Catalysis with a Skip: Dynamically Coupled Addition, Proton Transfer, and Elimination During Au- and Pd-Catalyzed Diol Cyclization

Author(s):  
Matthew Teynor ◽  
Windsor Scott ◽  
Daniel Ess

Au and Pd complexes have emerged as highly effective π-bond cyclization catalysts to construct heterocycles. These cyclization reactions are generally proposed to proceed through multi-step addition-elimination mechanisms involving Au- or Pd-alkyl intermediates. For Au- and Pd-catalyzed allylic diol cyclization, while the DFT potential energy surface landscapes show a stepwise sequence of alkoxylation π-addition, proton transfer, and water elimination, quasiclassical direct dynamics simulations reveal new dynamical mechanisms that depend on the metal center. For Au, trajectories reveal that after π-addition the Au-alkyl intermediate is always skipped because addition is dynamically coupled with proton transfer and water elimination. In contrast, for Pd catalysis, due to differences in the potential-energy landscape shape, only about half of trajectories show Pd-alkyl intermediate skipping. The other half of the trajectories show the traditional two-step mechanism with the intervening Pd-alkyl intermediate. Overall, this work reveals that interpretation of a DFT potential-energy landscape can be insufficient to understand catalytic intermediates and mechanisms and that atomic momenta through dynamics simulations is needed to determine if an intermediate is genuinely part of a catalytic cycle.<br>

2021 ◽  
Author(s):  
Matthew Teynor ◽  
Windsor Scott ◽  
Daniel Ess

Au and Pd complexes have emerged as highly effective π-bond cyclization catalysts to construct heterocycles. These cyclization reactions are generally proposed to proceed through multi-step addition-elimination mechanisms involving Au- or Pd-alkyl intermediates. For Au- and Pd-catalyzed allylic diol cyclization, while the DFT potential energy surface landscapes show a stepwise sequence of alkoxylation π-addition, proton transfer, and water elimination, quasiclassical direct dynamics simulations reveal new dynamical mechanisms that depend on the metal center. For Au, trajectories reveal that after π-addition the Au-alkyl intermediate is always skipped because addition is dynamically coupled with proton transfer and water elimination. In contrast, for Pd catalysis, due to differences in the potential-energy landscape shape, only about half of trajectories show Pd-alkyl intermediate skipping. The other half of the trajectories show the traditional two-step mechanism with the intervening Pd-alkyl intermediate. Overall, this work reveals that interpretation of a DFT potential-energy landscape can be insufficient to understand catalytic intermediates and mechanisms and that atomic momenta through dynamics simulations is needed to determine if an intermediate is genuinely part of a catalytic cycle.<br>


2020 ◽  
Vol 117 (26) ◽  
pp. 14987-14995 ◽  
Author(s):  
Ratan Othayoth ◽  
George Thoms ◽  
Chen Li

Effective locomotion in nature happens by transitioning across multiple modes (e.g., walk, run, climb). Despite this, far more mechanistic understanding of terrestrial locomotion has been on how to generate and stabilize around near–steady-state movement in a single mode. We still know little about how locomotor transitions emerge from physical interaction with complex terrain. Consequently, robots largely rely on geometric maps to avoid obstacles, not traverse them. Recent studies revealed that locomotor transitions in complex three-dimensional (3D) terrain occur probabilistically via multiple pathways. Here, we show that an energy landscape approach elucidates the underlying physical principles. We discovered that locomotor transitions of animals and robots self-propelled through complex 3D terrain correspond to barrier-crossing transitions on a potential energy landscape. Locomotor modes are attracted to landscape basins separated by potential energy barriers. Kinetic energy fluctuation from oscillatory self-propulsion helps the system stochastically escape from one basin and reach another to make transitions. Escape is more likely toward lower barrier direction. These principles are surprisingly similar to those of near-equilibrium, microscopic systems. Analogous to free-energy landscapes for multipathway protein folding transitions, our energy landscape approach from first principles is the beginning of a statistical physics theory of multipathway locomotor transitions in complex terrain. This will not only help understand how the organization of animal behavior emerges from multiscale interactions between their neural and mechanical systems and the physical environment, but also guide robot design, control, and planning over the large, intractable locomotor-terrain parameter space to generate robust locomotor transitions through the real world.


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