Data Science-Enabled Palladium-Catalyzed Enantioselective Aryl-Carbonylation of Sulfonimidamides.

New methods for the general asymmetric synthesis of sulfonimidamides are of great interest due to their applications in medicinal chemistry, agrochemical discovery, and academic research. We report a palladium-catalyzed cross-coupling method for the enantioselective aryl-carbonylation of sulfonimidamides. Using data science techniques, a virtual library of calculated bisphosphine ligand descriptors was used to guide reaction optimization by effectively sampling the catalyst chemical space. The optimized conditions identified using this approach provided the desired product in excellent yield and enantioselectivity. As the next step, a data science-driven strategy was also used to explore a diverse set of aryl and heteroaryl iodides, providing key information about the scope and limitations of the method. Furthermore, we tested a range of racemic sulfonimidamides for compatibility of this coupling partner. The developed method offers a general and efficient strategy for accessing enantioenriched sulfonimidamides, which should facilitate their application in industrial and academic settings.

Data Science Enables the Development of a New Class of Chiral Phosphoric Acid Catalysts.

The widespread success of BINOL-chiral phosphoric acids (CPAs) has led to the development of several high molecular weight, sterically encumbered variants. Herein, we disclose an alternative, minimalistic chiral phosphoric acid backbone incorporating only a single instance of point chirality. Data science techniques were used to select a diverse training set of catalysts, which were benchmarked against the transfer hydrogenation of an 8-aminoquinoline. Using a univariate classification algorithm and multivariate linear regression, key catalyst features necessary for high levels of selectivity were deconvoluted, revealing a simple catalyst model capable of predicting selectivity for out-of-set catalysts. This workflow enabled extrapolation to a catalyst providing higher selectivity than both reported peptide-type and BINOL-type catalysts (up to 95:5 er). These techniques were then successfully applied towards two additional transforms. Taken together, these examples illustrate the power of combining rational design with data science (ab initio) to efficiently explore reactivity during catalyst development.

Development of high-voltage bipolar redox-active organic molecules through the electronic coupling of catholyte and anolyte structures.

All-organic non-aqueous redox flow batteries (O-NRFBs) are a promising technology for grid-scale energy storage. However, most examples of high-voltage (>2 V) O-NRFBs rely upon the use of distinct anolytes and catholytes separated by a membrane or porous separator which can result in crossover of redox active material from one side of the battery to the other. The resulting electrolyte mixing leads to irreversible reductions in energy density and capacity. A potentially attractive solution to overcome this crossover issue is the implementation of symmetric flow batteries where a single bipolar molecule functions as both an anolyte and a catholyte. Herein, we report the development of a new class of bipolar redox active materials for use in such symmetric flow batteries through the electronic coupling of phenothiazine catholytes and phthalimide anolytes. Such a strategy results in hybrid molecules possessing higher cell voltages than what could be obtained together by their uncoupled building blocks. Performance in flow batteries is demonstrated for two members of this new class of molecules, with the highest performing candidate featuring a ΔE of 2.31 V and demonstrating 93.6% average coulombic efficiency, 86.8% energy efficiency, and 68.6% capacity retention over the course of 275 charge-discharge cycles and 5 cell polarity reversals. Finally, the superior performance of symmetric O-NRFBs is experimentally confirmed by comparing these results to an asymmetric flow battery constructed with a distinct phenothiazine catholyte and a distinct phthalimide anolyte on opposing sides of the cell.

Solvation Dynamics and the Nature of Reaction Barriers and Ion-Pair Intermediates in Carbocation Reactions.

Additions of acids to 1,3-dienes are conventionally understood as involving discrete intermediates that undergo an ordinary competition between subsequent pathways to form the observed products. The combined experimental, computational, and dynamic trajectory study here suggests that this view is incorrect, and that solvation dynamics plays a critical role in the mechanism. While implicit solvent models were inadequate, QM/QM' trajectories in explicit solvent provide an accurate prediction of the experimental selectivity in the addition of HCl to 1,3-pentadiene. Trajectories initiated from a protonation saddle point on the potential of mean force surface are predominantly unproductive due to a gating effect of solvation that allows diene protonation only when the incipient ion pair is neither too solvent-stabilized nor too little. Protonation then leads to relatively unsolvated ion pairs, and a majority of these collapse rapidly to the 1,2-product, without barrier and without achieving equilibrium solvation as intermediates. The remainder decay slowly, at a rate consistent with equilibrium solvation as true intermediates, affording a mixture of addition products. Overall, an accurate description of the nature and pathway selectivity of the ion pair intermediates in carbocation reactions must allow for species lacking equilibrium solvation. Potential reinterpretations of a series of historically notable observations in carbocation reactions are discussed.

Bond Memory in Dynamically Determined Stereoselectivity.

The carboborative ring contraction of cyclohexenes exhibits an abnormal selectivity pattern in which a formally concerted double migration gives rise to predominant but not exclusive inversion products. In dynamic trajectories, the inversion and retention products are formed from the same transition state, and the trajectories accurately account for the experimental product ratios. The unusual origin of the selectivity is the dynamically retained non-equivalence of newly formed versus pre-existing bonds after the first bond migration.

Comment on "Activation of methane to CH3 +: A selective industrial route to methanesulfonic acid".

Díaz-Urrutia and Ott (Reports, 22 March 2019, p. 1326) report a selective conversion of methane to methanesulfonic acid that is proposed to occur by a cationic chain reaction in which CH3 + adds to sulfur trioxide (SO3) to form CH3-S(O)2O+ This mechanism is not plausible because of the solvent reactivity of CH3 +, the non-nucleophilicity of the sulfur atom of SO3, and the high energy of CH3-S(O)2O^.

13 C Kinetic Isotope Effects as a Quantitative Probe To Distinguish between Enol and Enamine Mechanisms in Aminocatalysis.

A combination of experimental 13 C kinetic isotope effects (KIEs) and high-level density functional theory (DFT) calculations is used to distinguish between "enamine" and "enol" mechanisms in the Michael addition of acetone to trans-ß-nitrostyrene catalyzed by Jacobsen's primary amine thiourea catalyst. In light of the recent findings that the widely used 18 O-incorporation probe for these mechanisms is flawed, the results described in this communication demonstrate an alternative probe to distinguish between these pathways. A key advantage of this probe is that quantitative mechanistic information is obtained without modifying experimental conditions. This approach is expected to find application in resolving mechanistic debates, while providing valuable information about the key transition state of organocatalyzed reactions involving the α-functionalization of carbonyls.