FAQs

Certified reference materials (CRMs) are used to calibrate and verify the accuracy of chemical analyses in the mining industry. They play a vital role in Quality Assurance/Quality Control (QA/QC) programs for mineral exploration, mine development, and mineral processing.

CRMs are essentially control samples with known chemical compositions.  They are inserted into batches of samples undergoing analysis to monitor the consistency and accuracy of the analytical results.  This helps to ensure that the data obtained from the analysis of real samples is reliable and can be used for informed decision-making.

CRMs play a pivotal role in ensuring the accuracy and reliability of analytical data generated during mining and exploration programs.  

Geochemical data underpins all major technical and financial decisions, including resource definition, grade control, mine planning, metallurgical evaluation and environmental monitoring, so poor analytical data can lead to costly mistakes. 

By methodically inserting CRMs into sample batches, companies can monitor laboratory performance and verify their analytical methods are producing accurate results.  

CRMs help identify analytical bias, calibration problems, contamination, or instrument drift before these issues affect large datasets. 

CRMs also support compliance with reporting standards and industry best-practice QA/QC procedures. They provide confidence that laboratory results are consistent over time and across laboratories. 

In exploration and mining, reliable analytical data is essential, and CRMs provide an independent benchmark against which laboratories can assess their performance, helping ensure that decisions are based on precise and reliable information. 

Simply put, laboratories use CRMs to verify the accuracy and consistency of their analytical results.  

CRMs are routinely included at regular intervals in sample batches as part of a laboratory’s QA/QC program. When a CRM is analysed alongside unknown samples, the laboratory compares the CRM reported result to the certified value. If the result falls within acceptable limits, it confirms that the analytical method and instrument calibration are performing correctly. If results fall outside expected ranges, it may indicate issues such as calibration drift, contamination, preparation errors, or analytical bias. 

CRMs are also used during method development, instrument calibration verification, staff training, and inter-laboratory comparison programs. In mining and exploration, they help maintain confidence in assay data used for operational decision-making. 

Different CRMs are designed for different applications, including crushed rock, pulverised ore, synthetic materials and trace-level standards. Selecting the correct CRM for the sample matrix and analytical method is imperative for obtaining meaningful QA/QC results. 

A reference material becomes “certified” when its values have been determined through a rigorous technical and statistical process and are supported by documented evidence. 

CRMs are produced under strict quality systems, typically in accordance with the requirements of ISO 17034. ISO is an international organisation body that ensures for products, services, and systems are safe, reliable, and high-quality.  

The material must first be carefully prepared and tested to ensure it is sufficiently homogeneous and stable for its intended use. 

Certified values are then determined using validated analytical methods, often involving multiple laboratories and repeated measurements. The resulting data is statistically evaluated to determine the final certified values and associated uncertainties. 

A CRM certificate provides important supporting information, including the certified values, uncertainty estimates, traceability information, intended use, and storage instructions. 

The certification process ensures users can truly rely on the material as an independent standard for verifying analytical accuracy. Certification is what distinguishes a CRM from a general reference material or an internal laboratory standard. 

A Reference Material (RM) is any material that is sufficiently homogeneous and stable for use in analytical measurement or quality control. It may have indicative or informational values assigned to it, but these values may not have undergone full certification. 

A Certified Reference Material (CRM) is a higher-level reference material that has been fully characterised using validated analytical methods and statistical evaluation. Certified values are reinforced by documented uncertainties and traceability information. 

CRMs are produced under strict quality systems, typically in accordance with the requirements of ISO 17034. The certification process includes homogeneity testing, stability studies, analytical characterisation, and uncertainty calculations. 

While both RMs and CRMs can be useful for laboratory quality control, CRMs provide a greater level of confidence because the assigned values have been independently validated and documented. 

In mining and exploration, CRMs are the preferred standard for QA/QC programs because they provide a reliable benchmark for assessing laboratory accuracy and performance. 

The certified values listed on a CRM certificate are determined through a detailed analytical and statistical process designed to ensure accuracy, reliability, and traceability. 

The process typically begins with careful preparation of the candidate material, followed by homogeneity and stability testing to confirm the material is suitable for certification. 

Analytical characterisation is then performed using validated analytical methods. This commonly involves multiple laboratories and several analytical techniques to minimise bias and improve confidence in the final values. Alternatively, a single, highly reliable method can be used with established and fully evaluated uncertainties 

The resulting data is statistically evaluated to determine the certified value for each analyte along with its associated uncertainty. This includes evaluating method comparisons, identifying and removing outliers, and weighting datasets based on their precision and methodology. 

The final certified values and uncertainties are documented on the CRM certificate, together with traceability information and instructions for use. 

This rigorous process ensures the CRM provides laboratories with a reliable and independent benchmark for assessing analytical accuracy. 

Homogeneity refers to how consistent a material is from sample to sample throughout a CRM batch. In a homogeneous CRM, every jar, sachet, or portion contains effectively the same concentration of the certified analytes, within acceptable limits. 

Homogeneity is critical because laboratories typically analyse only a small sub-sample of the CRM. If the material is not sufficiently homogeneous, different portions may produce different analytical results, reducing the reliability of the CRM. 

To measure homogeneity, samples are taken from across the production batch and analysed statistically. Testing may evaluate both between-unit homogeneity and within-unit homogeneity, depending on the intended sample size and application. 

Good homogeneity ensures the CRM performs consistently across laboratories, instruments, and analytical runs. It is a key requirement of ISO 17034 and an essential part of the CRM certification process. 

Without sufficient homogeneity, a CRM cannot reliably be used to assess laboratory accuracy or analytical performance. 

Stability testing evaluates whether a CRM maintains its certified values over time and under expected storage or transport conditions. 

A CRM must remain stable throughout its intended shelf life so that users can rely on the certified values during routine laboratory use. Changes in moisture content, oxidation, segregation, chemical reactions, or contamination can all potentially affect stability. 

Stability studies may include short-term testing to simulate transport conditions and long-term testing to assess storage over months or years. Samples are periodically analysed and compared to the original certified values to identify any significant changes. 

The results of stability testing help determine expiry dates, recommended storage conditions, and handling instructions. 

Stability is an important requirement of ISO 17034 because even a well-characterised CRM is only useful if its values remain reliable over time. Proper storage and handling by the user also play an important role in maintaining stability. 

Uncertainty is a statistical measure of the confidence associated with a certified value. It indicates the range within which the true value is expected to lie, based on the available analytical data and statistical evaluation. 

Every measurement contains some degree of uncertainty and CRM certificates provide uncertainty estimates so users can properly interpret analytical results. 

Uncertainty is a quantified parameter that characterises the dispersion of values attributed to a measured quantity. It expresses how much you doubt the accuracy of your result due to factors like instrument limitations or human error. 

Uncertainty may include contributions from factors such as analytical measurement variability, between-laboratory differences, homogeneity, stability, and sample preparation. 

For example, a CRM may report an iron value of 62.50% Fe ± 0.15% Fe. This means the true value is expected to fall within that uncertainty range at a stated level of confidence. 

Understanding uncertainty is important because it helps laboratories determine whether analytical results are acceptable and whether differences between results are statistically meaningful. 

Well-characterised uncertainties are a key feature of Certified Reference Materials and an important requirement of ISO 17034. 

Traceability refers to the ability to link a measurement result back to a recognised reference through a documented and unbroken chain of comparisons, each with known uncertainties. 

In Certified Reference Materials, traceability helps ensure that certified values are accurate, reliable, and internationally comparable. This is achieved through validated analytical methods, calibrated instruments, recognised standards, and carefully controlled quality systems. 

Traceability is important because it gives laboratories confidence that their analytical results are based on recognised measurement systems rather than arbitrary values. It also supports consistency across laboratories, instruments, and analytical methods. 

Under ISO 17034, CRM producers must demonstrate appropriate traceability for certified values. This gives users confidence that the CRM can reliably support QA/QC programs, method validation, and laboratory performance monitoring. 

In industries such as mining, environmental testing, manufacturing and pharmaceuticals, traceability is essential for producing defensible and trustworthy analytical data. 

While CRMs are widely used in mining and mineral exploration, they are also essential across many other industries that depend on accurate analytical testing. 

Environmental laboratories use CRMs for testing soils, water, sediments, and air quality. The food and agriculture industries use them to verify nutrient content, contaminants, and food safety compliance. Pharmaceutical companies rely on CRMs for quality control, method validation, and regulatory testing. 

CRMs are also commonly used in petrochemical analysis, metallurgy, manufacturing, recycling, forensic science, clinical laboratories, and academic research. 

In all of these industries, CRMs help laboratories verify analytical accuracy, monitor instrument performance, and maintain confidence in reported results. They are a fundamental part of all QA/QC systems and help ensure analytical data is consistent, reliable, and traceable. 

Matrix matching refers to selecting a CRM that closely resembles the composition and physical characteristics of the samples being analysed. 

A matrix-matched CRM behaves similarly to routine samples during sample preparation, digestion, and instrumental analysis. This is important because different sample types can respond differently during analytical testing, potentially affecting recovery and accuracy. 

For example, iron ore samples are best monitored using iron ore CRMs rather than unrelated geological materials. Similarly, sulphide ores, bauxites, laterites, and concentrates may each require CRMs with similar mineralogy, particle size and chemistry. 

Matrix-matched CRMs are particularly important for complex analytical methods, trace-level analysis, and difficult sample matrices where matrix effects may influence results. 

Using an appropriate matrix-matched CRM helps laboratories better assess analytical bias, digestion efficiency, and overall method performance under real operating conditions. 

In mining and exploration, selecting the correct matrix-matched CRM helps improve the reliability and relevance of QA/QC monitoring programs. 

Synthetic CRMs are manufactured materials designed to contain specific analyte concentrations or chemical compositions. Unlike natural geological CRMs, they are created by blending high-purity compounds or carefully controlled ingredients. 

Synthetic CRMs are valuable because they allow producers to target specific element levels, analyte combinations, or concentration ranges that may be difficult to source from natural materials. They are commonly used for trace-level analysis, method validation, calibration verification, and specialised laboratory applications. 

And as their composition can be tightly controlled, synthetic CRMs exhibit excellent homogeneity and consistency. This makes them particularly useful for monitoring instrument performance and analytical precision. 

While natural matrix-matched CRMs are often preferred for routine geological QA/QC, synthetic CRMs can provide improved analytical checks and support for specialised analytical techniques and quality control requirements. 

The best choice depends on the analytical method, sample type, and the objectives of the laboratory QA/QC program. 

The key difference between crushed and pulverised CRMs is simply the particle size. 

Crushed CRMs contain coarser material, usually less than 5mm,  and are designed to more closely resemble samples encountered earlier in the preparation process. They are often used to monitor crushing, splitting, and pulverising stages within laboratories or preparation facilities and also for PhotonAssay or PAL (Pulverise and Leach) gold analysis which utilises coarse crushed samples.   

For PhotonAssay and PAL, crushed CRMs give better much representation as exactly the same physical matrix and particle size are being tested as the field samples. 

Pulverised CRMs are ground to a very fine particle size, less than 54 microns, similar to the final pulp submitted for chemical analysis. These materials are primarily used to monitor analytical accuracy of techniques such as fire assay, XRF and ICP-MS. 

Crushed CRMs can help identify contamination, segregation, preparation bias, and coarse gold effects that may not be detected using fine pulverised materials alone.  

Pulverised CRMs are generally more homogeneous and are widely used for routine analytical QA/QC. 

Crushed CRMs are typically used to monitor the sample preparation stage of laboratory or plant workflows. 

Because they contain coarser particles, crushed CRMs behave more like real field or plant samples during crushing, splitting, drying, and pulverising. This helps laboratories and mining operations assess whether preparation procedures are introducing contamination, segregation, or preparation bias. 

Crushed CRMs are especially useful in gold applications where coarse gold effects may occur, as fine pulverised CRMs may not fully represent the behaviour of coarse mineralisation. 

They are also well suited to analytical methods that analyse larger crushed aliquots directly, such as PhotonAssay and PAL (Pulverise and Leach) systems, where matching the physical matrix and particle size of field samples is important. 

In reverse circulation (RC) drilling programs, crushed CRMs can better mimic the particle size and physical behaviour of real RC samples, improving the relevance of QA/QC monitoring. 

Another advantage is that crushed CRMs can often be submitted anonymously to laboratories, reducing the likelihood that technicians immediately recognise them as highly homogenised QA/QC materials. 

While pulverised CRMs are generally preferred for routine analytical QC, crushed CRMs provide additional confidence that the sample preparation stage itself is operating correctly. 

Many QA/QC programs use both crushed and pulverised CRMs to achieve more complete process monitoring.

Whether a CRM should be dried before use depends on the material type, analytical method, and the instructions provided on the CRM certificate. 

Users should always follow the instructions supplied with the CRM certificate and maintain consistent handling procedures throughout the analytical process. 

Some CRMs are certified on an “as-received” basis and should be used exactly as supplied. Drying these materials may alter moisture content or chemical composition and could affect the certified values. 

Other CRMs may require drying to align with specific laboratory methods or reporting bases. In these cases, recommended drying temperatures and handling procedures are usually provided by the CRM producer. 

Improper drying can potentially cause oxidation, moisture loss, volatilisation of certain elements, or physical changes to the material. 

Avoiding contamination is absolutely essential for maintaining the integrity and reliability of a CRM. 

CRMs should always be handled using clean tools and equipment. Spatulas, scoops, and sampling surfaces should be cleaned thoroughly between uses to prevent cross-contamination. 

Unused material should never be returned to the original jar, as this can introduce contaminants or moisture. CRM containers should only be opened when required and resealed immediately after use. 

Exposure to excessive humidity, dust, chemicals, or laboratory fumes should also be minimised. Gloves may be appropriate when handling sensitive materials. 

For pulverised materials, excessive shaking or rough handling should be avoided, as segregation of fine particles may occur. 

CRMs should always be stored according to the conditions specified on the certificate or product documentation. Following good laboratory practices helps ensure the CRM remains representative and reliable throughout its usable life. 

Quality control programs in mining and laboratory analysis commonly use multiple CRM levels to monitor analytical performance across different concentration ranges. 

For example, laboratories may use low-grade, medium-grade, and high-grade CRMs to ensure that analytical methods remain accurate throughout the expected sample range. This helps identify issues that may only become apparent at certain concentration levels. 

Different CRMs may also be selected for different commodities, matrices, or analytical methods. Some QA/QC programs rely on matrix-matched geological CRMs, while others incorporate synthetic standards or trace-level materials for specialised applications. 

CRMs are commonly used alongside blanks, duplicates, and check samples to provide a comprehensive assessment of laboratory performance. 

An effective QA/QC program is designed to detect analytical bias, contamination, preparation errors, and instrument drift before they affect important datasets. 

Selecting appropriate CRM levels and insertion rates is an important part of building a reliable and meaningful quality control system. 

Custom: We manufacture custom CRMs to the exact specifications of our clients. Catalogue: CRMs we hold pre-existing stock for and you can buy immediately based on specification.

We are the only company in the world with the ability to manufacture custom Crushed or Pulverised materials across different commodity classes.

Selecting the right CRM requires matching three key parameters to your project: analytical method, target grade range and commodity.  Consideration also should be made regarding the stage of the project – exploration, resource measurements, or in operation.

Start by identifying the primary analytical method your laboratory will use a e.g. fire assay, photon assay, XRF, mixed acid digest ICP etc., and the elements of interest, as this determines what type of CRM is technically appropriate. Methods that analyse a crushed sample, such as photon assay, should use a crushed CRM.

Next, define the grade range you expect to encounter across your sample suite. In practice, most programs require at least two or three CRMs spanning low, mid, and high-grade ranges. A single CRM inserted at one grade point tells you very little about laboratory performance across the full analytical range.

Finally, consider the properties of your actual ore. A CRM prepared from material that is similar geochemically to your deposit will expose problems that a generic standard will not.

CRM grade selection should reflect the geological and operational context of the program and the method you are using for analysis

As a general guide:

• Exploration programs: Focus on the low-level grades so QC can detect false positives. Maintain some higher-grade CRMs if exploration trends are likely to extend.  Remain flexible with supply of different grade level CRMs in case the situation changes during the exploration program and targets change.
• Resource definition and mine geology: Grade control becomes more critical at this stage. CRMs should bracket the economic cut-off grade closely, with at least one CRM positioned at or near the cut-off itself, where classification and reporting decisions are most sensitive.
• Metallurgical and concentrate samples: These require CRMs appropriate to the much higher grades involved. Standard exploration-grade CRMs are not suitable and will not provide meaningful QC data at elevated concentrations.

A common mistake is using a single mid-grade CRM and assuming it covers the program. However, bias or drift may only manifest at certain grade levels so using multiple CRMs is the only way to detect grade-dependent analytical problems.

As closely as practical. The matrix of a CRM, i.e., its overall chemical and mineralogical composition, directly affects how well it will be digested in the lab and the instrument response, particularly inter-element interferences. If you are in ground with unknown mineralogy, match the grades and overall chemistry as a priority

For most base and precious metal programs, a CRM sourced from a geologically similar deposit type (orogenic gold, BIF, IOCG, pegmatite, ultramafic-hosted nickel etc) provides adequate matrix matching.

For technically complex ores such as refractory gold, complex polymetallic sulphide systems, rare earths, or deposits with unusual gangue mineralogy, matrix matching becomes substantially more important. In these cases, it is worth investing in CRMs specifically certified for your ore type, or engaging a CRM supplier to have custom made CRMs produced.

It is worth noting that perfect matrix matching is rarely achievable, and CRM certification itself requires sufficient material homogeneity across a large, prepared batch. The practical goal therefore is to use the closest available match and to be aware of any divergence between the CRM and your ore matrix.

Gold exploration programs analysed by fire assay should use fire assay-compatible CRMs which are typically fine-grained pulverised materials certified for 30g or 50g fire assay charge weights. The CRM particle size and mass submitted should be appropriate for the fire assay method in use.

For free-milling gold deposits, standard commercially available gold CRMs are generally suitable. For refractory ores (gold locked in sulphides or carbonaceous material), it is important to use a CRM prepared from genuinely refractory material. A free-milling CRM will not expose incomplete liberation or poor fusion efficiency that may be affecting your actual sample suite.

Coarse gold deposits present a particular challenge — see the separate FAQs below.

Coarse, or nuggety, gold deposits may seem to present a fundamental QC challenge rooted in the nugget effect.

When gold occurs as random, discrete coarse particles rather than fine disseminated grains evenly distributed through the sample, the probability of a sub-sample containing a gold particle is highly variable, and no amount of careful sample preparation fully eliminates this variability at typical fire assay charge weights. The solution, however, is not to use a “nuggety” CRM!  The CRM should still have sufficient homogeneity to assess the validity in the analysis and provide confidence.

For coarse gold programs, one approach is to focus quality control effort on:

• Coarse duplicate sampling (field duplicates, crusher duplicates) to quantify the magnitude of the nugget effect in your specific ore.
• Use of blanks to monitor contamination during preparation of high-grade material.
• Fine-grained gold CRMs to check laboratory performance on the dissolved fraction, accepting that the primary source of variability is sampling rather than analytical.

Recognising and documenting the nugget effect is more useful than attempting to use a CRM that cannot be properly certified for this style of mineralisation.

Conventional fire assay typically analyses use 30g or 50g charges and so the result becomes highly variable depending on whether a gold particle happens to be included in that aliquot.

A better approach may be to use a different analytical technique such as PhotonAssay or PAL (Pulverise and Leach) which makes use of at least 400g and up to 1kg aliquots of crushed material for analysis.

Crushed Gold CRMs are ~3mm rock chips specifically produced using our patent-pending, in-house manufacturing process.

Engineered specifically for large mass analytical methods like PhotonAssay™ and PAL, they are the only CRMs designed for these laboratory techniques. They are certified and matrix-matched to routine samples.

Quality control programs for laboratory analysis rely on treating certified reference materials (CRMs) identically to routine samples. Matching the physical and chemical characteristics, method of use, and handling in all laboratory processes for both CRMs and routine samples develop superior confidence in the results.

Pulverised CRMs have been used for PhotonAssay™ and PAL, but they behave adversely compared to crushed samples. To solve this issue, CrushedCRMs™ have been developed as the essential quality control material for these laboratory. methods.

Produced under our 17034 accreditation, we guarantee the inter-comparability of measurement results worldwide and the highest level of quality assurance that an accredited impartial manufacturer can obtain.

The Chrysos PhotonAssay technique uses a large sample mass (typically 500g) with a coarse grain size (minus 2-3mm) and X-ray fluorescence. High-energy gamma rays are fired at the sample to “excite” gold atoms, causing those atoms to emit their own characteristic energy signal, which can then be measured and quantified.

This sample format is fundamental incompatibility with standard pulverised CRMs, which are produced in small particle sizes and are not appropriate for a 500g bulk measurement of a crushed sample. Specially designed CRMs for PhotonAssay available from IMS should be used in this instance.

Utilising pulverised CRMs for a crushed method such as PhotonAssay is not ideal and is generally not recommended. Pulverised CRMs submitted as a 500g mass of fine powder do not represent the physical crushed form of the ore being measured. The non-destructive X-ray method is sensitive to the consistency and stability of particles packed in the analysing jar. Density variations within and between jars can be difficult to control with pulverised materials particularly when they are repeatedly analysed and subject to sever mechanical stresses.

For fit-for-purpose QC in PhotonAssay programs, crushed CRMs prepared and certified for the relevant submission mass are strongly preferred.

Copper-gold deposits require CRMs certified for both gold and copper, usually from a sulphide-bearing matrix comparable to your ore. The interaction between gold and copper during fire assay, particularly where high copper concentrations may affect the assay, means that a CRM carrying both analytes at representative grades provides better diagnostic value than separate gold-only and copper-only standards.

For the gold component, ensure the CRM is compatible with your fire assay method and charge weight. For the copper component, check that the CRM grade range covers your expected Cu distribution. High-grade copper intervals may require a separate CRM at elevated copper levels if the standard range CRM does not capture the upper tail of your data.

Iron ore QC programs typically involve XRF analysis for major elements (Fe, SiO₂, Al₂O₃, P, S, Mn, TiO₂) and multi-point loss on ignition (LOI). The CRM selection should be certified to cover all the analytical requirements.

• Use multi-element iron ore CRMs certified for the full suite of elements measured, not just total iron. Ensure the value are for fused bead digestion method, so the results are total and reliable.
• LOI at 1050°C is a critical parameter in iron ore QC. Correct evaluation of loss for the same CRM as the chemical analysis can ensure no significant components are missing in the analysis as all results should total to 100% for these methods.
• Thermo-gravimetric analysis (TGA) at multi-point temperatures is also important where mineralogical speciation is required. Ensure the CRMs have intermediate values at the correct temperature, such as 371°C or 425°C for goethite and 650°C for kaolinite dihydroxylations.
• Iron ore is hygroscopic — adsorbed moisture can affect XRF and LOI measurements and introduce variability. For programs where hygroscopic moisture is analytically significant, CRM handling and storage conditions should be controlled accordingly. Otherwise, ensure the CRM is dried in the same way as the samples prior to analysis. Check the certificate text as most CRM manufacturers, including IMS, will certify XRF and LOI analysis on a dry basis.
• Calibration standards for XRF should ideally span the full range of expected values as a multi-point calibration. A single-point CRM at one grade level is insufficient for a full XRF suite.

Iron ore deposits vary considerably in mineralogy, and this affects analytical behaviour. The three primary ore types requiring different CRM considerations are:

• Hematite ores: the most common direct shipping ore type. Standard iron ore CRMs are widely available for hematite-dominated systems.
• Goethite-rich ores: goethitic iron ores typically carry higher LOI values due to structurally bound water. CRMs for goethite-bearing systems should have certified LOI and TGA values reflecting this, and LOI behaviour during ignition should be verified against expected ranges.
• Magnetite ores and concentrates: magnetite programmes frequently produce high-grade concentrates requiring CRMs at significantly elevated iron grades. Additionally, if magnetite concentrates are produced, negative LOI values (oxidation of Fe2+ to Fe3+ during ignition) may be relevant, and CRM certification should cover this range.

Matching mineralogy is particularly important where LOI is a key product specification parameter. Using a haematite CRM on a magnetite-concentrate program, for example, will not provide meaningful QC data for LOI behaviour.

At times minor elements are important when selecting CRMs.  Penalty elements such as Mn, P and S are important for end user requirements, while alkalis along with Cl can provide information about samples below water table.

Particle size selection should be fit for purpose and matched to the analytical method. Particle size control during manufacture of CRMs is a critical parameter as it drives homogeneity.  As such, the grind size is dependent on the mineralogy of the CRM (distribution of elements of interest), and the analytical method aliquot size.

For fire assay, with a 50g charge, most CRMs are pulverised to a nominal -105µm (150 mesh) or finer specification, which is appropriate for fire assay.

For ICP dissolution, and most XRF applications, aliquot masses vary from 0.1 to 5g, and as such most CRMs are pulverised to a finer specification such as -53µm (300 mesh).

However, there are practical considerations at both ends of the particle size spectrum:

• Very fine CRMs (high proportion passing 32µm or finer) can exhibit handling effects such as electrostatic behaviour, agglomeration due to high surface area, poor flow properties, and difficulty achieving consistent sub-sampling. These issues can introduce variability that is not a reflection of laboratory performance.
• Coarser CRMs may have implications for homogeneity as the ability to sub-sample a consistent aliquot from a batch becomes more difficult as particle size increases. CRM certification tests homogeneity explicitly, but coarser materials carry inherently greater sub-sampling uncertainty.

Always check the certified particle size specification and confirm it is compatible with your analytical method and the mass being submitted.

The size specification varies by manufacturer, CRM type and laboratory method.

Most commercially available pulverised CRMs are prepared to a nominal 75µm (P80 or P90 passing) specification.

Some CRMs are prepared to finer specifications (e.g. -53µm or -45µm) for applications where small masses are analysed, and more complete dissolution is required.

Always refer to the CRM certificate of analysis or product data sheet for the specific particle size specification, as this is a certified parameter.

The mass submitted should be sufficient for the primary analytical method, with enough remaining for at least one repeat analysis if required.

Understanding how your laboratory batches their samples is important as different analytical methods have different minimum charge weights, and submitting less than the method requires will invalidate the QC result.

Below are some indicative mass requirements by method:

• Multi-element methods such as XRF and ICP: Typically, a 0.1g to 1g analytical aliquot is used. A 10g CRM sachet is usually submitted in these cases.
• Fire assay (FA): Standard 30g or 50g charge. The CRM mass submitted should match the standard charge weight as submitting a partial charge invalidates the fire assay result. A 60-100g CRM sachet is usually submitted in these cases.
• PhotonAssay (PA): Normally requires 500g or more of material. Standard pulverised CRMs are not suitable for PhotonAssay — see the specific PhotonAssay FAQ. IMS PhotonAssay CRMs are provided already pre-packed ready in a jar so there is no need to be concerned by the mass in this case
• PAL cyanidation assay: Method-specific charge weights apply but are usually 500g-1kg. Consult your laboratory for the required mass and confirm CRM compatibility with the leach procedure. IMS PAL CRMs are packaged in 500g bags ready for single shot QC use.

An important point: Always check the certified minimum sub-sample mass specified on the certificate. Submitting below this mass risks non-representative sampling and introduces uncertainty that is not accounted for in the certified uncertainty budget.

Yes, without exception.

A single CRM at one grade level monitors laboratory performance only at that specific concentration. Analytical bias, calibration errors, and method-specific problems frequently manifest differently across the grade range — a laboratory may perform acceptably at mid-grade while showing systematic bias at low or high grades.

As a minimum, most programs should include:

• A low-grade CRM: positioned below the expected average grade or near the lower limit of economic interest. This monitors performance in the region where detection limit proximity and low-level accuracy are most critical.
• A mid-grade CRM: positioned near the expected average grade of the sample population or cut-off grade. This is the most representative QC check for the bulk of your data.
• A high-grade CRM: positioned at or above the expected upper grade range or economic cut-off. This monitors performance where high-grade intercepts have the most influence on resource estimates and mine planning decisions.

Where a program has a clearly defined cut-off grade, positioning one CRM at or near that cut-off is strongly recommended, as this is the grade range where classification decisions are most sensitive to analytical error.

Understanding how your laboratory processes samples is important before designing your insertion protocol.

Most laboratories work in fixed batch sizes — fire assay is commonly batched in 50-pot or 84-pot configurations, and insertion rates should be designed with laboratory batch size in mind.

A practical guide for insertion frequency is listed below:

• A minimum insertion rate of 1 CRM per 20 samples is widely used as a baseline in exploration programs — this equates to approximately 5% QC.
• For resource definition drilling or grade control, higher insertion rates of 1 in 10 (10%) are common.
• Where multiple CRM grades are being used, rotate them through the batch so that each grade level is represented regularly rather than clustering all CRMs of one type together.

Coordinate with your laboratory to understand their batch or rack structure. Inserting CRMs at positions that fall at the beginning, middle, and end of a fire assay batch, for example, provides better coverage of potential within-batch drift than random placement.

CRMs and blanks serve different but complementary QC functions and should be used together.

CRMs monitor analytical accuracy and bias — they tell you whether the laboratory is returning the correct value. Blanks monitor contamination, particularly during sample preparation — they tell you whether material from a previous sample is carrying over into subsequent samples.

The placement of blanks is important. Blanks should be submitted as low-grade or near-zero grade material inserted immediately after high-grade samples or known mineralised intervals. The purpose of a blank is to detect contamination during sample preparation and analysis. Ideally, a blank should contain:

• negligible concentrations of the target analytes
• minimal contamination risk
• physical properties reasonably compatible with the preparation process.

Blanks can themselves be a source of contamination if not handled correctly. A blank submitted after a high-grade sample will pick up contamination which is the intended function. However, the elevated blank result represents material that may also have been carried forward into the next sample in sequence.

As such, consideration of the type of blank should be made.  Insertion of quartz or calcium carbonate blanks throughout an iron ore sample preparation program risks more contamination from the blank to the samples than the benefits of detecting iron ore in the blank.  In this case, a crushed iron ore CRM performs both as blank and CRM.  When coupled with pulverised CRMs submitted after sample preparation, any difference in analytical performance in the crushed CRM compared to the pulverised CRM indicates there have been issues in sample preparation.

A blank that returns an elevated value may indicate preparation contamination, most commonly from incomplete cleaning of crushing or pulverising equipment between samples.

Blanks can also be strategically inserted after high grade samples to protect contamination in the next sample, while providing a measurement of the carry-over expected from routine laboratory operations.

Therefore, when reviewing blank data, consider not just whether the blank has failed, but what the contamination implications are for the sample immediately following the blank in the preparation sequence. A blank only tells you contamination has occurred — it does not tell you exactly where contamination entered the workflow. Interpretation still requires understanding the preparation sequence and laboratory process.

The combination of CRMs (accuracy) and blanks (contamination) provides a more complete picture of laboratory performance than either tool alone.

Yes. CRMs and blanks address different failure modes and neither substitutes for the other. A QC program relying solely on CRMs will not detect preparation contamination. A program relying solely on blanks will not detect analytical bias or calibration drift. A robust QC program incorporates both, along with field duplicates or preparation duplicates to monitor sampling precision.

As a working framework:

• CRMs: inserted at regular intervals throughout the batch to monitor analytical accuracy across the grade range.
• Blanks: inserted after high-grade samples or mineralised intervals to monitor preparation contamination.
• Duplicates (field or preparation): inserted to monitor sampling precision and preparation reproducibility, distinct from the accuracy and contamination checks provided by CRMs and blanks.

Together, these three QC tools provide a defensible, comprehensive quality assurance framework appropriate for programs operating under JORC, NI 43-101, SAMREC, or equivalent reporting codes.

Custom: We manufacture custom CRMs to the exact specifications of our clients. Catalogue: CRMs we hold pre-existing stock for and you can buy immediately based on specification.

We are the only company in the world with the ability to manufacture custom Crushed or Pulverised materials across different commodity classes.

Our flexible system allows us to produce custom batches from small to 20 tonnes.

Pilbara Standards was the original name of IM Standards. Set up in 2012 it became the world’s leading supplier of iron ore certified reference materials. 

In 2021 we rebranded to Independent Mineral Standards, to better reflect the growing breadth of our product range and our focus on certified reference materials across multiple commodities.

The certificate is the primary reference document for a certified reference material. It contains all the information needed to use a CRM.

There are two broad categories of information in a CRM certificate.

Firstly, headline data.  This includes the certified values for each analyte — the concentration or analytical result that has been rigorously established — together with the associated uncertainty. These are the values you will use most directly in your QA/QC program.

Supporting information on the certificate describes the material itself: its matrix, particle size, preparation method, and any processing steps conducted. It identifies the analytical methods used during certification, the number of participating laboratories, and the statistical approach used to derive the certified values. Minimum sample mass, storage conditions, and expiry or stability information is also provided.

It is recommended to read the certificate in full before use. The headline values are only meaningful in the context of the supporting information — particularly the minimum sample mass, the analytical methods to which values apply, and any conditions attached to informational-only values.

The statistical values on a CRM certificate quantify how well the certified values are known and the range of results you should expect when using the material.

• The certified value is typically the mean of results from multiple independent measurements, often across multiple laboratories. It represents the best estimate of the true value for that analyte in that matrix. The true concentration or value, however, remains unknown within a statistically determined confidence interval.
• Standard deviation statistics on the certificate are common terms that describe the variability observed during the certificate process. Where both within-laboratory and between-laboratory (global) standard deviations are reported, they reflect different sources of variability that are relevant to different aspects of QA/QC program design. Standard deviations are commonly used within a laboratory QAQC programs to test analytical accuracy and bias.
• The uncertainty describes the range within which the true value is expected to sit. It is usually expressed as “expanded” uncertainty, which basically refers to the “margin of doubt” around a certified value. Expanded uncertainty indicates how confidently the certified value is known. It is not simply a measure of laboratory precision; it incorporates contributions from the measurement process, the analytical method, and the properties of material itself including short- and long-term stability.

When a laboratory repeatedly analyses the same CRM, the results won’t be identical every time. Small variations are normal. Standard deviation is a measure of the spread of a set of determinations around their mean.

One standard deviation (1SD) defines a range that, for a normal distribution, 68% of all results are expected to lie within. To calculate 2SD, multiply the standard deviation value by 2. To calculate 3SD, multiply by 3. These 2D and 3D ranges are broader and contain 95% and 99.7% of results, respectively.

Example: if a CRM has a certified value of 1.50 g/t Au and a standard deviation of 0.05 g/t:

• 1SD range: 1.45–1.55 g/t. 68% of the population of results are expected to be within this range
• 2SD range: 1.40–1.60 g/t. 95% of the population of results are expected to be within this range
• 3SD range: 1.35–1.65 g/t. 99.7% of the population of results are expected to be within this range

The SD value to use for these calculations depends on the purpose of your QA/QC program.

In a QA/QC program, 2SD and 3SD control limits define the warning and action thresholds for CRM performance- they can be thought of as QA/QC traffic lights:

These thresholds are the basis of standard Shewhart-style control charts widely used in exploration and mining laboratory QA/QC. The specific response protocol should be defined in your laboratory’s QA/QC plan before data collection begins.

Simply, a Shewhart chart turns a series of QC results into a visual check on whether the laboratory process is staying in control. It is a statistical process control chart used to monitor analytical results over time and identify unusual changes in performance.

In a laboratory QA/QC program, a Shewhart chart can be used to plot CRM results against the certified value, usually with a central line representing the expected value and control limits showing the range of expected variation.

As new CRM results are added, the chart makes it easier to see patterns that may not be obvious from a table of numbers — such as a sudden outlier, a sustained shift, or a developing trend.

For example, if CRM results are consistently moving towards the upper control limit, that may warrant investigation even if individual results are still technically within the limits.

Uncertainty is a quantitative expression of the doubt that exists about the result of any measurement. It does not mean error or mistake — it is an inherent property of all measurement, and a well-characterised uncertainty is a sign of rigorous analytical practice.

Uncertainty in CRM certification arises from three main sources, sometimes referred to as the three Ms:

• Measurement uncertainty: variability in the measurement process itself, including instrument precision, instrument condition, repeatability, errors in taking weights and measuring volumes, procedural repeatability and analyst variability.
• Method uncertainty: variations that occur in sample preparation particularly during size and mass reduction, extraction errors, digest extraction efficiency, the instrument calibration model and sample matrix effects.
• Material uncertainty: inhomogeneity within and between units of the CRM, which means that different sub-samples of nominally identical material may not have precisely the same composition, material stability overtime, sub-sampling effects

The combined standard uncertainty (little “u”) integrates these three sources. The expanded uncertainty (capital “U”) is the combined standard uncertainty multiplied by a coverage factor, k, (typically k = 2), which gives a range that contains the true value with approximately 95% probability. It is not simply a measure of laboratory precision; it incorporates contributions from the measurement process, the analytical method, and the behaviour of the material itself.

A value is listed as informational (sometimes called indicative) when the available evidence is insufficient to support full certification.

This may occur for several reasons. The analyte may have been measured by only one method or one laboratory, providing too little independent data to derive a statistically robust certified value. Results across participating laboratories may have shown unacceptably high variability, suggesting the measurement is method-sensitive, or the material is inhomogeneous at the sub-sample level for that analyte. Alternatively, the analyte concentration may be close to detection limits for some methods, making precise characterisation difficult.

Informational values can still be useful — for example, to confirm that a contaminant is present, to describe the matrix with a list of elements of interest, or to provide orientation for method development. However, they should not be used as a primary reference for pass/fail decisions in a QA/QC program. For critical analytes, use only certified values with their associated uncertainty.

Analytical methods are specified on the certificate because the certified values for most analytes are method dependent. A result is only directly comparable to the certified value if the same, or an analytically equivalent, method was used. This is the concept of commutability.  Certificates contain a commutability statement indicating which methods have been applied to the data, and if they are transferrable to any other methods.  Generally, in the case of CRMs for routine QAQC in mining laboratories, the certified values are not commutable. The CRM values are certified only for the methods stated.  Calibration grade CRMs where the total concentration of elements have been determined by special methods can be commutable to alternate methods also determining the absolute concentration of the same element.

Commutability is particularly relevant for analytes subject to partial versus total digestion (gold being the most common example in exploration), for elements with different oxidation states that respond differently to various dissolution techniques, and for volatile or labile analytes where sample preparation conditions affect recovery.

The methods section also provides transparency about how the certification was conducted — how many independent methods were used, whether values from different methods were pooled or reported separately, and whether any method-specific corrections were applied. This information is essential for interpreting the certified value correctly and for deciding whether the laboratory’s method is fit for direct comparison.

Different analytical methods can give different results for the same analyte in the same material because they do not necessarily measure the same thing.

The clearest example is gold. A fire assay with a lead collection (a standard total-gold method) dissolves and collects all gold present in the sample, including gold locked in refractory sulphides. An aqua regia or cyanide digest, by contrast, is a partial dissolution — it extracts soluble or available gold but may not fully liberate refractory or encapsulated gold. The amount of gold recovered is affected by method parameters such as temperature, time and sample particle size. The two methods can give substantially different results for the same sample, and both results can be analytically correct within their own method definitions.

Similar effects occur for other analytes. Trace elements in resistant minerals such as chromite or zircon may dissolve incompletely in acid digestion but fully in a fusion. Sequential extraction schemes designed to identify element partitioning between mineral phases will not necessarily return similar values to a total digest.

When a CRM certificate reports values for the same analyte by more than one method, those values are not in conflict — they reflect genuine method-specific differences in what is being measured. Always confirm that your laboratory’s method matches the method for which the certified value applies.

Global SD (also called between-laboratory SD or inter-laboratory SD) describes the variability of results across all participating laboratories in the certification study. It is always equal to or greater than the within-laboratory SD, because it incorporates both the within-laboratory variation of each participant and the additional variation arising from differences in instruments, calibration standards, reagents, and analytical protocols between laboratories

Within-laboratory standard deviation (also called repeatability SD or intra-laboratory SD) describes the variability of results produced by a single laboratory under consistent conditions. i.e. same instruments, same analysts, same reagents. It reflects the precision of a specific measurement process in a controlled environment.

For QA/QC program design, the choice of which SD to use for control limits depends on context. If you are monitoring the consistency of a single laboratory over time, within-laboratory SD is the more sensitive and appropriate measure. However, if you are comparing results across different laboratories — for example, in a check assay program or an umpire assay scenario — global SD is more appropriate, as it reflects the realistic variability expected between independent analytical environments.

Minimum sample mass is the smallest quantity of CRM that can be used while still producing a result that is statistically representative of the certified value. This limit is generally related to the aliquot size used for the methods of certification, and the unit size of the certified material when undergoing homogeneity testing.  Factors that affect an appropriate minimum sample mass are also particle size distribution and the degree of heterogeneity of the material.

For most fine-pulp CRMs used in exploration and mining — typically ground to 75–150 µm or less — minimum sample masses are in the range of 0.2 to 0.5 g for standard fire assay or digest protocols. Some materials, particularly those with coarse or heterogeneously distributed mineralisation, require larger minimum masses.

The minimum sample mass is always method specific. If the certificate lists different values for different analytical methods, use the value that corresponds to your laboratory’s method. The sample mass used for each method is determine largely by economics, but also industry sub-sampling practice.  Importantly, in any particulate sample, the larger the particles and the more heterogeneous the material, the larger the minimum mass required to ensure that the sub-sample contains a representative proportion of all mineral phases present. This is the basis of sampling theory as formalised by Pierre Gy. For fire assay, laboratories will typically use a sample mass of between 30g and 50g.  Lower sample masses may be used where the sample is deemed to be of sufficient homogeneity to be subsampled (for example a copper concentrate with trace gold).  For most other methods such as mixed acid digests and fusions, sample masses are from 0.2 to 2g.

Note that using less than the minimum recommended mass increases the risk of sub-sampling error, which manifests as inflated analytical variability that cannot be distinguished from genuine laboratory imprecision.

The laboratories therefore balance an acceptable sub-sampling error for the method, with the economics of processing samples.  Certified reference materials should be used according to the method sample size range listed, and these should match the method mass for the samples.

Whether you can subsample a CRM packet depends on the unit size, the particle size of the material, and any instructions provided on the certificate.

For fine-pulp CRMs supplied in sachets or pouches of several grams or more, subsampling is generally acceptable provided the entire packet is thoroughly mixed before a sub-sample is taken, and the sub-sample mass meets or exceeds the minimum sample mass stated on the certificate. Homogenisation by rolling or gentle agitation — but not vigorous shaking, which can cause size segregation — is recommended before subsampling.

Some CRMs are supplied as single-use units sized to deliver exactly one analytical portion. These should not be subsampled, as the unit size has been chosen to ensure that sampling variance is within the bounds established during certification.

The difference between whether a CRM can be sub-sampled to a mass below its unit size depends on the homogeneity/heterogeneity characteristics of the CRM, and their packaged state.

If the certificate includes specific instructions regarding subsampling, those instructions take precedence. When in doubt, contact the CRM producer.

The appropriate sachet size depends primarily on the aliquot size used for the analysis.  and how many analytical portions you need to obtain from each unit. Sufficient material for a repeat analysis should be available.

If you require only a single analytical portion per CRM insertion, which is the most common scenario in routine QA/QC, a single-use sachet sized to deliver one portion or aliquot is the most efficient choice. It eliminates any risk associated with subsampling and ensures each insertion uses a consistent quantity of material.

It is also important to consider storage and handling: once opened, CRM packets should be resealed promptly and stored under the conditions specified on the certificate. For high-humidity environments or materials sensitive to moisture or oxidation, single-use sachets reduce the risk of deterioration between uses.

CRMs are specified to be used within a target mass.  The certified values and uncertainty calculations are based on the typical masses used for each method by multiple laboratories.  If a laboratory uses less than the minimum recommended sample mass sub-sampling errors are introduced — a source of variability that is independent of, and additive to, normal analytical imprecision.

In any particulate material, a sub-sample that is too small may not contain a representative selection of all the mineral phases present.  This is the reason the sachet size should be sufficient to cover a primary, and repeat analysis for the target mass of the method (minimum sachet size = 2x method aliquot)

For a gold CRM, for example, an underweight portion may contain slightly more or fewer gold-bearing particles than the certified value reflects, by chance alone. This produces results that scatter more widely around the certified value than expected, making it difficult to distinguish genuine analytical problems from sampling artefacts.

The practical consequences are twofold. First, your control charts will show apparently elevated variability, which may trigger false-positive failure flags and erode confidence in otherwise sound analytical results. Second, if the poor precision is not recognised as a sampling effect, it may mask real analytical problems that warrant investigation.

If you find that your laboratory consistently uses less than the minimum sample mass — because of instrument constraints, for example — you should work with the laboratory to bring the sample weight into specification.

The mean is the average of all results, while the median is the middle result when values are ranked from lowest to highest. Therefore, the mean is more sensitive to unusually high or low results, whereas the median is more resistant to outliers.

During CRM certification, robust statistical methods are often used to ensure that a small number of unusual results do not unduly influence the certified value.

For most mining CRM certifications today, a robust mean is listed rather than a simple arithmetic mean or a pure median. The certificate will indicate from the data which term is used.  This is essentially a compromise that uses the information in all the data while reducing the influence of outliers. A robust mean prevents one or two unusual results from excessively influencing the certified value.

Consensus values are derived from the combined results of multiple independent laboratories without a single laboratory’s results being treated as the reference.

The most common approach is to calculate the mean (or a robust mean, after removal of statistical outliers) of all results submitted by participating laboratories. Each laboratory analyses the candidate material using its own validated method, and the results are pooled. Outlier identification is typically performed using specific statistical tests, which flag results that are inconsistent with the overall dataset.

Where multiple analytical methods are used and yield systematically different results, values may be reported separately by method, or a weighted consensus may be derived that accounts for method-specific biases. This is common for analytes that are subject to method-dependent extraction.  These values may be considered indicative, or informational on the certificate and should be used with caution for quality control.

The robustness of a consensus value depends heavily on the number of participating laboratories, and the consistency of results across participants for the same method.

Homogeneity is a measure of consistency from sample to sample throughout a CRM batch. In a homogeneous CRM, every jar, sachet, or portion contains the same concentration of the certified analytes, within a stated uncertainty or variance.

Homogeneity is established through statistical testing conducted during the certification process, and the results are either summarised on the certificate or documented in an accompanying technical report.

Homogeneity is always qualified by the sample mass at which it has been demonstrated. A material may be homogeneous at the 50g level but heterogeneous at 1g, because smaller portions sample fewer particles and are more susceptible to local compositional variation (heterogeneity). This is why the minimum sample mass on the certificate is a hard lower bound, not a guideline.

While the homogeneity of a batch of material is commonly determined at the analytical method mass, a better measurement at a lower mass can be determined if the precision of the method allows.  In which case, the homogeneity variance at the method mass for which the certified values have been determined, can be inferred.  A better quality, or more homogeneous, CRM is one that is determined to meet the homogeneity metric at the lower mass.

Homogeneity testing quantifies the variability of composition within and between units of a reference material at a defined sample mass, using replicate analysis and analysis of variance.

The standard approach is to analyse multiple individual units drawn randomly from across the production batch, using a method with sufficient precision to detect compositional differences between units. A method with better precision compared to the certification method is preferred and is a recommendation in ISO 17034. The within-unit variability (i.e. from replicate analyses of the same unit) is compared to the between-unit variability (across different units) using an F-test or analysis of variance (ANOVA).

If between-unit variability is less than the within-unit variability, the material is considered homogeneous for the analyte and unit size tested.

The between-unit standard deviation derived from this analysis is the homogeneity contribution to the material’s overall uncertainty budget.

If between-unit variability is statistically indistinguishable from within-unit analytical noise, the material is classed as homogeneous at that mass and analyte combination.

Heterogeneity tends to be greatest for analytes present at low concentrations, for coarsely ground materials, and for analytes hosted in minerals that are sparsely or irregularly distributed through the matrix.

Within-unit homogeneity refers to the consistency of composition within a single packet, sachet, or bottle of CRM material. It reflects whether different sub-samples drawn from the same unit will give the same result — that is, whether the material is well-mixed and uniform at the scale of the analytical portion.

Between-unit homogeneity refers to the consistency of composition across different units from the same production batch. It reflects whether unit A and unit B from the same batch have the same certified composition — that is, whether the bulk material was uniformly distributed during filling and packaging.

In the case the CRM is sold in a unit that contains multiple analytical aliquots, both types of homogeneity are relevant to the CRM performance. Poor within-unit homogeneity causes high variability between replicate analyses of the same unit. Poor between-unit homogeneity causes systematic differences between units, which may appear as a drift or step-change in control chart results as successive units from different positions in the batch are consumed.

In the case that the CRM is sold in a unit equal to the analytical aliquot, the within unit homogeneity is not relevant.  In fact, some crushed CRMs are designed to be heterogeneous within the unit to mimic real samples that may have a grade bias by particle size, for example.  This is the unique value in crushed CRMs where they are used to assess biases and contamination that may occur during sample preparation.

A box-and-whisker plot is a compact graphical summary of a dataset’s distribution. It displays five key statistics simultaneously, making it useful for comparing analytical results across laboratories or methods immediately.

One of the benefits of these plots is they can simultaneously display accuracy and precision.  Accuracy relates to the location of the box, and precision is related to the vertical span of the box.  Individual outliers can also be displayed as dots.

Box and whisker plots make use of quartiles. A quartile divides a set of ordered data into four equal parts, with each part containing roughly 25% of the observations.

• Q1 (first quartile) — 25% of the data falls below this value.
• Q2 (second quartile) — the median; 50% of the data falls below this value.
• Q3 (third quartile) — 75% of the data falls below this value.

The box spans the interquartile range (IQR) — from the 25th percentile (Q1) to the 75th percentile (Q3) — and contains the central 50% of all results. The line inside the box marks the median. The whiskers extend from the box to the most extreme values that fall within 1.5 times the IQR above Q3and below Q1.  Essentially the box-and-whisker plot displays the distribution of the data vertically.

Data points beyond the whiskers are plotted individually and are considered potential outliers.

In the context of CRM certification, box-and-whisker plots are commonly used to display the distribution of results from all participating laboratories during the characterisation study. They allow rapid visual identification of laboratories or methods that are performing well within the central cluster, those producing systematically high or low results (bias), and those with high internal variability (poor precision). The certified value and its uncertainty range are typically overlaid on the plot for reference.