How can you identify proteins from FTIR?
This page summarizes the recurring FTIR evidence reported for proteins, including the most frequent peaks, supporting functional groups, and literature-backed interpretation patterns. It is a structured evidence page, not a claim of automatic single-spectrum certainty.
Backed by 18 cited sources
Quick answer
proteins is usually reported with a recurring pattern of peaks and functional-group evidence. The most useful approach is to cross-check at least two characteristic peaks before treating it as a match, then verify whether the full spectrum still fits the same material family.
Peak interpretation
Possible materials / groups
| Functional group | Evidence |
|---|---|
| Amide | 38 |
| Alkyl C-H | 16 |
| Methacrylate | 15 |
| Acetate | 15 |
| Hydroxyl (O-H) | 11 |
| Carboxyl (COOH) | 10 |
| Methoxy (OCH3) | 10 |
| C-O single bond | 10 |
Spectrum logic
The logic here is evidence aggregation: repeated literature mentions of proteins, repeated peak positions, and repeated functional-group associations. A strong material hypothesis should still be supported by multiple peaks that agree with each other, not by one headline band alone.
Real-world usage
This page is designed for polymer identification, incoming-material QC, unknown plastic analysis, recycled-content review, and literature-backed interpretation of reference spectra.
Common mistakes
- Calling a material match too early because one famous peak is present.
- Ignoring sample prep, fillers, oxidation, water, or additives that can change the apparent pattern.
- Using literature evidence without checking whether your own sampling mode and spectrum quality are comparable.
Verification advice
Use DSC, GC-MS, or TGA to validate the material hypothesis when the peak pattern is ambiguous or mixed.
Literature behind this page
-
confidence 0.9
proteins
Plastics everywhere: first evidence of polystyrene fragments inside the common Antarctic collembolan <i>Cryptopygus antarcticus</i> DOI: 10.1098/rsbl.2020.0093 -
confidence 0.9
proteins
Rebufa 等 - 2021 - AComDim, a multivariate tool to highlighting impac DOI: 10.1111/j.1745-4557.2008.00218. -
confidence 0.8
proteins
Ganim 等 - 2008 - Amide I two-dimensional infrared Spectroscopy of p DOI: 10.1021/ar700188nCCC -
confidence 0.8
proteins
Alizadeh 等 - 2022 - Application of SPRA Technology for Delivery of Ery DOI: 10.5812/ijpr-134282. -
confidence 0.8
proteins
Balakhnina 等 - 2017 - Low-frequency vibrational spectroscopy of proteins DOI: 10.1117/1.JBO.22.9.091509. -
confidence 0.8
proteins
Fiocco 等 - 2021 - Reflection FTIR spectroscopy for the study of hist DOI: 10.1016/j.culher.2019.11.004. -
confidence 0.8
proteins
Koliastasi 等 - 2019 - Emulsifiers from Partially Composted Olive Waste DOI: 10.3390/foods8070271 -
confidence 0.8
proteins
A New Method for D<sub>2</sub>O/H<sub>2</sub>O Exchange in Infrared Spectroscopy of Proteins DOI: 10.1155/2012/791342 -
confidence 0.8
proteins
ATR-FTIR spectroscopy and spectroscopic imaging to investigate the behaviour of proteins subjected to freeze–thaw cycles in droplets, wells, and under flow DOI: 10.1039/d1an00087j -
confidence 0.7
proteins
DNA-RNA, DNA-DNA, DNA-protein and protein-protein interactions in diagnosis of skin cancers by FT-IR microspectroscopy DOI: 10.1117/12.874692
See proteins in your own spectrum
Upload your FTIR spectrum and get AI-assisted polymer analysis and peak-by-peak interpretation from your own spectrum.