five

Suspect Screening of Liquid Crystal Monomers (LCMs) in Sediment Using an Established Database Covering 1173 LCMs

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
https://figshare.com/articles/dataset/Suspect_Screening_of_Liquid_Crystal_Monomers_LCMs_in_Sediment_Using_an_Established_Database_Covering_1173_LCMs/19804145
下载链接
链接失效反馈
官方服务:
资源简介:
Recent studies have suggested that liquid crystal monomers (LCMs) are emerging contaminants in the environment, and knowledge of this class of substances is very rare. Here, we reviewed existing LCM-related documents, i.e., publications and patents, and established a database involving 1173 LCMs. These 1173 LCMs were further calculated for their physicochemical properties, i.e., persistence (P), bioaccumulation (B), long-range transport potential (LRTP), and Arctic contamination and bioaccumulation potential (ACBAP). We found that 476 out of them were P&B chemicals (99% of them were halogenated), and 320 of them could have ACBAP properties (67% of them were halogenated). This LCM database was further applied for suspect screening of LCMs in n = 33 sediment samples by use of gas chromatography coupled to quadrupole time-of-flight mass spectrometry (GC-QTOF/MS). We tentatively identified 26 LCM formulas, which could have 43 chemical structures. Two out of these 43 suspect LCM candidates, 1-butoxy-2,3-difluoro-4-(4-propylcyclohexyl) benzene (3cH4OdFP) and 1-ethoxy-2,3-difluoro-4-(4-pentyl cyclohexyl) benzene (5cH2OdFP), were fully confirmed by a comparison of unique GC and MS characteristics with their authentic standards. Overall, our present study expanded the previous LCM database from 362 to 1173, and 1173 LCMs in this database were calculated for their physicochemical properties. Meanwhile, taking n = 33 sediment samples as an exercise, we successfully developed a suspect screening strategy tailored for LCMs, and this strategy could have promising potential to be extended to other environmental matrices.
创建时间:
2022-05-20
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作