Machine learning models and performance dependency on 2D chemical descriptor space for retention time prediction of pharmaceuticals.

The predictive modeling of liquid chromatography methods can be an invaluable asset, potentially saving countless hours of labor while also reducing solvent consumption and waste. Tasks such as physicochemical screening and preliminary method screening systems where large amounts of chromatography data are collected from fast and routine operations are particularly well suited for both leveraging large datasets and benefiting from predictive models. Therefore, the generation of predictive models for retention time is an active area of development. However, for these predictive models to gain acceptance, researchers first must have confidence in model performance and the computational cost of building them should be minimal. In this study, a simple and cost-effective workflow for the development of machine learning models to predict retention time using only Molecular Operating Environment 2D descriptors as input for support vector regression is developed. Furthermore, we investigated the relative performance of models based on molecular descriptor space by utilizing uniform manifold approximation and projection and clustering with Gaussian mixture models to identify chemically distinct clusters. Results outlined herein demonstrate that local models trained on clusters in chemical space perform equivalently when compared to models trained on all data. Through 10-fold cross-validation on a comprehensive set containing 67,950 of our company's proprietary analytes, these models achieved coefficients of determination of 0.84 and 3 % error in terms of retention time. This promising statistical significance is found to translate from cross-validation to prospective prediction on an external test set of pharmaceutically relevant analytes. The observed equivalency of global and local modeling of large datasets is retained with METLIN's SMRT dataset, thereby confirming the wider applicability of the developed machine learning workflows for global models.

Cationic molybdenum oxo alkylidenes stabilized by N-heterocyclic carbenes: from molecular systems to efficient supported metathesis catalysts.

Cationic d0 group 6 olefin metathesis catalysts have been recently shown to display in most instances superior activity in comparison to their neutral congeners. Furthermore, their catalytic performance is greatly improved upon immobilization on silica. In this context, we have developed the new family of molecular cationic molybdenum oxo alkylidene complexes stabilized by N-heterocyclic carbenes of the general formula [Mo(O)(CHCMe3)(IMes)(OR)[X-]] (IMes = 1,3-dimesitylimidazol-2-ylidene; R = 1,3-dimesityl-C6H3, C6F5; X- = B(3,5-(CF3)2C6H3)4 -, B(ArF)4, tetrakis(perfluoro-t-butoxy)aluminate (PFTA)). Immobilization of [Mo(O)(CHCMe3)(IMes)(O-1,3-dimesityl-C6H3)+B(ArF)4 -] on silica via surface organometallic chemistry yields an active alkene metathesis catalyst that shows the highest productivity towards terminal olefins amongst all existing molybdenum oxo alkylidene catalysts.

Single-Site Iridium Picolinamide Catalyst Immobilized onto Silica for the Hydrogenation of CO2 and the Dehydrogenation of Formic Acid.

The development of an efficient heterogeneous catalyst for storing H2 into CO2 and releasing it from the produced formic acid, when needed, is a crucial target for overcoming some intrinsic criticalities of green hydrogen exploitation, such as high flammability, low density, and handling. Herein, we report an efficient heterogeneous catalyst for both reactions prepared by immobilizing a molecular iridium organometallic catalyst onto a high-surface mesoporous silica, through a sol-gel methodology. The presence of tailored single-metal catalytic sites, derived by a suitable choice of ligands with desired steric and electronic characteristics, in combination with optimized support features, makes the immobilized catalyst highly active. Furthermore, the information derived from multinuclear DNP-enhanced NMR spectroscopy, elemental analysis, and Ir L3-edge XAS indicates the formation of cationic iridium sites. It is quite remarkable to note that the immobilized catalyst shows essentially the same catalytic activity as its molecular analogue in the hydrogenation of CO2. In the reverse reaction of HCOOH dehydrogenation, it is approximately twice less active but has no induction period.

HTE and Data Analysis for Discovery and Molecular-level Understanding of Catalysts.

The combination of high-throughput experimentation (HTE) and data analysis is a valuable methodology for mechanistic interrogation and rational development of catalysts. In this article, we point out the general structure of HTE-data analysis workflow and illustrate how it can be applied with examples of olefin metathesis and cyanation reactions.

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

Since its early days, olefin metathesis has been in the focus of scientific discussions and technology development. While heterogeneous olefin metathesis catalysts based on supported group 6 metal oxides have been used for decades in the petrochemical industry, detailed mechanistic studies and the development of molecular organometallic chemistry have led to the development of robust and widely used homogeneous catalysts based on well-defined alkylidenes that have found applications for the synthesis of fine and bulk chemicals and are also used in the polymer industry. The development of the chemistry of high-oxidation group 5-7 alkylidenes and the use of surface organometallic chemistry (SOMC) principles unlocked the preparation of so-called well-defined supported olefin metathesis catalysts. The high activity and stability (often superior to their molecular analogues) and molecular-level characterisation of these systems, that were first reported in 2001, opened the possibility for the first direct structure-activity relationships for supported metathesis catalysts. This review describes first the history of SOMC in the field of olefin metathesis, and then focuses on what has happened since 2007, the date of our last comprehensive reviews in this field.

Boosting the Metathesis Activity of Molybdenum Oxo Alkylidenes by Tuning the Anionic Ligand σ Donation.

The catalytic performances of molecular and silica-supported molybdenum oxo alkylidene species bearing anionic O ligands [ORF9, OTPP, OHMT - where ORF9 = OC(CF3)3, OTPP = 2,3,5,6-tetraphenylphenoxy, OHMT = hexamethylterphenoxy] with different σ-donation abilities and sizes are evaluated in the metathesis of both internal and terminal olefins. Here, we show that the presence of the anionic nonafluoro-tert-butoxy X ligand in Mo(O){═CH-4-(MeO)C6H4}(THF)2{X}2 (1; X = ORF9) significantly increases the catalytic performances in the metathesis of both terminal and internal olefins. Its silica-supported equivalent displays slightly lower activity, albeit with improved stability. In sharp contrast, the molecular complexes with large aryloxy anionic X ligands show little activity, whereas the activity of the corresponding silica-supported systems is greatly improved, illustrating that surface siloxy groups are significantly smaller anionic ligands. Of all of the systems, compound 1 stands out because of its unique high activity for both terminal and internal olefins. Density functional theory modeling indicates that the ORF9 ligand is ideal in this series because of its weak σ-donating ability, avoiding overstabilization of the metallacyclobutane intermediates while keeping low barriers for [2 + 2] cycloaddition and turnstile isomerization.

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

A combination of high-throughput experimentation (HTE), surface organometallic chemistry (SOMC) and statistical data analysis provided the platform to analyze in situ silica-grafted Mo imido alkylidene catalysts based on a library of 35 phenols. Overall, these tools allowed for the identification of σ-donor electronic effects and dispersive interactions and as key drivers in a prototypical metathesis reaction, homodimerization of 1-nonene. Univariate and multivariate correlation analysis confirmed the categorization of the catalytic data into two groups, depending on the presence of aryl groups in ortho position of the phenol ligand. The initial activity (TOFin) was predominantly correlated to the σ-donor ability of the aryloxy ligands, while the overall catalytic performance (TON1 h) was mainly dependent on attractive dispersive interactions with the used phenol ligands featuring aryl ortho substituents and, in sharp contrast, repulsive dispersive interactions with phenol free of aryl ortho substituents. This work outlines a fast and efficient workflow of gaining molecular-level insight into supported metathesis catalysts and highlights σ-donor ability and noncovalent interactions as crucial properties for designing active d0 supported metathesis catalysts.

Noncovalent Interactions Drive the Efficiency of Molybdenum Imido Alkylidene Catalysts for Olefin Metathesis.

High-throughput experimentation and multivariate modeling allow identification of noncovalent interactions (NCIs) in monoaryloxy-pyrrolide Mo imido alkylidene metathesis catalysts prepared in situ as a key driver for high activity in a representative metathesis reaction (homodimerization of 1-nonene). Statistical univariate and multivariate modeling categorizes catalytic data from 35 phenolic ligands into two groups, depending on the substitution in the ortho position of the phenol ligand. The catalytic activity descriptor TON1h correlates predominantly with attractive NCIs when phenols bear ortho aryl substituents and, conversely, with repulsive NCIs when the phenol has no aryl ortho substituents. Energetic span analysis is deployed to relate the observed NCI and the cycloreversion metathesis step such that aryloxide ligands with no ortho aryls mainly impact the energy of metallacyclobutane intermediates (SP/TBP isomers), whereas aryloxides with pendant ortho aryls influence the transition state energy for the cycloreversion step. While the electronic effects from the aryloxide ligands also play a role, our work outlines how NCIs may be exploited for the design of improved d0 metathesis catalysts.