What absorbs at 3074 cm⁻¹ in an FTIR spectrum?
A band near 3074 cm⁻¹ can point to several functional groups. Below are the most likely assignments, ranked by how much published evidence supports each — every one traceable to literature (DOI) and cross-validated against our 130,000+ reference spectra and knowledge graph.
Backed by 5 cited sources
可能的官能团归属
| 官能团 | 支持性事实 | 引用来源 | 最高置信度 |
|---|---|---|---|
| Alkyl C-H | 2 | 2 | 1.0 |
| Aromatic ring | 1 | 1 | 1.0 |
| Methoxy (OCH3) | 1 | 1 | 1.0 |
| Methacrylate | 1 | 1 | 1.0 |
| C-O single bond | 1 | 1 | 1.0 |
| Acetate | 1 | 1 | 1.0 |
| Amide | 1 | 1 | 1.0 |
| Hydroxyl (O-H) | 1 | 1 | 1.0 |
排名反映了累积的文献证据，而非单一的权威规则。请始终对照您的样品背景进行确认。
这些分配背后的文献
-
Hydroxyl (O-H) 置信度 1.0
“A peak at cm-1 3074 belonged to weak O-H stretching [30] and cm-1 a broad peak at 3322 was attributed to O-H”
Influence of Ho3+ substitution on structural and magnetic properties of Mg–Mn ferrites DOI: 10.1007/s10854-021-05547-9 -
Alkyl C-H 置信度 1.0
“ized by Raman spectroscopy studies should be considered as 2 3 cm-1 suggesting the presence of water), 3074 (C-H stretching), 3 distinct survival strategy against osmotic stressful conditions b cm-1 cm-1 2955 (asymmetric stretching vibratio”
Cojoc 等 - 2019 - Carotenoids produced by halophilic bacterial strai DOI: 10.1093/femsle/fnz243 -
Amide 置信度 1.0
“LLM confirmed rule peak-group candidate”
Dolete 等 - 2019 - Development and sequential analysis of a collagen- DOI: 10.25083/rbl/24.1/108.117 -
Acetate 置信度 1.0
“Neat unsaturated 1276.64cm-1 hasapeakat3074.41cm-1 in lignin.The peak at can be assigned to C-O-C resultingfromthe=C-H polyester”
Sahari 和 Maleque - 2016 - Mechanical Properties of Oil Palm Shell Composites DOI: 10.1155/2016/7457506 -
Aromatic ring 置信度 1.0
“The characteristic bands of alkenes and aromatic compounds are 3074 cm-1, 1630 cm-1, 910 cm-1, cm-1, cm-1, cm-1, The characteristic bands of alkenes and aromatic compounds are 3074 1630 910 3033 cm-1, 1496 cm-1, and 698 cm-1.”
Degradation Classification of 3D Printing Thermoplastics Using Fourier Transform Infrared Spectroscopy and Artificial Neural Networks DOI: 10.3390/app8081224
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