Micro-Contaminant Analysis Using AIMsight Infrared Microscope

Applications | 2023 | ShimadzuInstrumentation
FTIR Spectroscopy, Microscopy
Industries
Environmental, Materials Testing
Manufacturer
Shimadzu

Summary

Significance of Micro-Contaminant Analysis


The identification and characterization of microscopic contaminants in consumer products have become critical for ensuring safety and quality in industries such as pharmaceuticals and food manufacturing. Trace particles can originate from raw materials, production equipment wear, or end-user mishandling, and may consist of organic or inorganic substances. Reliable detection and precise qualitative analysis at the micrometer scale support root cause investigations and compliance with regulatory standards.

Objectives and Study Overview


This study demonstrates the application of the AIMsight infrared microscope coupled with the IRTracer-100 spectrometer to perform ATR measurements of a micro-contaminant adhering to the surface of a button cell. It evaluates the system’s imaging and spectral acquisition capabilities and illustrates how Shimadzu’s Contaminant Library and the Spectrum Advisor function aid efficient qualitative analysis.

Methodology and Instrumentation


The micro-contaminant located on the button cell was first observed with a wide-field camera covering 10 × 13 mm, then zoomed into subregions as small as 30 × 40 μm using a microscope camera with up to 10× digital zoom. Sample dimensions were measured via the AMsolution software’s length measurement tool. ATR spectra were collected under these conditions:
  • Instrument: IRTracer-100 and AIMsight infrared microscope
  • Optical resolution: 8 cm⁻¹
  • Accumulations: 200 scans
  • Apodization function: square triangle
  • Detector: T2SL

Results and Discussion


The high signal-to-noise ratio of 30000:1 allowed acquisition of strain-free, low-noise spectra from a contaminant measuring 18 μm × 60 μm. Search against a standard library suggested acrylonitrile butadiene rubber as the main component with additives such as calcium carbonate, phthalate ester, and kaolin. Further matching using Shimadzu’s original Contaminant Library enhanced identification accuracy by incorporating data on real-world mixtures, along with metadata on elemental composition, color, shape, hardness, and luster. The Spectrum Advisor function then evaluated spectrum quality interactively, guiding baseline corrections and peak validation through a user-friendly interface.

Benefits and Practical Applications


Key advantages of this workflow include:
  • Rapid location of contaminants using wide-field and microscope cameras without repositioning errors
  • Precise size measurement and imaging down to 10 × 10 μm regions
  • High-quality ATR spectra acquired in short times, even for microscopic samples
  • Improved identification confidence via an extensive contaminant library featuring real-sample data
  • Guided spectral quality checks that reduce operator training requirements

The approach streamlines QA/QC tasks in pharmaceutical and food sectors where trace contamination analysis is essential.

Future Trends and Opportunities


Developments likely to enhance micro-contaminant analysis include:
  • Automated stage scanning and AI-driven spectral interpretation to increase throughput
  • Expansion of contaminant databases with user-contributed spectra and mixture data
  • Integration of complementary imaging modalities such as Raman mapping for multimodal analysis
  • Portable infrared microspectroscopy systems for on-site inspections

Conclusion


The combination of the AIMsight infrared microscope, IRTracer-100 spectrometer, and advanced software tools provides a robust platform for high-sensitivity analysis of micro-contaminants. The synergy of accurate imaging, precise measurements, comprehensive libraries, and interactive quality checks accelerates contaminant identification and supports reliable root cause investigations in critical industries.

Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.

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