Machine Learning C-N Couplings: Obstacles for a General-Purpose Reaction Yield Prediction.

Pd-catalyzed C-N couplings are commonplace in academia and industry. Despite their significance, finding suitable reaction conditions leading to a high yield, for instance, remains a challenging and time-consuming task which usually requires screening over many sets of conditions. To help select promising reaction conditions in the vast space of reagent combinations, machine learning is an emerging technique with a lot of promise. In this work, we assess whether the reaction yield of C-N couplings can be predicted from databases of chemical reactions. We test the generalizability of models both on challenging data splits and on a dedicated experimental test set. We find that, provided the chemical space represented by the training set is not left, the models perform well. However, the applicability domain is quickly left even for simple reactions of the same type, as, for instance, present in our plate test set. The results show that yield prediction for new reactions is possible from the algorithmic side but in practice is hindered by the available data. Most importantly, more data that cover the diversity in reagents are needed for a general-purpose prediction of reaction yields. Our findings also expose a challenge to this field in that it appears to be extremely deceiving to judge models based on literature data with test sets which are split off the same literature data, even when challenging splits are considered.

Water as a Blood Model for Determination of CO2 Removal Performance of Membrane Oxygenators.

CO2 removal via membrane oxygenators has become an important and reliable clinical technique. Nevertheless, oxygenators must be further optimized to increase CO2 removal performance and to reduce severe side effects. Here, in vitro tests with water can significantly reduce costs and effort during development. However, they must be able to reasonably represent the CO2 removal performance observed with blood. In this study, the deviation between the CO2 removal rate determined in vivo with porcine blood from that determined in vitro with water is quantified. The magnitude of this deviation (approx. 10%) is consistent with results reported in the literature. To better understand the remaining difference in CO2 removal rate and in order to assess the application limits of in vitro water tests, CFD simulations were conducted. They allow to quantify and investigate the influences of the differing fluid properties of blood and water on the CO2 removal rate. The CFD results indicate that the main CO2 transport resistance, the diffusional boundary layer, behaves generally differently in blood and water. Hence, studies of the CO2 boundary layer should be preferably conducted with blood. In contrast, water tests can be considered suitable for reliable determination of the total CO2 removal performance of oxygenators.

What can reaction databases teach us about Buchwald-Hartwig cross-couplings?

Despite the widespread and increasing usage of Pd-catalyzed C-N cross couplings, finding good conditions for these reactions can be challenging. Practitioners mostly rely on few methodology studies or anecdotal experience. This is surprising, since the advent of data-driven experimentation and the large amount of knowledge in databases allow for data-driven insight. In this work, we address this by analyzing more than 62 000 Buchwald-Hartwig couplings gathered from CAS, Reaxys and the USPTO. Our meta-analysis of the reaction performance generates data-driven cheatsheets for reaction condition recommendation. It also provides an interactive tool to find rarer ligands with optimal performance regarding user-selected substrate properties. With this we give practitioners promising starting points. Furthermore, we study bias and diversity in the literature and summarize the current state of the reaction data, including its pitfalls. Hence, this work will also be useful for future data-driven developments such as the optimization of reaction conditions via machine learning.

Lewis Acid Catalyzed Synthesis of α-Trifluoromethyl Esters and Lactones by Electrophilic Trifluoromethylation.

An electrophilic trifluoromethylation of ketene silyl acetals (KSAs) by hypervalent iodine reagents 1 and 2 has been developed. The reaction proceeds under very mild conditions in the presence of a catalytic amount of trimethylsilyl bis(trifluoromethanesulfonyl)imide (up to 2.5 mol %) as a Lewis acid providing a direct access to a variety of secondary, tertiary, and quaternary α-trifluoromethyl esters and lactones in high yield (up to 98%).

Acid-mediated formation of trifluoromethyl sulfonates from sulfonic acids and a hypervalent iodine trifluoromethylating agent.

A variety of sulfonic acids have been trifluoromethylated using 1-trifluoromethyl-1,2-benziodoxol-3(1H)-one under mild conditions in good to excellent yields. Initial mechanistic investigations of this reaction show a clean second-order kinetics and only very weak substrate electronic effects.

Zinc-mediated formation of trifluoromethyl ethers from alcohols and hypervalent iodine trifluoromethylation reagents.

A (fluor)ry of activity: The transfer of an intact trifluoromethyl group from a hypervalent iodine reagent to an aliphatic alcohol occurs smoothly upon activation by zinc bis(triflimide). This constitutes a straightforward method for the preparation of trifluoromethoxy alkyl derivatives, compounds otherwise difficult to access.

Reactivity of a 10-I-3 hypervalent iodine trifluoromethylation reagent with phenols.

The reaction of the 10-I-3 hypervalent iodine electrophilic trifluoromethylation reagent 1-trifluoromethyl-1,2-benziodoxol-3-(1H)-one (2) with 2,4,6-trimethylphenol, after deprotonation with NaH and in the presence of 18-crown-6 in a polar, nonprotic solvent, affords 1,3,5-trimethyl-2-(trifluoromethoxy)benzene (4) only as a byproduct. Trifluoromethylation occurs preferentially at the ortho- and para-positions of the aromatic core, giving the corresponding trifluoromethylcyclohexadienones 5 and 6. In case the ortho- and/or para-positions are not substituted, the corresponding products of an aromatic, electrophilic substitution are obtained in moderate yield, for example, 2-trifluoromethyl-4-tert-butylphenol (10a) from 4-tert-butylphenol (10).