Molecular-level insight in supported olefin metathesis catalysts by combining surface organometallic chemistry, high throughput experimentation, and data analysis

Abstract

<p>Combination of high-throughput experimentation, surface organometallic chemistry and data analysis helps to extract key structural parameters that facilitate olefin metathesis. </p>

Olefin metathesis: what have we learned about homogeneous and heterogeneous catalysts from surface organometallic chemistry?

“…More recently, a combination of high-throughput experimentation, surface organometallic chemistry and statistical data analysis was employed to gain a better understanding of key parameters that drive the efficiency of silica-grafted molybdenum imido alkylidene catalysts for the homometathesis of 1-nonene. 124 Evaluation of in situ prepared formulations from a library of 35 phenols and two molybdenum bis-pyrrolide precursors allowed quantitative relation of the productive turnover number and turnover frequency to structural features of the aryloxy ligands by examining their computed electronic and steric characteristics. Apart from σ-donor electronic effects, dispersive interactions were found to be the key driver for high activity in the homodimerization of 1-nonene.…”

Advancement in Organic Synthesis Through High Throughput Experimentation

“…Further developments are likely where HTE becomes integrated with statistical [82] and computational modeling, [83] as well as with machine learning approaches [84] . The approach towards multi‐step one‐pot synthesis can be further utilized for other C−C or C−X reactions including direct or remote C−H activation with 3d transition metals [85] .…”

Development and Molecular Understanding of a Pd‐Catalyzed Cyanation of Aryl Boronic Acids Enabled by High‐Throughput Experimentation and Data Analysis

“…In this context, robotized high‐throughput experimentation (HTE) methods have been utilized to accelerate the acquisition of data on large libraries of formulations and build robust structure–activity relationships (SAR), ultimately enabling the identification of well‐performing catalytic systems [27–29] . These robotized approaches are particularly auspicious as they enable obtaining reproducible data sets that, in concert with statistical analysis tools, allow for correlating reaction outputs to specific physico‐chemical properties [30–32] .…”