Fourier Transform Infrared Spectroscopy (FTIR) is a powerful analytical tool for assessing the aging processes of nanomaterials, particularly oxidation and hydrolysis. The technique provides molecular-level insights into chemical changes by detecting functional group transformations. In carbon-based nanomaterials, oxidation manifests through carbonyl group formation, while in quantum dots and silica-based nanoparticles, hydrolysis leads to silanol generation. Accelerated aging tests, when correlated with natural degradation processes, allow researchers to identify spectral markers that predict long-term stability.
The aging of carbon nanomaterials such as graphene, carbon nanotubes, and fullerenes primarily involves oxidation. FTIR spectra reveal this degradation through the appearance of C=O stretching vibrations between 1700 and 1750 cm⁻¹, indicative of carbonyl formation. Additional peaks may emerge at 1200–1300 cm⁻¹ (C-O stretching) and 3000–3500 cm⁻¹ (O-H stretching), confirming progressive oxidation. The intensity ratio of carbonyl peaks to intrinsic carbon peaks (e.g., C=C at 1500–1600 cm⁻¹) serves as a quantitative measure of degradation extent. Accelerated aging under elevated temperatures or UV exposure accelerates carbonyl growth, with studies showing a 20–40% increase in C=O peak intensity after 100 hours of thermal oxidation at 150°C compared to natural aging over six months.
For quantum dots, particularly those with silica shells or oxide surfaces, hydrolysis dominates aging. FTIR detects silanol (Si-OH) formation through a broad absorption band at 3200–3700 cm⁻¹ (O-H stretching) and a sharp peak near 950 cm⁻¹ (Si-OH bending). The ratio of silanol to siloxane (Si-O-Si, 1000–1100 cm⁻¹) peaks quantifies hydrolysis progression. In cadmium-based quantum dots, accelerated aging under high humidity (85% RH at 60°C) shows a 30–50% increase in silanol peaks within 72 hours, mirroring natural degradation over one year. Phosphorus-containing capping ligands on indium phosphide quantum dots exhibit P=O stretching at 1250 cm⁻¹ upon oxidation, another key FTIR marker.
Polymer-coated nanomaterials present complex aging profiles where FTIR distinguishes chain scission, crosslinking, and additive migration. Polyethylene glycol (PEG)-coated nanoparticles show ether bond (C-O-C) degradation at 1100 cm⁻¹, while poly(lactic-co-glycolic acid) (PLGA) particles exhibit ester carbonyl loss (1750 cm⁻¹) and carboxylic acid formation (1710 cm⁻¹). The crystallinity index, calculated from the 720 cm⁻¹/730 cm⁻¹ peak ratio in polyolefins, decreases with aging due to chain reorganization.
Accelerated aging protocols must carefully replicate natural degradation mechanisms to ensure predictive validity. For oxidation studies, temperatures below 200°C prevent artificial reaction pathways, while humidity levels above 80% RH accelerate hydrolysis without inducing phase changes. UV exposure at wavelengths matching solar spectra (280–400 nm) provides realistic photoaging data. FTIR spectra from accelerated tests should align with natural aging in three aspects:
1) Identical functional group transformations
2) Comparable peak intensity ratios at equivalent degradation stages
3) Consistent band broadening patterns indicating amorphous phase formation
Spectral deconvolution enhances FTIR analysis by separating overlapping peaks. Gaussian fitting of the 1500–1800 cm⁻¹ region in carbon nanomaterials quantifies ketones (1715 cm⁻¹), aldehydes (1730 cm⁻¹), and carboxylic acids (1770 cm⁻¹) individually. For silica nanoparticles, deconvoluting the 800–1200 cm⁻¹ range distinguishes cyclic siloxanes (1020 cm⁻¹) from linear chains (1080 cm⁻¹). Second-derivative spectroscopy suppresses baseline artifacts, revealing hidden peaks like hydrogen-bonded silanols at 3650 cm⁻¹.
The table below summarizes key FTIR markers for nanomaterial aging:
Material | Degradation Type | FTIR Marker (cm⁻¹) | Interpretation
Carbon Nanotubes | Oxidation | 1715 (C=O) | Carbonyl formation
Graphene Oxide | Hydrothermal Aging | 1620 (C=C) | Conjugated domain loss
Silica QDs | Hydrolysis | 950 (Si-OH) | Surface hydroxylation
PLGA Nanoparticles | Hydrolytic Scission | 1750→1710 | Ester to acid conversion
Gold-PEG Conjugates | Oxidative Cleavage | 1100 (C-O-C) | Ether bond breakdown
Long-term stability predictions require correlating FTIR data with performance metrics. In photovoltaic nanomaterials, a 10% increase in carbonyl content typically corresponds to a 15–20% efficiency drop. For drug-loaded nanoparticles, silanol formation exceeding 5% relative to initial values often precedes burst release behavior. Machine learning models trained on FTIR aging datasets now predict shelf life with over 90% accuracy when validated against real-time studies.
Operational parameters critically influence FTIR assessment. Attenuated total reflectance (ATR) mode provides surface-sensitive data for coatings, while transmission mode suits powdered samples. Resolution settings below 4 cm⁻¹ resolve narrow peaks like crystalline phases, and 64+ scans ensure adequate signal-to-noise for trace degradation products. Background subtraction must account for atmospheric CO₂ (2350 cm⁻¹) and water vapor (1600 cm⁻¹) interference.
Emerging FTIR techniques push aging analysis further. Nano-FTIR with atomic force microscopy probes local degradation at individual nanoparticles. Time-resolved FTIR tracks real-time oxidation kinetics, revealing that carbon nanomaterial oxidation follows logarithmic rather than linear progression. Synchronized FTIR-Raman systems provide complementary data, with Raman confirming structural disorder while FTIR quantifies chemical changes.
Standardization remains challenging due to nanomaterial diversity, but ASTM E1252-98 provides guidelines for peak assignment. Future work should establish material-specific degradation indices based on FTIR band ratios, enabling direct comparison across studies. For now, researchers must document spectrometer settings, sample preparation methods, and peak fitting algorithms to ensure reproducibility.
Through careful experimental design and data interpretation, FTIR spectroscopy serves as an indispensable tool for understanding nanomaterial aging mechanisms. The technique's molecular specificity, combined with accelerated testing protocols, enables accurate stability predictions that guide material selection and lifespan estimation across industries from medicine to energy storage.