合成这些 enantiomerenreiner 6,10-Epoxybenzocycloocten-7-amine mit ZNS-Aktivität
摘要:
在 einer oxa-analogen Pictet-Spengler-Reaktion kondensiert der (S)-Phenylmilchsäureester 6 mit Methyllävulinat (7a) zu den 2-Benzopyranen cis-8a und trans-8a, die sich mit CH3I zu cis-den-9an烷烃拉森。Durch Mitteldruck-Flüssigchromatographie lassen sich die Diastereomeren cis-9a 和 trans-9a trennen。Bei der anschließenden Dieckmann-Cyclisierungliefert cis-9a direkt den linksdrehenden β-Ketoester (-)-10a, während
DOI:
10.1002/ardp.19923251110
作为产物:
描述:
L-薄荷醇 、 乙酰丙酸 在
Silica-supported propylsulfonic acid 、 air 作用下,
以
neat (no solvent) 为溶剂,
以76%的产率得到(-)-Menthyl-laevulinat
参考文献:
名称:
Silica-supported sulfonic acids as recyclable catalyst for esterification of levulinic acid with stoichiometric amounts of alcohols
Solvent-free transesterification of methyl levulinate and esterification of levulinic acid catalyzed by a homogeneous iron(III) dimer complex
作者:Massimo Melchiorre、Raffaele Amendola、Vincenzo Benessere、Maria E. Cucciolito、Francesco Ruffo、Roberto Esposito
DOI:10.1016/j.mcat.2020.110777
日期:2020.3
solvents, additives and plasticizers. In this work a variety of levulinates (R= n-butyl, n-hexyl, n-octyl, 2-ethylhexyl, geranyl, 2-ethoxyethyl, benzyl, 2-octyl, cyclohexyl, menthyl) is obtained from the solvent-free transesterification of methyl levulinate (ML) and esterification of levulinic acid (LA), catalyzed by a dimeric complex of iron(III). The results are competitive with the few related reports
乙酰丙酸酯MeC(O)CH 2 CH 2 CO 2 R(LAE)是新兴的生物基化学品,用作溶剂,添加剂和增塑剂。在这项工作中,从无溶剂酯交换反应中获得了多种乙酰丙酸酯(R =正丁基,正己基,正辛基,2-乙基己基,香叶基,2-乙氧基乙基,苄基,2-辛基,环己基,薄荷基)。乙酰丙酸甲酯(ML)的合成和乙酰丙酸(LA)的酯化反应;),由铁(III)的二聚配合物催化。该结果与主要基于多相催化的一些相关文献报道相比具有竞争力。因此,基于均相催化系统的第一个系统研究代表了生物质增值领域的重大扩展。
Unveiling Stereo‐Electronic Effects in Homogeneous Catalysis Integrating Theory and Experiments: the Potential of Dimeric Iron(III) Salen Complexes in Methyl Levulinate Transesterification
• Structure-activity relationship of Fe(III) salendimeric catalysts for methyl levulinate transesterification.• DFT and Machine Learning techniques correlate Fe−O−Fe angle and LUMO energy with catalytic activity.• Comprehending electronic and steric effects in Lewis-acid catalysis and rational catalyst design.• High-yield synthesis of industrially relevant esters under mild conditions.