Molecular Dynamics of Iron Porphyrin-Catalyzed C-H Hydroxylation of Ethylbenzene

Physics-Informed Active Learning for Accelerating Quantum Chemical Simulations

Quantum chemical simulations can be greatly accelerated by constructing machine learning potentials, which is often done using active learning (AL). The usefulness of the constructed potentials is often limited by the high effort required and their insufficient robustness in the simulations. Here, we introduce the end-to-end AL for constructing robust data-efficient potentials with affordable investment of time and resources and minimum human interference. Our AL protocol is based on the physics-informed sampling of training points, automatic selection of initial data, uncertainty quantification, and convergence monitoring. The versatility of this protocol is shown in our implementation of quasi-classical molecular dynamics for simulating vibrational spectra, conformer search of a key biochemical molecule, and time-resolved mechanism of the Diels-Alder reaction. These investigations took us days instead of weeks of pure quantum chemical calculations on a high-performance computing cluster.

Evidence for Dearomatizing Spirocyclization and Dynamic Effects in the Quasi-stereospecific Nitrogen Deletion of Tetrahydroisoquinolines

Selectivity in organic chemistry is generally presumed to arise from energy differences between competing selectivity-determining transition states. However, in cases where static density functional theory (DFT) fails to reproduce experimental product distributions, dynamic effects can be examined to understand the behavior of more complex reaction systems. Previously, we reported a method for nitrogen deletion of secondary amines which relies on the formation of isodiazene intermediates that subsequently extrude dinitrogen with concomitant C-C bond formation via a caged diradical. Herein, a detailed mechanistic analysis of the nitrogen deletion of 1-aryl-tetrahydroisoquinolines is presented, suggesting that in this system the previously determined diradical mechanism undergoes dynamically controlled partitioning to both the normal 1,5-coupling product and an unexpected spirocyclic dearomatized intermediate, which converges to the expected indane by an unusually facile 1,3-sigmatropic rearrangement. This mechanism is not reproduced by static DFT but is supported by quasi-classical molecular dynamics calculations and unifies several unusual observations in this system, including partial chirality transfer, nonstatistical isotopic scrambling at the ethylene bridge, the isolation of spirocyclic dearomatized species in a related heterocyclic series, and the observation that introduction of an 8-substituent dramatically improves enantiospecificity.

Manganese Complex Catalyzed Sequential Multi-component Reaction: Enroute to a Quinoline-Derived Azafluorenes

The development of innovative synthetic strategies for constructing complex molecular structures is the heart of organic chemistry. This significance of novel reactions or reaction sequences would further enhance if they permitted the synthesis of new classes of structural motifs, which have not been previously created. The research on the synthesis of heterocyclic compounds is one of the most active topics in organic chemistry due to the widespread application of N-heterocycles in life and material science. The development of a new catalytic process that employs first-row transition metals to produce a range of heterocycles from renewable raw materials is considered highly sustainable approach. This would be more advantageous if done in an eco-friendly and atom-efficient manner. Herein we introduce, the synthesis of various new quinoline based azafluorenes via sequential dehydrogenative multicomponent reaction (MCR) followed by C(sp3)-H hydroxylation and annulation. Our newly developed, Mn-complexes have the ability to direct the reaction in order to achieve a high amount of desired functionalized heterocycles while minimizing the possibility of multiple side reactions. We also performed a series of control experiments, hydride trapping experiments, reaction kinetics, catalytic intermediate and DFT studies to comprehend the detailed reaction route and the catalyst's function in the MCR sequence.

Dynamical Origin of Rebound versus Dissociation Selectivity during Fe-Oxo-Mediated C-H Functionalization Reactions

The mechanism of catalytic C-H functionalization of alkanes by Fe-oxo complexes is often suggested to involve a hydrogen atom transfer (HAT) step with the formation of a radical-pair intermediate followed by diverging pathways for radical rebound, dissociation, or desaturation. Recently, we showed that in some Fe-oxo reactions, the radical pair is a nonstatistical-type intermediate and dynamic effects control rebound versus dissociation pathway selectivity. However, the effect of the solvent cage on the stability and lifetime of the radical-pair intermediate has never been analyzed. Moreover, because of the extreme complexity of motion that occurs during dynamics trajectories, the underlying physical origin of pathway selectivity has not yet been determined. For the reaction between [(TQA_Cl)FeIVO]+ and cyclohexane, here, we report explicit solvent trajectories and machine learning analysis on transition-state sampled features (e.g., vibrational, velocity, and geometric) that identified the transferring hydrogen atom kinetic energy as the most important factor controlling rebound versus nonrebound dynamics trajectories, which provides an explanation for our previously proposed dynamic matching effect in fast rebound trajectories that bypass the radical-pair intermediate. Manual control of the reaction trajectories confirmed the importance of this feature and provides a mechanism to enhance or diminish selectivity for the rebound pathway. This led to a general catalyst design principle and proof-of-principle catalyst design that showcases how to control rebound versus dissociation reaction pathway selectivity.