≥98% for sensitive chromatographic and analytical workflows requiring minimal baseline interference.
Room temperature,Argon charged Ships Normal Check lot-specific COA for exact specifications.
SDS, COA, datasheet, and spec sheet available for download. Lot-specific COA accessible via lot number lookup.
Cited in 1 peer-reviewed publications across chromatography, organic synthesis, and cross-coupling reactions.
| Pubchem Sid | 488188399 |
|---|---|
| Kanonisches Lächeln | [B-](F)(F)(F)F.CCN |
| IUPAC Name | ethanamine;tetrafluoroborate |
| InChIKey | YAGCIVXJAKJBMA-UHFFFAOYSA-N |
| INCHI | 1S/C2H7N.BF4/c1-2-3;2-1(3,4)5/h2-3H2,1H3;/q;-1 |
| Isomere SMILES | [B-](F)(F)(F)F.CCN |
| PubChem CID | 166605 |
| Molekulargewicht | 132.90 |
Comprehensive hazard, handling, storage, and regulatory compliance document.
Download SDS →Lot-specific quality data. Enter your lot number to retrieve the exact COA.
Look up COA →Full quality attributes and acceptance criteria for this grade.
View spec sheet →Find and download the COA for your product by matching the lot number on the packaging.
| Lot Number | Certificate Type | Datum | Artikel |
|---|---|---|---|
 F2625069 | Certificate of Analysis | Jul 13, 2026 | E493992 |
| F23161295 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161298 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161299 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161301 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161302 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161305 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161306 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161307 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161309 | Certificate of Analysis | May 27, 2023 | E493992 |
| F23161310 | Certificate of Analysis | May 27, 2023 | E493992 |
| Empfindlichkeit | Moisture sensitive. |
|---|
| 1. Hong Zhang, Jing Gao, Zhonghao Shi, Bo Gao, Xiangnan Wang, Jie Wu, Rutao Wang, Ye Han. (2026) High-throughput screening of efficient ionic liquid additives for aqueous zinc-ion batteries assisted by machine learning. Journal of Energy Storage, [PMID:] [10.1016/j.est.2026.121278] |
