Vibrational assignments of some simple and complexes structures are analysed to know some basics aspects necessaries in the assignments of bands observed in the infrared and Raman spectra combined with the Scaled Quantum Mechanical Force Field (SQMFF) methodology. Fundamentals characteristics are necessaries in machine learning to replace a human expert in vibrational analysis. The use of that approach implies the correct definitions of normal internal coordinates of the different groups and rings present in the structures and, obviously, the knowledge of all vibration modes and, in particular, of regions where these groups are expected. The results show that it is possible to identify neutral and zwitterionic forms of L-phenylalanine from imidazolyl phenylalanine if the vibration modes of six- and five-member rings are performed. In chiral species, reliable assignments are performed when the R and S structures of enantiomers are optimized and analysed. However, in components of extract isolated from plants with a high number of atoms in the structures, only machine learning could replace a human expert due to the high computational cost involved in optimizations, studies of potential energy surfaces, and construction of internal coordinates. In species with multiple rings, the greatest difficulty lies in constructing the internal coordinates of different rings, while, in nitrate species, both coordination monodentate and bidentate modes of these groups should be considered in the assignments. In phosphate species, the correct use of a local C2V or C3V symmetry for the phosphate group is indispensable to assurance consistent and safe vibrational assignments. Finally, to identify hydrated species, the librations modes of water molecules, in addition to stretching and deformation modes, should also be identified and assigned.
Research Article | Open Access | Download Full Text
Volume 4 | Issue 2 | Year 2026 | Article Id: AIR-V4I2P101 DOI: https://doi.org/10.59232/AIR-V4I2P101
Basics Aspects to Identify Different Structures by Using Vibrational Spectroscopy Combined with the SQMFF Approach and Machine Learning
Silvia Antonia Brandán
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 20 Mar 2026 | 25 Apr 2026 | 18 May 2026 | 20 Jun 2026 |
Citation
Silvia Antonia Brandán. “Basics Aspects to Identify Different Structures by Using Vibrational Spectroscopy Combined with the SQMFF Approach and Machine Learning.” DS Journal of Artificial Intelligence and Robotics, vol. 4, no. 2, pp. 1-43, 2026.
Abstract
Keywords
Molecular Structure; FTIR; DFT; SQMFF; Vibrational Assignments; Machine Learning.
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