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Quantifying Uncertainties in Solvation Procedures for Modeling Aqueous Phase Reaction Mechanisms
preprintsubmitted on 02.10.2020, 03:56 and posted on 05.10.2020, 09:02 by alex maldonado, Satoshi Hagiwara, Tae Hoon Choi, Frank Eckert, Kathleen Schwarz, Ravishankar Sundararaman, Minoru Otani, John Keith
Computational quantum chemistry modeling provides fundamental chemical and physical insights into solvated reaction mechanisms across many areas of chemistry, especially in homogeneous and heterogeneous renewable energy catalysis. Such reactions may depend on explicit interactions with ions and solvent molecules that are non-trivial to characterize. Rigorously modeling explicit solvent effects with molecular dynamics usually brings steep computational costs while the performance of continuum solvent models such as polarizable continuum model (PCM), nonlocal solvent models with charge asymmetry (CANDLE), conductor-like screening model for real solvents (COSMO-RS) and effective screening medium method with the reference interaction site model (ESM-RISM) are less well understood for reaction mechanisms. Here, we revisit a fundamental aqueous phase hydride transfer reaction, carbon dioxide (CO2) reduction by sodium borohydride (NaBH4), as a test case to evaluate how different solvent models perform in aqueous phase charge migrations that would be relevant in general to renewable energy catalysis mechanisms. For this system, quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulations almost exactly reproduced energy profiles from all-QM simulations, and the Na+ counterion in the QM/MM simulations plays an insignificant role over ensemble averaged trajectories that describe the reaction pathway.
However, solvent models used on static calculations gave much more variability in data depending on whether the system was modeled using explicit solvent shells and/or the counter ion. We pinpoint this variability due to unphysical descriptions of charge-separated states in the gas phase (i.e., self-interaction errors), and we show that using more accurate hybrid functionals and/or explicit solvent shells will lessens these errors and allow more reliable results to be obtained.
This work closes with recommended procedures for treating solvation in future computational efforts in studying renewable energy catalysis mechanisms.