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The Analytical Scientist / Issues / 2026 / July / Spectroscopy Roundup Hidden Structure and Sharper Signals
Spectroscopy News and Research

Spectroscopy Roundup: Hidden Structure and Sharper Signals

From carbon defects and milliliter-scale gas sensing to proton-transfer dynamics and machine-learned spectra, spectroscopy delivers sharper structural readouts

07/07/2026 6 min read
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Objective:

To clarify the structural origins of defect peaks in high-temperature carbon materials and enhance Raman sensitivity for gas detection.

Approach:
  • Carbon Defects Study: Combined experimental Raman, infrared, and XPS measurements with density functional theory calculations on isotropic pitch-based carbon fiber.
  • Raman Cavity Development: Developed an asymmetric hollow-core fiber cavity to enhance Raman sensitivity for detecting multiple gas species from milliliter-scale samples.
  • Hafnium Chloride Scintillator: Created a scintillator screen using hafnium chloride to improve brightness and sharpness in indirect X-ray imaging.
Key Findings:
  • The 285 eV XPS feature in carbon fibers is linked to carbon atoms surrounded by three rings, including non-hexagonal defects.
  • Raman spectra indicate that peaks between 1500 and 1550 cm−1 are influenced by nearby non-hexagonal rings and oxygen-containing groups.
  • The Raman cavity design increased signal sensitivity by 170-fold compared to hollow-core fiber alone.
  • The hafnium chloride scintillator achieved a light yield of 56,563 ± 1,250 photons/MeV with minimal blurring.
Interpretation:

The findings provide a clearer understanding of defect structures in carbon materials and enhance detection capabilities in spectroscopy.

Conclusion:

The studies advance the understanding of carbon defect structures and improve spectroscopic techniques.

This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.

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