Calculating Entropies of Large Molecules in Aqueous Phase

Automated Microsolvation for Minimum Energy Path Construction in Solution

Describing chemical reactions in solution on a molecular level is a challenging task due to the high mobility of weakly interacting solvent molecules which requires configurational sampling. For instance, polar and protic solvents can interact strongly with solutes and may interfere in reactions. To define and identify representative arrangements of solvent molecules modulating a transition state is a nontrivial task. Here, we propose to monitor their active participation in the decaying normal mode at a transition state, which defines active solvent molecules. Moreover, it is desirable to prepare a low-dimensional microsolvation model in a well-defined, fully automated, high-throughput, and easy-to-deploy fashion, which we propose to derive in a stepwise protocol. First, transition state structures are optimized in a sufficiently solvated quantum-classical hybrid model, which are subjected to a redefinition of a then reduced quantum region. From the reduced model, minimally microsolvated structures are extracted that contain only active solvent molecules. Modeling the remaining solvation effects is deferred to a continuum model. To establish an easy-to-use free-energy model, we combine the standard thermochemical gas-phase model with a correction for the cavity entropy in solution. We assess our microsolvation and free-energy models for methanediol formation from formaldehyde; for the hydration of carbon dioxide (which we consider in a solvent mixture to demonstrate the versatility of our approach); and, finally, for the chlorination of phenol with hypochlorous acid.

CoTCNQ as a Catalyst for CO2 Electroreduction: A First Principles r2SCAN Meta-GGA Investigation

Using first principles calculations we investigate cobalt-coordinated tetracyanoquinodimethane (R-CoTCNQ) as a potential catalyst for the CO2 electroreduction reaction (CO2ERR). We determine that exchange-correlation functionals beyond the generalized gradient approximation (GGA) are required to accurately describe the spin properties of R-CoTCNQ, therefore, the meta-GGA r2SCAN functional is used in this study. The free energy CO2ERR reaction pathways are calculated for the reduced catalyst ([R-CoTCNQ]-1e) with reaction products HCOOH and HCHO predicted depending on our choice of electrode potential. Calculations are also performed for [R-CoTCNQ]-1e supported on a H-terminated diamond (1 1 0) surface with reaction pathways being qualitatively similar to the [R-CoTCNQ]-1e monolayer. The inclusion of boron-doping in the diamond support shows a slightly improved CO2ERR reaction pathway. Furthermore, structurally, supported R-CoTCNQ provide a high specific area of active Co active sites and could be promising catalysts for future experimental consideration.

Harnessing Ultrasound-Derived Hydroxyl Radicals for the Selective Oxidation of Aldehyde Functions

Ultrasonic irradiation holds potential for the selective oxidation of non-volatile organic substrates in the aqueous phase by harnessing hydroxyl radicals as chemical initiators. Here, a mechanistic description of hydroxyl radical-initiated glyoxal oxidation is constructed by gleaning insights from photolysis and radiation chemistry to explain the yields and kinetic trends for oxidation products. The mechanistic description and kinetic measurements reported herein reveal that increasing the formation rate of hydroxyl radicals by changing the ultrasound frequency increases both the rates of glyoxal consumption and the selectivity towards C2 acid products over those from C-C cleavage. Glyoxal consumption also occurs more rapidly and with greater selectivity towards C2 acids under acidic conditions, which favor the protonation of carboxylate intermediates into their less reactive acidic forms. Leveraging such pH and frequency effects is crucial to mitigating product degradation by secondary reactions with hydroxyl radicals and oxidation products (specifically hydrogen peroxide and superoxide). These findings demonstrate the potential of ultrasound as a driver for the selective oxidation of aldehyde functions to carboxylic acids, offering a sustainable route for valorizing biomass-derived platform molecules.

On the prediction by density functional theory of entropies in solution within implicit solvation models

CONTEXT

Entropies are fundamental contributions to Gibbs energies that carry important chemical information, in particular when investigating reaction mechanisms. However, evaluating them in solution is far from being straightforward. In this paper, we focus on its evaluation within the framework of implicit solvation models. To this aim, successive corrections (with increased complexity) involving only contributions available from any standard quantum chemistry code and macroscopic solvent properties are built and assessed by comparison to more than one hundred experimental entropy values measured in a liquid phase. It turns out that significant improvement with respect to the standard ideal gas approximation can be achieved at an almost negligible computational cost, affording a robust and transferable predictive model.

METHODS

DFT calculations with the ADF software at the PBE or PBE0/TZ2P level of theory with COSMO solvent model. Python scripts for regressions.

The entropic penalty for associative reactions and their physical treatment during routine computations

A systematic study of the entropic penalty for associative reactions is presented. It is shown that computed solution-phase Gibbs free energies typically overestimate entropic contributions. This entropic penalty for associative reactions in solution, i.e., if the number of particles decreases along the reaction coordinate (sum of stoichiometric numbers ), originates from the insufficient treatment of entropic effects by implicit solvent models. We propose an additive correction scheme to Gibbs free energies that is suitable for routine applications by non-expert users. This correction is based on Garza's formalism for the solution-phase entropy [A. J. Garza, J. Chem. Theory Comput., 2019, 15, 3204.] that is physically sound and embedded into an efficient black-box type algorithm. To critically evaluate the entropic penalty and its proposed treatment, we compiled an experimental benchmark set of 31 Δ_rG and 22 in 15 different solvents. Using a representative best-practice computational protocol (at wave function theory (WFT) based DLPNO-CCSD(T) and density functional theory (DFT) based revDSD-PBEP86-D4 level with an implicit solvent model), we determined a sizeable entropic penalty ranging from 2-11 kcal mol^-1. Using the correction scheme presented herein, the entropic penalty is corrected to the chemical accuracy of ≤1 kcal mol^-1 (WFT and DFT). The same applies to at the WFT level. Barriers at the DFT level are overestimated by 2 kcal mol^-1 (classic) and underestimated by 2 kcal mol^-1 (corrected). This effect is attributed to the finding that barriers computed at the DFT level are systematically 2-3 kcal mol^-1 lower than barriers obtained with WFT.

Portable Models for Entropy Effects on Kinetic Selectivity

Differences in entropies of competing transition states can direct kinetic selectivity. Understanding and modeling such entropy differences at the molecular level is complicated by the fact that entropy is statistical in nature; i.e., it depends on multiple vibrational states of transition structures, the existence of multiple dynamically accessible pathways past these transition structures, and contributions from multiple transition structures differing in conformation/configuration. The difficulties associated with modeling each of these contributors are discussed here, along with possible solutions, all with an eye toward the development of portable qualitative models of use to experimentalists aiming to design reactions that make use of entropy to control kinetic selectivity.

Towards understanding solvation effects on the conformational entropy of non-rigid molecules

The absolute molecular entropy is a fundamental quantity for the accurate description of thermodynamic properties. For non-rigid molecules, a substantial part of the entropy can be attributed to a conformational contribution. Systems and properties where this is relevant, e.g., protein-ligand binding affinities or pK_a values refer usually to the liquid phase. In this work, the influence of solvation on the conformational entropy is investigated. A recently introduced state-of-the-art and automated computational protocol for the computation of conformational entropies [Pracht et al., Chem. Sci., 2021, 12, 6551-6568.] is applied in combination with fast and accurate semiempirical quantum-chemical methods and implicit solvation models for a set of 25 commercially available drug molecules and five transition metal compounds. Computed gas-phase conformational entropies are compared with values obtained in implicit n-hexane and water. It is found that implicit solvation can have a substantial effect of several cal mol^-1 K^-1 on the entropy as a result of large conformational changes in the different phases. We conclude that for flexible molecules chemical accuracy for free energies in solution can only be achieved if solvation effects on the conformational ensemble are considered.