Detection of carbon nanotubes in environmental matrices using programmed thermal analysis

Area of Science:

• Environmental Science
• Analytical Chemistry
• Materials Science

Background:

• Carbon nanotube (CNT) production is increasing, necessitating robust analytical methods for environmental quantification.
• Existing methods struggle with complex organic matrices and diverse CNT properties (single-walled vs. multiwalled).
• The thermal optical transmittance/reflectance (TOT/R) method, used for air pollution analysis, needed adaptation for CNTs.

Purpose of the Study:

• To adapt and validate the TOT/R method for quantifying various carbon nanotubes (CNTs) in complex environmental and biological matrices.
• To understand and differentiate the thermal properties of different CNT types.
• To establish optimized temperature programs and quantification rules for CNT analysis.

Main Methods:

• Studied 14 single-walled (SWCNTs) and multiwalled CNTs (MWCNTs).
• Evaluated CNT thermal properties using Raman spectroscopy to classify them as 'weak' or 'strong'.
• Modified the programmed thermal analysis (PTA) method, a variant of TOT/R, with optimized temperature programs and quantification rules.

Main Results:

• Classified CNTs into 'thermally weak' and 'strong' categories using Raman spectroscopy.
• Achieved good recoveries (96-99%) for strong CNTs in cyanobacteria matrices after pretreatment.
• Identified matrix interferences in cyanobacteria and urban air, particularly for weak CNTs, and established a detection limit of 55 ng/m³ for strong CNTs in urban air.

Conclusions:

• The combined Raman/PTA method offers a viable approach for quantifying diverse CNTs in complex matrices.
• Matrix pretreatment is crucial for accurate analysis, especially in biological samples like cyanobacteria.
• Further research is needed to minimize interferences and lower detection limits for broader CNT quantification.