How to Determine Whether Coal Sample Preparation Equipment Causes Cross-Contamination

Meta Description: Learn how the ABBA trend verification method identifies cross-contamination between coal samples and why equipment residue alone does not necessarily indicate contamination.

Sample contamination is one of the greatest threats to reliable analytical results, and cross-contamination is one of its most common causes. As automated sample preparation systems become increasingly common in coal testing laboratories, the risk of cross-contamination has received growing attention.

For users, the priority is not simply whether the equipment can operate automatically, but whether the resulting data accurately represents the quality of the sample being tested.

Cross-contamination is one of the key factors that can compromise this data integrity.

So, what exactly is cross-contamination? How can we scientifically determine whether sample preparation equipment is causing it?

Drawing on years of research and practical experience in automated coal sample preparation, Sundy Technology explains the issue in clear and practical terms.

What Is Cross-Contamination?

In simple terms, cross-contamination occurs when residue from a previous sample remains inside the equipment, enters the next sample, and affects its analytical result.

For example:

• Sample A has a relatively high ash content.
• Sample B has a relatively low ash content.

If residue from Sample A enters Sample B, the measured ash content of Sample B may be biased high. Conversely, if residue from Sample B enters Sample A, the measured ash content of Sample A may be biased low.

In either case, the result no longer fully represents the true characteristics of the sample currently being tested.

Why Does Cross-Contamination Matter?

Cross-contamination can affect more than an individual analytical result. It may directly influence coal quality assessment and commercial settlement.

Consider two batches of coal supplied by different vendors:

• Sample A: approximately 10% ash
• Sample B: approximately 30% ash

If residue from Sample A is carried into Sample B and accounts for 2% of the mass of Sample B, the measured ash content of Sample B would be approximately 0.4 percentage points lower than its true value.

This deviation could directly affect trade settlement.

In coal trading, parameters such as ash content, moisture content and calorific value are often directly linked to price. Even a seemingly small analytical bias can have a significant economic impact when large quantities of coal are involved.

Cross-contamination may appear to be only a minor residue issue inside the equipment, but it is fundamentally a matter of analytical data integrity and reliability.

Residue Is Not the Same as Cross-Contamination

When discussing cross-contamination, many people immediately focus on sample residue.

However, residue and cross-contamination are not equivalent.

During mechanical sample preparation, coal passes through multiple operations, including:

• Crushing
• Sample division
• Conveying
• Material transfer

A small amount of sample adhesion, retention or residue is an unavoidable physical phenomenon.

In other words, some residue inside the equipment is normal and, to a certain extent, inevitable. Just as a perfect vacuum does not exist in nature, completely residue-free mechanical sample preparation is not realistically achievable.

The real question is not whether residue exists.

The real question is:

Does residue from the previous sample affect the next sample?

That is the essential criterion for determining cross-contamination.

Note on Sample Residue

In this article, “residue” refers to small traces of sample material adhering inside the equipment during normal operation. The amount remains within an acceptable range and does not cause significant sample mass loss.

Relevant standards specify limits for sample loss during sample preparation, such as a total system sample-loss rate of no more than 2.0%. Compliant sample preparation equipment must meet these requirements.

Cross-contamination and sample loss are two separate concepts.

What Problem Does Sundy Address?

The issue is not residue itself, but whether the previous sample affects the next one.

Through long-term research, Sundy has found that not all residue causes cross-contamination.

Cross-contamination is caused specifically by residue that can be dislodged by a subsequent sample, carried through the equipment and incorporated into the next prepared sample.

To address this problem, Sundy uses a current-sample flushing and displacement technique.

The principle is straightforward: the current sample itself is used to displace any remaining material from the previous sample inside the equipment.

Residue belonging to the previous sample is therefore replaced by material from the current sample. Even if some residue remains inside the equipment, it now consists of the current sample and no longer causes the previous sample to affect the next one.

The key issue is not whether the equipment contains residue, but whether residue from the previous sample can enter the subsequent sample.

The objective is therefore not to pursue an unrealistic state of zero residue. Instead, current-sample flushing and displacement converts previous-sample residue into current-sample residue, preventing interference between consecutive samples.

How Can Cross-Contamination Be Verified?

Based on extensive research, Sundy has developed a simple and intuitive verification procedure known as the ABBA Trend Verification Method.

First, prepare two samples with clearly different ash contents.

An ash-content difference of at least 15 percentage points is recommended. A difference of 30 percentage points or more makes the cross-contamination trend easier to identify.

• Sample A: high-ash reference sample
• Sample B: low-ash reference sample

Before beginning the formal verification test, either:

• Thoroughly clean the inside of the equipment; or
• Process one of the samples, such as Sample A, several times until the residual condition inside the equipment becomes stable.

The samples are then processed continuously in an ABBA sequence.

Recommended Test Sequence

A → B → B → A → A → B → B → A → A → B → B …

Multiple ABBA cycles should normally be completed so that any recurring trend becomes easier to identify.

What Trend Indicates Cross-Contamination?

If residue from the previous sample affects the subsequent sample, the following trend may appear:

A⁰ → B⁺ → B⁰ → A⁻ → A⁰ → B⁺ → B⁰ → A⁻ …

The symbols represent the following conditions:

• 0: The sample is not affected by the preceding sample, and its ash result remains normal.
• +: The sample is affected by the preceding sample, and its ash result is biased high.
• −: The sample is affected by the preceding sample, and its ash result is biased low.

The method evaluates adjacent samples to determine whether the preceding sample influences the next one.

For example, if the ash content of the first B sample is consistently higher than that of the second B sample, the first B sample may have been affected by high-ash residue from the preceding A sample.

Similarly, if the first A sample after Sample B consistently gives a lower ash result than the second A sample, it may have been affected by low-ash residue from Sample B.

The symbols 0, + and − do not represent specific analytical values. They illustrate the expected direction of the bias caused by cross-contamination.

The primary value of the ABBA method is therefore not any individual result. Its purpose is to determine whether a consistent and repeatable trend appears over multiple test cycles.

If repeated cycles consistently show that:

• The first B sample is biased high; and
• The first A sample is biased low,

then the previous sample is influencing the subsequent sample, indicating interference between samples.

The ABBA method is fundamentally a trend-based assessment method.

Key Requirements for the ABBA Verification Method

1. Use an Identical Preparation Procedure for Both Samples

Both samples should undergo exactly the same preparation procedure. This minimizes differences introduced during sample preparation and prevents such differences from interfering with the trend assessment.

Based on long-term testing, Sundy recommends that the two comparison samples have a nominal top size of no more than 13 mm.

Each sample should be homogenized by passing it through a riffle splitter at least three times. It should then be divided into two equal portions using the same riffle splitter.

Strict control of this procedure minimizes variation between sample portions and improves the reliability of the cross-contamination assessment.

2. Use Samples With a Sufficient Difference in Ash Content

The difference between Samples A and B should be at least 15 percentage points. A difference of 30 percentage points or more is preferable.

When the ash contents of Samples A and B are too similar, the effect of cross-contamination may be masked by natural sample variability and analytical uncertainty.

For example:

• With an ash-content difference of 15 percentage points, a 2% carryover by mass would produce an analytical bias of approximately 0.3 percentage points.
• With an ash-content difference of 30 percentage points, the same 2% carryover would produce a bias of approximately 0.6 percentage points.

At the larger difference, the resulting trend becomes considerably easier to identify.

Conclusion

When evaluating cross-contamination, the most important question is not:

Is there any residue inside the equipment?

The correct question is:

Does the previous sample affect the next sample?

The value of the ABBA Trend Verification Method lies in converting a complex technical issue into a clear and observable trend.

At the same time, current-sample flushing and displacement prevents sample-to-sample interference by converting previous-sample residue into current-sample residue.

Sundy Technology has long been involved in the research and practical evaluation of cross-contamination in automated sample preparation systems. The company has also actively supported the standardization of relevant assessment methods.

Through joint efforts across the industry, this evaluation method has been incorporated into the national standards framework, providing a unified basis for assessing cross-contamination in coal sample preparation.

Sundy Technology will continue working with users, research institutions and industry partners to advance automated sample preparation technology and strengthen the integrity and reliability of coal testing data.