Structure and Vibrational Spectroscopy of C 82 Fullerenol Valent Isomers: An Experimental and Theoretical Joint Study.
Felix N TomilinPolina V ArtyushenkoIrina A ShchugorevaAnastasia V RogovaNatalia G VnukovaGrigory N ChurilovNikolay P ShestakovOlga N TchaikovskayaSergei G OvchinnikovPavel V AvramovPublished in: Molecules (Basel, Switzerland) (2023)
Gd@C 82 O x H y endohedral complexes for advanced biomedical applications (computer tomography, cancer treatment, etc.) were synthesized using high-frequency arc plasma discharge through a mixture of graphite and Gd 2 O 3 oxide. The Gd@C 82 endohedral complex was isolated by high-efficiency liquid chromatography and consequently oxidized with the formation of a family of Gd endohedral fullerenols with gross formula Gd@C 82 O 8 (OH) 20 . Fourier-transformed infrared (FTIR) spectroscopy was used to study the structure and spectroscopic properties of the complexes in combination with the DFTB3 electronic structure calculations and infrared spectra simulations. It was shown that the main IR spectral features are formed by a fullerenole C 82 cage that allows one to consider the force constants at the DFTB3 level of theory without consideration of gadolinium endohedral ions inside the carbon cage. Based on the comparison of experimental FTIR and theoretical DFTB3 IR spectra, it was found that oxidation of the C 82 cage causes the formation of Gd@C 82 O 28 H 20 , with a breakdown of the integrity of the parent C 82 cage with the formation of pores between neighboring carbonyl and carboxyl groups. The Gd@C 82 O 6 (OOH) 2 (OH) 18 endohedral complex with epoxy, carbonyl and carboxyl groups was considered the most reliable fullerenole structural model.
Keyphrases
- high frequency
- density functional theory
- high efficiency
- single molecule
- liquid chromatography
- molecular dynamics
- mass spectrometry
- high resolution
- transcranial magnetic stimulation
- molecular dynamics simulations
- optical coherence tomography
- nitric oxide
- molecular docking
- hydrogen peroxide
- high resolution mass spectrometry
- machine learning
- simultaneous determination
- solid phase extraction