Here is the hard truth: in most cases, the material is fine. The instrument is fine. The problem is a misunderstanding of what FTIR matching actually measures, and it is costing pharmaceutical QC labs hours of unnecessary retesting, false rejections and eroded confidence in a technology that is genuinely excellent at its job.

This article unpacks the three real causes of low match scores, what FTIR can and cannot tell you, and how to build a workflow that turns your spectrometer into the trusted identification workhorse it was designed to be.

Why does my FTIR keep giving me low match scores?

Walk into most pharmaceutical QC labs and you will see some version of the same frustration. A technician places a powder loosely on the diamond crystal, presses the plunger halfway down, gets a poor match score and logs it as a suspected material failure. After years of working alongside QC teams across hundreds of laboratories, the Chemetrix team can tell you that this scenario almost always comes down to one of three things.

Poor ATR crystal contact: Infrared light only penetrates a few micrometres into the sample surface. Air gaps or inconsistent pressure mean the evanescent wave never reaches the material properly, producing a weak and noisy spectrum that will not match any reference cleanly.

Generic reference libraries: Most labs rely on commercial libraries built from a single reference sample under ideal conditions. When your actual material arrives with slight batch variation, a different particle size or minor additives, it will not match that idealised reference, even if it is exactly the right material.

Misplaced expectations: A match score measures similarity under the conditions of measurement. It is not an absolute verdict on material identity. Even a correct material from the correct supplier can return a score well below 100% if technique or library quality is off.

The good news is that all three of these problems are fixable.

What is FTIR actually measuring?

FTIR spectroscopy works by focussing on infrared light at a sample and measuring which wavelengths the material absorbs. Every compound has a unique pattern of absorption peaks, its molecular fingerprint. The ATR (attenuated total reflectance) method makes this fast and practical by bouncing the infrared beam off a diamond crystal in contact with the sample, requiring no preparation beyond placing the material on the sensor.

Library matching then compares your sample’s fingerprint to a reference spectrum using a mathematical correlation algorithm. The result is a match score, not a binary yes or no,
but a measure of how similar the two spectra are under the conditions of that measurement. Importantly, standard library search methods are designed to detect differences in the 5 to 10% range between a sample and its reference, which means some variation is expected
and entirely normal.

This is a critical distinction. Natural spectral variation occurs between batches of the same material due to:

• Moisture content and surface effects
• Particle size differences between suppliers or manufacturing runs
• Trace additives or stabilisers that are entirely acceptable within specification

None of these make the material wrong. But all of them will affect your match score if your reference library was not built to account for them.

Here is the insight that changes everything:

Most importantly, the Cary 630 runs Agilent MicroLab software, a method-driven and pictorial interface that makes building site-specific libraries an intuitive task rather than a data science project. MicroLab supports advanced classification methods including PLS-DA (partial least squares discriminant analysis). In published testing using the Cary 630 with MicroLab, a PLS-DA method achieved 100% correct classification of pharmaceutical samples and detected contaminants at levels as low as 0.5%. Results are displayed as colour-coded pass/fail indicators and automatically logged in 21 CFR Part 11 compliant audit trails.

This is what Chemetrix calls the Golden Reference Library: a site-specific and validated collection of spectra that reflects your materials, your suppliers and your real-world conditions. Not a generic database. Yours.

What challenges do manual workflows present during peak testing periods?

How can automation help labs overcome throughput bottlenecks?

Why is automation crucial for South Africa’s diverse testing requirements?

What are the specific benefits of Raykol’s automated SPE systems during festive peaks?

Raykol’s automated SPE systems

Ready to transform your lab’s festive season workflow?

✅ TL;DR – Key Takeaways

• December is the peak testing season for South African labs across multiple industries.
• Manual prep workflows cause delays, errors, and staff fatigue during high volumes.
• Automation with Raykol SPE systems accelerates prep, boosts throughput, and ensures consistent results.
• Lab automation frees scientists to focus on data interpretation and innovation.
• Essential for labs handling diverse testing needs to stay competitive and compliant.

 

Why is PFAS detection in textiles so difficucon

• Be present in ultra-trace amounts
• Be embedded in complex synthetic fibres
• Require extensive and delicate preparation before testing

• Delays in turnaround times
• Inconsistent results
• Potential non-compliance with regulations

Automation is transforming textile PFAS testing

• Faster processing of large sample volumes
• Minimised manual intervention
• Higher consistency and reproducibility
• Freed-up lab staff for data analysis rather than repetitive prep tasks

How does Raykol’s automated SPE system improve sample prep?

• Reduced contamination risk from human handling
• Faster preparation times for large volumes
• Seamless compatibility with LC/MS workflows
• Improved repeatability and lab efficiency

Agilent LC/MS: Trusted precision for PFAS detection

• Comply with global regulations (e.g. EU REACH, US EPA, SAICM)
• Process large test batches without compromising accuracy
• Stay competitive by delivering reliable, compliant results on time

PFAS testing protects more than compliance

• Consumer trust during peak sales seasons
• Brand differentiation as safety-conscious and transparent
• Supply chain resilience against new international bans or restrictions
• Preparedness for the expanding global push toward PFAS elimination

What’s next? Build a smarter PFAS detection strategy

In this discussion, we will cover:

• The significance of connections
• Considerations for the mobile phase
• Quality considerations
• Preventing microbial growth
• Compatibility of sample and solvent
• Characteristics of the column; their significance and limitations
• The importance of sample preparation

Speakers

Rita Steed
Application Engineer
Agilent Technologies, Inc.

Rita Steed began supporting the LC column line for Agilent in 1999. As a Chromatography Specialist (first with Chromatography, Inc., then directly for Agilent), Rita worked on-site with researchers in Pharmaceutical and other industries presenting technical seminars and assisting researchers with troubleshooting and method development. Rita has over 20 years of Chromatography experience in the Biotechnology, Chemical, and Pharmaceutical industries. She has held positions in Research, Sales, and Technical Service. Rita has earned degrees in Microbiology and Life Sciences/Biochemistry. In her current position, she is an inside Application Engineer supporting LC columns.

Register and watch on demand >

Specifically, Agilent automation offers intuitive workflows that provide high data reproducibility and increased throughput while reducing hands-on time. In this webinar, we describe key learnings revealed during the automation of several workflows that extract metabolites and/or lipids from plasma and mammalian cell samples.

Speakers

Genevieve Van de Bittner, Ph.D.
R&D Researcher
Agilent Research Laboratories
Agilent Technologies, Inc.

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Chromatograpahy & Mass Spec

Since most samples encountered in a chromatography laboratory are not in a form to be directly placed into the analytical instrument, some form of preparation is required for nearly every sample. The sample preparation could be as simple as “dilute and shoot” or as complex as multistage sample handling. The aim of sample preparation is to provide a sample aliquot that (a) is relatively free of interferences, (b) will not damage the column or instrument and (c) is compatible with the intended analytical method. In chromatography, the sample solvent should dissolve in the HPLC mobile phase or be injectable into a GC column without affecting sample retention or resolution, the stationary phase itself, and without interfering with detection. 

Fundamentals

Here you can find useful resources on Sample Preparation for Chromatography Techniques

Sample Preparation Fundamentals for Chromatography

Primer

Simple Approaches to SPE Method Development

Simple Steps to Maximize Lipid Removal with EMR-Lipid