18999-70-7

Basic information

• Product Name: 2,2-dimethyl-2,3-dihydro-1-benzofuran-7-yl (hydroxymethyl)carbamate
• CAS NO: 18999-70-7
• Molecular Formula: C₁₂H₁₅NO₄
• Molecular Weight: 237.2518
• Mol File: 18999-70-7.mol
• Article Data: 1

Chemical Properties

• Boiling Point: 364.1°C at 760 mmHg
• Flash Point: 174°C
• Density: 1.236g/cm³
• Vapor Pressure: 6.11E-06mmHg at 25°C
• Refractive Index: 1.55
• CAS DataBase Reference: 2,2-dimethyl-2,3-dihydro-1-benzofuran-7-yl (hydroxymethyl)carbamate(CAS DataBase Reference)
• NIST Chemistry Reference: 2,2-dimethyl-2,3-dihydro-1-benzofuran-7-yl (hydroxymethyl)carbamate(18999-70-7)
• EPA Substance Registry System: 2,2-dimethyl-2,3-dihydro-1-benzofuran-7-yl (hydroxymethyl)carbamate(18999-70-7)

Safety Data

• Hazardous Substances Data: 18999-70-7(Hazardous Substances Data)

Upstream product

• 222641-43-2 benzyloxymethylcarbamic acid 2,2-dimethyl-2,3-dihydrobenzofuran-7-yl ester 
• 1563-66-2 2,3-dihydro-2,2-dimethyl-7-benzofuranol methylcarbamate 
• 1563-38-8 2,3-dihydro-2,2-dimethylbenzofuran-7-ol 

Relevant articles and documents

Chemical models of cytochrome P450 catalyzed insecticide metabolism. Application to the oxidative metabolism of carbamate insecticides

Cytochrome P450 (CP450) catalyzed oxidative metabolism of carbofuran (1), carbaryl (2), and pirimicarb (3) has been modeled using biomimetic oxidations catalyzed by iron(III) tetraarylporphyrins. Oxidation products of 1 were identified by comparison of HPLC retention times measured under standardized conditions for metabolites synthesized and characterized by 1H and 13C NMR spectroscopy. Comparison of product distributions to in vivo metabolic profiles revealed that the H2O2/meso- tetrakis(pentafluorophenyl)porphyrin iron(III) chloride [Fe(TF20PP)] system mimics the action of insect CP450s against carbofuran. The effectiveness of this system was further demonstrated by the biomimetic oxidation of other carbamate insecticides (2 and 3) monitored by HPLC/electrospray MS. The predictive power of this biomimetic model was compared to that of knowledgebased expert systems. Although similar models were recently applied in pharmaceutical research, the usefulness of this approach has first been demonstrated for the prediction of metabolic profiles of agrochemicals.