • Match the matrix of your calibration standards to that of your samples to improve accuracy
  • Include a check standard in your run schedule

It is also important to be sure you have a high-quality calibration blank! Purchasing a CRM with a certificate of analysis that includes a trace scan can give you confidence in your blank.

  1. What is the best way to prepare your samples?

Top goals of sample preparation include bringing the sample to a suitable form for your instrument/ technique, ensuring sample homogeneity, and to manage potential interference’s resultant from the sample’s original form. Equally important is considering the quantity sample preparations and rate of throughput required for your lab. While there are many methods for sample analysis, some preparation techniques offer additional advantages in terms of speed and number of samples that can be prepared at once.

 

How do you prepare your instrument and samples for analysis? Share your best practices in the comments!

 

Written by: Courtney Dillon, Posted by : LGC ARMI MBH (www.armi.com)

THE IMPORTANCE OF CALIBRATING YOUR REMOTE SENSING IMAGERY

Most people using satellite or aerial imagery understand the importance of geometric calibration; you need to tie the pixels in the imagery to the corresponding coordinate locations on the earth so that you can use the imagery in mapping applications, and for analyses such as change detection.

However, there is another type of calibration that you should be doing on your optical remote sensing imagery to ensure that you are getting high quality and useful results from your images.  Accurate radiometric calibration is a critical component for successful imagery analysis.

Radiometric calibration, also known as radiometric correction, is important to successfully convert raw digital image data from satellite or aerial sensors to a common physical scale based on known reflectance measurements taken from objects on the ground’s surface.  This type of correction is important for reliable quantitative measurements of the imagery.

Each pixel in a spectral image has a signature based on the object or objects that the pixel represents as shown below:

On the left is a subset of an AVIRIS hyperspectral image that has been converted to reflectance. The spectral signature of the material associated with the pixel in the crosshairs is shown in the Spectral Profile plot on the right. ENVI software was used to display the image and the spectral plot.

You won’t see much of a difference in the image itself when correcting an image from radiance to reflectance.  The difference show up in the spectral signature associated with each pixel.

Ground Target Collection

The collection of known reflectance measurements from ground targets is performed using a field spectroradiometer like ASD’s FieldSpec 4.  To get the best results, you would try to measure the ground targets with the FieldSpec coincident with the overflight of the imaging sensor.  The collected field data is then used as input, along with the remote sensing imagery, in a software tool like ENVI to convert the radiance data to reflectance.

 

Measuring reflectance using a FieldSpec 4

What does this actually mean? 

Well, imagery typically starts out with uncalibrated, raw digital numbers (DN) for pixel values in the image.  These DN values get converted to radiance by applying a series of gains and offsets supplied by the data provider.  Imagery data that you purchase has often already been converted to radiance, or the data provider attaches some metadata with the corrections that you can apply using a remote sensing analysis package like ENVI software.

Radiance depends on the illumination (intensity and direction), orientation and position of the target feature being imaged, and the path of the light through the atmosphere.

Factors that affect radiance (Diagram from Humboldt State University [1])

The issue with radiance is that is has a lot of variability in terms of solar illumination and atmospheric effects such as water vapor in the atmosphere, so to get reliable and repeatable results, radiance typically gets converted to reflectance for image analysis.  Reflectance is the proportion of radiation striking a surface to the radiation reflected from it. With reflectance, the atmospheric variability is removed, so you get much more reliable measurements.

Spectral signatures showing radiance versus reflectance for a pure white panel, vegetation, and a dirt road. The radiance signatures show some of the main areas where atmospheric effects are a problem. [2]

Converting your imagery data to reflectance by using field reflectance measurements collected with a FieldSpec  gives you the most accurate results and greatly improves your ability to analyze your imagery, whether you are characterizing features or identifying target materials in your imagery.

If you would like more information on the FieldSpec or the benefits of calibrating your imagery, please click here

 

Written by : Ms. Susan Parks, Posted by: Malvern Panalytical (www.material-talks.com)

THE VALUE OF MINERALOGICAL ANALYSES FOR BASE METAL MINING AND BENEFICIATION – NICKEL

This blog elaborates on the nickel ore application in more detail.

Nickel ore processing

Primary sources of mined nickel are [1] magmatic sulphide deposits with pentlandite as a main ore mineral; and [2] laterites deposits, where primary minerals are nickeliferous limonite and garnierite. Historically most nickel production was derived from sulphide deposits due to the lower cost of processing, compared to laterite ores. However, today laterite nickel ore became an important second source of nickel production, next to the sulphide deposits.

Mined sulfide ore, after crushing and grinding, is concentrated using flotation and magnetic separation. Subsequently, concentrates are smelted to produce nickel matte, which is further refined to produce pure nickel metal. Mineralogy plays an important role during flotation to separate nickel sulfides from gangue minerals. Apart from usual “trouble-makers”, like talc and other soft minerals, the different crystallographic modifications of pyrrhotite (commonly occurring together with pentlandite) affect downstream processing.  Pyrrhotite is an iron-deficient sulfide, which occurs in either hexagonal (hpo) or monoclinic (mpo) form. Mpo and hpo pyrrhotites differ in their magnetic properties and hence behave differently during magnetic separation. Furthermore, hpo is known to be more reactive, which must be taken into account during the flotation.

Processing of laterite nickel ore is more complex. Crushed and ground ore is leached under high pressure using sulphuric acid. After the separation the nickel liquor goes straight to a refinery for pure metal production. Alternatively intermediate nickel hydroxide (or sulphide) is produced that is further processed in a nickel refinery. Similar to the processing of nickel sulphide ore, the mineralogy of nickel laterites defines the efficiency of the leaching step. Soft minerals, (e.g talc, clays) need to be monitored carefully since such minerals can decrease the efficiency of the leaching process. Soft minerals will react with sulphuric acid, thus excluding a portion of that expensive reagent from the process. Furthermore, large concentration of soft minerals may cause blockages and reduce the pumping efficiency.

Accurate and frequent mineralogical monitoring of nickel ore by either x-ray diffraction (XRD) or near-infrared spectroscopy (NIR) helps to increase the efficiency of the concentration and refining and enables corrective measures that increase the lifetime of processing equipment and avoid unexpected maintenance.

The added value of XRD for efficient nickel ore processing

In the previous section we discuss the challenge of handling two modifications of pyrrhotite, hpo and mpo, during sulphide nickel ore concentration. As both modifications have different crystal structure (hexagonal vs. monoclinic) they can be easily identified and quantified using XRD.

Figure 1 zooms on the characteristic diffraction peaks of hpo and mpo pyrrhotite modifications.

the characteristic diffraction pattern with the main hpo and mpo peaks
Figure 1. Characteristic peaks of mpo (left) and hpo (right) – modifications of pyrrhotite.

Any XRD pattern is a set of diffraction peaks of different intensities, located at certain diffraction angles (2Theta), specific to a certain mineralogical phase. Peak positions enable identification of present phases.

The hexagonal modification (Figure 1, right) has a simpler diffraction pattern and gives a single peak just above 51 °2Theta (using Co radiation). The diffraction pattern of monoclinic pyrrhotite (Figure 1, left) is more complex with two overlapping peaks forming a doublet. In the case of hpo/ mpo mixtures peaks from both modifications overlap each other additionally.

XRD can distinguish between the two modifications of pyrrhotite. Using the relative intensities of the various mineral contributions to the diffraction pattern. Subsequently the different amounts can be quantified using the full-pattern Rietveld refinement method [1].

The full diffraction pattern along with the full mineralogical quantification for nickel ore concentrate is shown in Figure 2. The sample consists of 50% of mpo with only 3% of hpo and 4% of pentlandite. The hpo/ mpo ratio helps to define a strategy for the following separation steps. Analysis of gangue minerals is as important as characterization of nickel-bearing phases. For example, the sample, analyzed in Figure 2, contains significant amount of chlorite and biotite, known for their detrimental effects during flotation, which should be considered to improve the recovery rate. Quartz and other hard materials should also be monitored to increase the lifetime of crushing and milling equipment.

Results of XRD analysis of nickel ore concentrate
Figure 2. Results of XRD analysis of nickel ore concentrate.

Additional XRD tools for process monitoring

In the above section, we analyzed the mineralogy of nickel ore concentrate required for the optimization of downstream processing. In addition to the classical quantitative phase analysis, XRD offers several other tools to simplify day-to-day process monitoring. In our following blogs on iron ore and heavy mineral sand processing, we will give an example of cluster analyses [2,3] being used for quick and easy monitoring of different ore grades and mineral separation efficiency. A similar approach can be used to monitor the flotation and separation efficiency at nickel ore processing plant. Mineralogy of tails and waste products can also be controlled using XRD.

Added-value of on-line analysis by near-infrared (NIR) spectroscopy

In our blog about “The value of mineralogical monitoring”  near-infrared spectroscopy (NIR) was discussed as a valuable tool for mine exploration and on-line process control. A typical NIR application for nickel ores processing is the real-time monitoring of clays, chlorite and other gangue minerals in the ore on a belt.

To summarize, efficiency of nickel ore processing is directly determined by the mineralogy of the ore. The properties of the minerals, not the elemental content, define the behaviour during separation and concentration. At-line XRD and on-line NIR can be easily implemented into the process flow and ensure fast and accurate mineralogy monitoring at the most sensitive process steps.

References:

  • [1] H.M. Rietveld, A profile refinement method for nuclear and magnetic structures, J. Appl. Cryst. (1969), 2, 65 – 71.
  • [2] H. Lohninger, Teach Me Data Analysis, Springer-Verlag, Berlin-New York-Tokyo, 1999, ISBN 3-540-14743-8.
  • [3] G.N. Lance, W.T. Williams, A general theory of classification sorting strategies 1., Hierarchical systems, Comp. J. (1966), 9, 373 – 380.

 

Written by : Dr. Olga Narygina, Posted by : Malvern Panaltyical (www.materials-talk.com)

August 2020 – New Tool Steel, Cu and Al Alloy CRMs

Our partners ARMI | MBH team has continued their work to develop new products to ensure that we can provide the products you need for your analytical testing.. I am proud to announce the release of 5 new CRMs across a variety of base alloys for our industrials portfolio. included in this are two tool steels, two copper based alloys, and one aluminum alloy. If you want to learn more about any one of products listed you can simply click on the links to view the certificate of analysis.

ARMI is well known for its wide variety of non-ferrous alloys. This week we are proud to continue this tradition with the release of two copper based alloys, a Monel 450 and a CDA 647.

The Monel 450 ( IARM-Cu715-20) copper-nickel alloy is known for its superior corrosion resistance, especially in seawater. Typical uses for this alloy include seawater condenser, saltwater piping and other distiller/condenser parts which benefit from the corrosion resistance inherent in this alloy. Our CRM is certified for 12 elements, including Cu, Fe, Mn, Ni and P, which all fall within range for the typical composition. Informational values are also included for an additional 19 elements.

Silicon Bronze, modified CDA647 (IARM-Cu647-18) is the second new copper alloy which is a new alloy type for our portfolio. This type of alloy is typically used for applications such as brazing or welding rods, as well as welding electrodes and also for fasteners. It has moderate strength and is good for corrosion resistance. Our CRM is certified for Ni, Si, Al, Fe, Mg, Mn, Zn and Zr. Informational values for an additional 22 trace elements plus Cu, are also listed.

Our new tool steels include AISI S-7 and M-2 grades. The S-7, (IARM-FES7-18) is typical of the grade, which is known for good resistance to high impact and shock loading. Our S7 grade is certified for 22 elements, including those used for the composition definition, C, Mn, Si, Cr and Mo. In addition to the 22 certified elements, reference values are provided for an additional 9 elements, making this CRM easily adaptable for many different steel analysis applications.

Steel-Drill_iStock-157483587

The M2 grade, (IARM-FeM2-18) is a high speed tool steel. This W-Mo high speed steel grade has a relatively high C content, and good wear resistance. The new CRM for ARMI | MBH is perfectly in range for all elements in the compositional definition. The certified values include the grade definition elements of C, Mn, Si, W, Mo, Cr, V, Ni and S and also include certified values for an additional 11 elements, plus reference values for 12 more trace elements.

Our final new CRM is an Aluminum alloy for our MBH product portfolio is MBH-55X G04H8 K. This Al foundry casting alloy is an AA A319.0 type alloy, which generally has good casting and machining capabilities. Our CRM has certified values for 16 elements, including Cu=3.56%; Si=5.48%, Zn=1.07% and Fe=0.58%.

All of these new materials are available as either disks for OES/XRF analysis, or as chipped material for ease of digestion for analysis using ICP. You can measure the difference with ARMI | MBH CRMs!

For inquiries and Quote please CLICK HERE

 

Written by: Kim Halkiotis – ARMI MBH (www.armi.com)

HOW TO STREAMLINE SAMPLE PREPARATION FOR XRF

Sample tracking may not be the most exciting part of XRF workflows, but it’s one of the most vital.

The importance of XRF sample tracking

If you’re an XRF specialist, you’ll know there are many things that determine whether or not your sample fuses nicely to give a homogenous glass disk with the correct composition. These include sample particle size and degree of oxidation, flux purity and relative quantity, fusion temperature, and use of high-quality platinumware.

With so many factors at play, it’s vital to be able to identify reasons why a particular sample has failed to give a good result. Of course, this relies on knowing which disk came from which sample, and logging the success or failure of the fusion process. Up to now, this logging has always been manual – something that is easy enough on a small scale, but not if you’re running 500 samples a day.

It’s not always obvious why sample fusion for XRF succeeds or fails, and troubleshooting any difficulties depends critically on keeping track of samples – which is where our new software option comes in

In fact, it was precisely this need to handle high-throughput workflows that, back in 2018, spurred one of our larger customers to ask me if a sample-tracking option could be incorporated into our XRF sample preparation platforms.

The result (thanks to my Product team here at Malvern Panalytical) is a new ‘sample monitoring’ software option for our Claisse TheOx Advanced sample fusion system. It’s simple, it’s easy to use, and we think it will go a long way to improving workflows in labs running large numbers of samples.

Better sample tracking, easier troubleshooting

So what’s in the new software release for TheOx Advanced? We’ve added four main features to the existing user-friendly interface, which mean that you can now:

  • Associate a sample id with each fusion position – either manually, or using a plug-in barcode reader.
  • Mark a particular sample as having succeeded or failed.
  • Control the instrument remotely.
  • Send sample data directly to your LIMS system.
The user interface in the new software release for TheOx Advanced has additional features that enhance sample tracking and troubleshooting… but in all other aspects, it maintains the familiar appearance and existing easy-to-use functionality

The biggest benefit from these new features is eliminating the risk of losing track of your samples: I know for sure that a couple of our larger customers will be wanting to implement this feature straight away. In addition, being able to monitor the success or failure of individual samples means that it’s much easier to diagnose troublesome sample batches, and resolve problems with a particular fusion position or method.

One other aspect is also handy. Because the results can be fed into a LIMS system, requests for repeat analysis can automatically be generated for failed samples. This means one less thing for the operator to remember!

Making a new link in ‘the analytical chain’

Of course, getting successful XRF results involves more than just reliably tracking samples through the fusion process. At Malvern Panalytical, we like to think of it as being one link in our ‘analytical chain’ – products that support the entire analytical process from beginning to end. Over the 16 years that I’ve been with Claisse/ Malvern Panalytical, I’ve seen this range grow, to now include everything from high-quality fluxes and calibration standards, to automated sample weighing equipment, and of course the XRF platforms themselves.

So, whether you’re interested in simply streamlining data-handling in your XRF sample preparation system, or you need a fresh perspective on your entire workflow from sampling to analysis, rest assured that we can help you!

Reliable tracking for XRF sample preparation using TheOx Advanced is just one of the links in the ‘analytical chain’ of products offered by Malvern Panalytical

Getting the new software option

The new ‘sample monitoring’ software option for TheOx Advanced is available straight away – to enquire about pricing, simply contact your regional sales rep.

We know that it’s not always easy (or desirable) to download software onto lab instruments, so we’re providing the new software option for TheOx Advanced on a USB stick, for direct transfer onto the instrument. And installation doesn’t take long – it’ll be complete in about 10–20 minutes, and you’ll be ready to enjoy the benefits of improved sample tracking!

For inquiries please CLICK HERE 

 

Written by: Chantal Audet – Malvern Panaltyical (www.materials-talks.com)

Maximize your Mining productivity

Improved profitability, greater efficiency, optimum quality – it all starts with reliable data.

Low grade deposits and the increasing cost of processing are dampening profitability across minerals industries. But could you be making more of your mineral deposits? Representative sampling and accurate analysis provides the data you need to optimise all aspects of your exploration and mining processes. What you get:Greater control over the life of your mine

  • Greater control over the life of your mine
  • A sound basis for making process decisions
  • A better-quality product – and the proof to back it up
  • Improved profitability and process efficiency

For Inquiries please CLICK HERE

Posted by: FLSmidth (www.flsmidth.com)

The 5 most common ways to prepare samples for XRF analysis

Sample Preparation for XRF Analysis

XRF (X-ray Fluorescence Spectrometry) is a comparative chemical analysis technique that is capable of analyzing a wide range of materials in different forms for a large part of the periodic table. This versatility makes it applicable to a wide range of applications from quality control for metal alloys, to the analysis of sulfur in gasoline to heavy metals in plastics and electronics. XRF can analyze almost any material you can present to the spectrometer, but the better you prepare a sample the more accurate your analytical results. Your choice of sample preparation will always be a balance of the quality of results your require, the effort your are willing to expend (labor, complexity) and the cost (sample preparation equipment, labor, time to analysis). Your choice may be different for different materials depending on your analysis requirements.

How do you choose what sample preparation method is best for your application?

Here we review the 5 most common ways to prepare samples for XRF analysis and what you need to consider with each method.

 

Blog Image XRF Sample Preparation.png

Solid Samples

Solid samples can be anything from unprepared pieces of metal or electronics or plastics to cut and polished metal samples. The ideal sample for XRF analysis will have a perfectly flat surface. Irregular sample surfaces change the distance from the sample to the x-ray source and introduce error. All XRF systems are calibrated based on a fixed sample to source distance. Changing the distance can increase or decrease the intensity coming from any element contained in the sample.

Solid samples such as metal alloys, can be analyzed with no sample preparation or they can be cut and polished for a more quantitative analysis.

ARMI ARt Shot2.jpg

Even for largely flat samples, surface finish can affect your analysis, particularly for lighter elements. Rough surfaces can cause scattering and re-absorption of longer wavelength elements. This effect is energy dependent so while the Ni signal may not be affected, the signal from C or S could be dramatically reduced. Quantitative analysis of solid samples often requires finishing the surface with a lathe or grinding paper. The finer the finish the better the results will be for the lightest elements.

testing. It is also important to note that the sample preparation you choose should be applied to your calibration standards as well as any unknown samples.

Loose Powders

The analysis of loose powdered material usually requires that the sample be placed into a plastic sample cup with a plastic support film.  This insures a flat surface to the X-ray analyzer and the sample to be supported over the X-ray beam. The more finely ground the sample the more likely it is to be homogeneous and have limited void spaces providing for a better analysis.  Sufficient powder should be used to insure infinite thickness is obtained for all of the elements of interest. This requirement can be met by using 15g of sample for most materials. Special care should be taken for the analysis of metal powders in high power (2-4Kw) WDXRF instruments. The sample can heat up during analysis and melt through the support film resulting in abrasive powder being spilled directly into your instrument.

Pressed Pellets

Pressing powder into pellets is a more rigorous sample preparation than pouring loose powders into a sample cup.  The process includes grinding a sample into a fine powder, ideally to a grain size of <75um, mixing  it with a binding /grinding aid and then pressing the mixture in a die at between 20 and 30T to produce a homogeneous sample pellet. The binding /grinding aid is usually a cellulose wax mixture and combines with the sample in a proportion of 20%-30% binder to sample.

pressed pellets.jpg

This sample preparation approach provides better analytical results than loose powders because the grinding and compression creates a more homogeneous representation of the sample with no void spaces and little sample dilution. This leads to higher intensities for most elements than loose powders.  Pressed pellets are still susceptible to particle size effects if not ground fine enough, but the biggest limitation to this approach is the mineralogical effects which most predominantly affect the analysis of major elements. Pressed pellets are excellent for the analysis of elements in the ppm range. Pressed pellets are also relatively simple and inexpensive to prepare only requiring a pulverizing mill and sample press.

Fused Beads

Sample prepared as fused beads provide a near perfectly homogeneous representation of the sample to the XRF and is considered by many to be the ideal sample preparation method for solids.  Fused beads are created by mixing a finely powdered (<75um) sample with a flux in a flux/sample ratio of 5:1 to 10:1 and then heated to 900C-1000C in a platinum crucible. The sample is dissolved in the flux(usually a lithium tetraborate or tetraborate/metaborate mixture )and cast into a mold  with a flat bottom. The resultant glass disc or fused bead is a

Fused Beads.jpg

homogeneous representation of the sample free of mineral structures. The benefits of this approach are the reduction of mineralogical or matrix effects leading to more accurate analyses and the ability to combine several different matrix types into the same calibration curve.  Downsides include the relatively high sample dilution which has a negative effect on the analysis of trace elements and the higher cost associated with this type of sample preparation (fusion equipment, platinum crucibles and consumables) Typical fused beads are also only approximately 3mm thick and thus are susceptible to infinite thickness issues for heavier elements. Fused beads usually require higher initial costs between platinumware and a fusion device, but then have similar cost/sample to prepare as pressed pellets.

Liquids

Liquids are prepared by pouring them into a plastic sample cup in the same way as loose powdered samples. There are limited options for analyzing liquid samples and the main trick is to choose the correct support film that provides a balance of strength and transmission capabilities and contamination.  Mylar is a good general purpose film often used for the analysis of sulfur in fuels or lubricating oils. Polypropylene has better transmission than Mylar but has a lower tensile strength.  Kapton is the “bomb proof” film but dramatically attenuates your signal for lighter elements and is susceptible to strongly basic solutions.  If you are going to analyze liquids you will need to do a little research into selecting the best support film for your analysis goals. If you are using your XRF to analyze sulfur in fuels.

Conclusion

There are many ways to prepare samples for XRF analysis and the method you choose will be a balance of the sample type, the amount of effort you are willing to expend and the quality of results you require.

 

Written by: David Coler Posted by LGC ARMI | MBH  (www.armi.com)

Know “Why” & “How” ICP-OES Wavelength Calibration is needed and done

ICP-OES is one of the the analyzing technique across a number of industries, and when configured correctly, today’s instruments yield detection limits of 1 to 10 ppb for the majority of elements. Although a powerful elemental analysis technique, it is in fact a simple comparator, incapable of making absolute measurements.

Crystals_cropped_iStock-661239146 (4)

Fundamentally, qualitative identification of each element is determined by the presence or absence of emission lines and quantification is determined using the emission intensity. Unfortunately, optical spectra are very complex and variations in optical configurations mean that every ICP-OES instrument has a unique correlation between emission wavelengths and where they are positioned on the instrument’s detection system. Accurate indexing of each wavelength is critical for obtaining accurate data.

Wavelength calibration is the process used to “teach” the instrument exactly which position of its detection system corresponds to each emission wavelength. Wavelength calibration in ICP-OES is typically achieved by aspirating a multi-element solution which will produce elemental emission for each element contained in the solution.  This multi-element solution should be run regularly to adjust for daily variations which inevitably can occur in the optical chamber of the ICP. The specific elements contained in the solutions are chosen to produce relatively simple spectra while also covering the relevant wavelength range of the instrument. All modern ICP-OES instruments incorporate an automated wavelength calibration routine. The instrument operator simply loads the wavelength calibration solution designed for use with their model instrument and the software does the rest.

Wavelength calibration impacts virtually every aspect of your ICP’s performance, including its sensitivity (detection limits), stability (RSDs), and susceptibility to interferences. Accuracy of the preparation of the wavelength calibration solution is directly tied to the integrity of all of the analysis performed on the calibrated instrument.

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As we explored in a previous blog, Three Common Pitfalls to Avoid When Preparing Aqueous Multi-element Standards for AA, ICP, or ICP-MS, there are many opportunities to introduce inaccuracies while preparing multi-element standards. To mitigate that risk, regulations increasingly require that instrument calibrations carry international validity, particularly in industries producing legally defensible data. As a result, labs must use commercially available CRMs prepared by appropriately accredited manufacturers for all wavelength calibration. If you need help tuning your spectrometer, or selecting the appropriate wavelength calibration solution, one of our industry experts can help.

Ask an Expert 

Or if you want to know more about our Aqueous CRMs,

Visit our Aqueous Page

Written by: Courtney Dillon Posten on : ARMI MBH (www.armi.com)

Metal Processing Optical Emission Spectrometry (OES)

In Metal Industry, checks during all the production processes are extremely necessary, starting from raw material control and primary material fusion, up to quality verification before shipping the final product.

During all manufacturing phases, forming, molding, die-casting, extrusion, mechanical manufacturing, it is necessary evaluate different chemical-physical parameters in order to give the essential information for production cycle.

Our partner GNR offers advanced solutions to perform different and wide analytical tasks in the metal industry. 

For Metal Processing Optical Emission Spectrometry (OES) using Arc/Spark excitation is the traditional reference technique for fast and accurate  elemental analysis of solid metallic samples.

It is a well proven technology nowadays used in all the metal  industry  sector from production control to R&D, from incoming material inspection to scrap sorting.

GNR offers PMT-based or CMOS-based spectrometers, Bench Top, Floor Stand and Portable systems to provide high uptime and stable performance for enhanced productivity.

To know more about the GNR OES please CLICK HERE

 

Posted by GNR – Analytical Instrument Groups (www.gnr.it)