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Merck
CN

251321

Sigma-Aldrich

1,5-二甲基萘

98%

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About This Item

线性分子式:
C10H6(CH3)2
CAS号:
分子量:
156.22
Beilstein:
2039843
EC 号:
MDL编号:
UNSPSC代码:
12352100
PubChem化学物质编号:

方案

98%

沸点

265-266 °C (lit.)

mp

77-82 °C (lit.)

SMILES字符串

Cc1cccc2c(C)cccc12

InChI

1S/C12H12/c1-9-5-3-8-12-10(2)6-4-7-11(9)12/h3-8H,1-2H3

InChI key

SDDBCEWUYXVGCQ-UHFFFAOYSA-N

基因信息

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象形图

Exclamation mark

警示用语:

Warning

危险声明

预防措施声明

危险分类

Eye Irrit. 2 - Skin Irrit. 2 - STOT SE 3

靶器官

Respiratory system

储存分类代码

13 - Non Combustible Solids

WGK

WGK 3

闪点(°F)

Not applicable

闪点(°C)

Not applicable

个人防护装备

dust mask type N95 (US), Eyeshields, Gloves

法规信息

新产品

历史批次信息供参考:

分析证书(COA)

Lot/Batch Number

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Kunal Roy et al.
European journal of medicinal chemistry, 44(5), 1941-1951 (2008-12-27)
A series of naphthalene and non-naphthalene derivatives (n=42) having cytochrome P450 2A6 and 2A5 inhibitory activities, reported by Rahnasto et al., were subjected to QSAR and QAAR studies. The analyses were performed using electronic, spatial, shape and thermodynamic descriptors to
Laura E Korhonen et al.
Journal of medicinal chemistry, 48(11), 3808-3815 (2005-05-27)
The purpose of this study was to determine the cytochrome P450 1A2 (CYP1A2) inhibition potencies of structurally diverse compounds to create a comprehensive three-dimensional quantitative structure-activity relationship (3D-QSAR) model of CYP1A2 inhibitors and to use this model to predict the
Minna Rahnasto et al.
Journal of medicinal chemistry, 48(2), 440-449 (2005-01-22)
The purpose of this study was to develop screening and in silico modeling methods to obtain accurate information on the active center of CYP2A6, a nicotine oxidizing enzyme. The inhibitory potencies of 26 naphthalene and 16 non-naphthalene derivatives were determined
A A Toropov et al.
European journal of medicinal chemistry, 43(4), 714-740 (2007-07-17)
Simplified molecular input line entry system (SMILES) has been utilized in constructing quantitative structure-property relationships (QSPR) for octanol/water partition coefficient of vitamins and organic compounds of different classes by optimal descriptors. Statistical characteristics of the best model (vitamins) are the

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