Analysis of Diamonds by FT-IR Spectroscopy

Significance of the Topic

FT-IR spectroscopy provides a rapid, non-destructive and highly specific approach to confirm whether a faceted gemstone is indeed diamond and to characterize trace impurities trapped in the crystal lattice. Because diamonds command high market value and are subject to both treatments and synthetics (notably HPHT-grown diamonds), reliable analytical workflows are essential for gemological laboratories, trade quality control, and forensic verification. Infrared active defects—especially nitrogen aggregation states, hydrogen, boron and carbonate-related features—give diagnostic spectral fingerprints that enable classification and assist in detecting synthetic or treated material.

Objectives and Study Overview

This application note demonstrates FT-IR–based protocols and multivariate analysis strategies for:

• Rapid confirmation that a stone is diamond versus a simulant,
• Classification of diamonds by nitrogen aggregation types,
• Detection and quantification of low-level defect-related peaks relevant to treatment or synthetic origin (e.g., HPHT),
• Automating routine workflows to deliver fast, reproducible results with a confidence metric.

The work illustrates practical examples using a Thermo Scientific Nicolet 6700 FT-IR system coupled with optimized beam-condensing or reflection accessories and TQ Analyst multivariate software.

Methodology and Analytical Approach

Sample handling and spectral acquisition: Faceted diamonds are positioned under an optimized condenser accessory to collect high-quality spectra quickly and without damaging the stones. Acquisition covers the phonon and impurity regions relevant to diamond characterization (notably ~1500–4000 cm-1 and specific defect bands).

Data analysis workflows illustrated:

• Similarity Match (automated material confirmation): Reference spectra (e.g., type IIa diamond) are used in a spectral similarity algorithm that returns a match score from 0 to 100. A threshold of ~80 was empirically set to accept samples as diamonds while avoiding false positives. Type IIb diamonds with high boron content can distort phonon regions and reduce similarity scores.
• Classical Least Squares (CLS): Used to model a spectrum as a linear combination of reference spectra representing diamonds with defined nitrogen aggregate states (IaA, IaB, Ib). CLS provides relative concentrations (here illustrated with an arbitrary 100 ppm reference) and a standard error for each fitted component, supporting assessment of detection confidence.
• Curve resolution / Peak fitting (Peak Resolve): Employed to deconvolute overlapping or asymmetric features such as the platelet-related band near 1360 cm-1, yielding parameters like peak position and FWHM to track shifts and broadening associated with different defect structures.

Used Instrumentation

The key hardware and software components used in the examples:

• Thermo Scientific Nicolet 6700 FT-IR spectrometer
• Optimized 4X beam condenser or reflection accessory for faceted stones
• TQ Analyst multivariate analysis software (Similarity Match, CLS workflows)

Typical analysis time per stone (acquisition + automated processing) is under one minute when samples are properly positioned.

Main Results and Discussion

Confirming diamond identity: Phonon bands from the diamond lattice (observed primarily across ~1500–4000 cm-1) are reliable markers for confirming diamond material. The Similarity Match approach using a type IIa reference produced no false positives at a pass threshold of ~80, except for strong Type IIb (boron-rich) cases which alter the phonon region.

Nitrogen aggregate classification and quantification: CLS modeling using reference spectra for Type IaA, IaB and Ib enabled relative quantification of nitrogen aggregate types. Results showed contributions from multiple nitrogen forms in example spectra; however, adding more and better-characterized standards improves resolution between close components (for example to clarify weak Ib signals).

Platelet band analysis: A commonly observed band near 1360 cm-1—attributed to platelets—was shown to shift and broaden depending on the sample. Peak fitting resolved asymmetric profiles into two synthetic components and documented a FWHM increase (example: from 3.2 cm-1 at 1359 cm-1 to 4.8 cm-1 at 1364 cm-1), which provides a quantitative means to compare samples.

Detection of low-level defect peaks: CLS was applied to confirm and quantify weak absorptions at 3107 cm-1, 1344 cm-1 and 1332 cm-1 associated with low nitrogen content or other defects. The CLS-provided standard error allows a practical detection rule: measured peak intensities roughly three to five times greater than the reported error support reliable detection.

Limitations and caveats: Low overall nitrogen or other trace element concentrations can make assignment difficult. Type IIb diamonds with significant boron distort the phonon region and complicate similarity matching. Statistical confidence from CLS standard error is indicative but not strictly probabilistic; independent confirmatory methods may still be necessary for ambiguous or high-value cases.

Benefits and Practical Applications

Practical advantages demonstrated by the FT-IR approach include:

• Non-destructive, fast screening of faceted diamonds enabling high-throughput laboratory workflows,
• Automatable and operator-independent routines producing reproducible outputs plus a confidence metric,
• Ability to distinguish natural diamonds from common simulants and to flag stones for further expert examination when spectra deviate from known natural signatures,
• Capability to quantify relative amounts of nitrogen aggregation states and detect low-level defect-related peaks useful for identifying synthetic or treated material (e.g., HPHT signatures).

Future Trends and Potential Applications

Opportunities to extend or improve FT-IR diamond analysis include:

• Expanding high-quality spectral libraries (including well-characterized synthetic, treated and natural standards) to improve multivariate discrimination,
• Integrating FT-IR results with complementary techniques (Raman, photoluminescence, UV-Vis, EPR) for robust multi-modal classification workflows,
• Enhancing accessory designs and detectors for greater sensitivity to ultralow impurity concentrations and for mapping spatial variations within stones,
• Applying advanced chemometric and machine-learning models to improve sensitivity, reduce false positives/negatives, and provide probabilistic confidence metrics,
• Deploying automated sample-handling and reporting systems for routine certification and quality-control environments.

Conclusion

FT-IR spectroscopy, when combined with optimized optics and multivariate analysis, is a powerful, rapid, and non-destructive tool for diamond confirmation, defect characterization, and screening for synthetic or treated stones. The methods illustrated—Similarity Match for material ID, CLS for component quantification, and curve-resolution for peak characterization—provide complementary information and practical confidence metrics that support everyday gemological workflows. For ambiguous or critical cases, FT-IR should be integrated with additional spectroscopic methods and enriched spectral standards to improve diagnostic certainty.

References

The source application note demonstrating these methods was authored by Stephen Lowry, Ph.D. (Thermo Fisher Scientific) and describes analyses performed with Thermo Scientific Nicolet 6700 FT-IR instrumentation and TQ Analyst software. The note includes illustrative figures showing the instrument setup, similarity-matching results, CLS nitrogen-aggregate quantification, platelet peak curve fitting, and low-level peak detection examples.