Hybrid discrete‐continuum solvation methods

Computational Design of an Electro-Organocatalyst for Conversion of CO2 into Long Chain Aldehydes

Density functional theory calculations employing a hybrid implicit/explicit solvation method were used to demonstrate that an electro-organocatalyst designed in our previous work for reducing CO2 to formaldehyde could also be capable of coupling formaldehyde to form long chain aldehydes. The catalytic activity is enabled by an electron-rich vicinal enediamine (>N-C═C-N<) backbone that activates formaldehyde by reversing the polarity on the carbon atom, enabling it to act as a nucleophile in the subsequent aldol addition step. The catalyst then enables reductive dehydroxylation of the aldol addition product by facilitating outer-sphere electron transfer. The optimal pH as well as the limiting potential and formaldehyde concentration are identified and related to the kinetic balance between several rate limiting steps. Finally, the optimal conditions for coupling with the CO2 reduction cycle are discussed, demonstrating that the electro-organocatalyst is capable of efficiently converting CO2 into aldehyde products with a turnover frequency (per carbon atom) on the order of 0.1-1 s-1.

Flavin-N5OOH Functions as both a Powerful Nucleophile and a Base in the Superfamily of Flavoenzymes

Flavoenzymes can mediate a large variety of oxidation reactions through the activation of oxygen. However, the O2 activation chemistry of flavin enzymes is not yet fully exploited. Normally, the O2 activation occurs at the C4a site of the flavin cofactor, yielding the flavin C4a-(hydro)hydroperoxyl species in monooxygenases or oxidases. Using extensive MD simulations, QM/MM calculations and QM calculations, our studies reveal the formation of the common nucleophilic species, Flavin-N5OOH, in two distinct flavoenzymes (RutA and EncM). Our studies show that Flavin-N5OOH acts as a powerful nucleophile that promotes C-N cleavage of uracil in RutA, and a powerful base in the deprotonation of substrates in EncM. We reason that Flavin-N5OOH can be a common reactive species in the superfamily of flavoenzymes, which accomplish generally selective general base catalysis and C-X (X=N, S, Cl, O) cleavage reactions that are otherwise challenging with solvated hydroxide ion base. These results expand our understanding of the chemistry and catalysis of flavoenzymes.

CREST-A program for the exploration of low-energy molecular chemical space

Conformer-rotamer sampling tool (CREST) is an open-source program for the efficient and automated exploration of molecular chemical space. Originally developed in Pracht et al. [Phys. Chem. Chem. Phys. 22, 7169 (2020)] as an automated driver for calculations at the extended tight-binding level (xTB), it offers a variety of molecular- and metadynamics simulations, geometry optimization, and molecular structure analysis capabilities. Implemented algorithms include automated procedures for conformational sampling, explicit solvation studies, the calculation of absolute molecular entropy, and the identification of molecular protonation and deprotonation sites. Calculations are set up to run concurrently, providing efficient single-node parallelization. CREST is designed to require minimal user input and comes with an implementation of the GFNn-xTB Hamiltonians and the GFN-FF force-field. Furthermore, interfaces to any quantum chemistry and force-field software can easily be created. In this article, we present recent developments in the CREST code and show a selection of applications for the most important features of the program. An important novelty is the refactored calculation backend, which provides significant speed-up for sampling of small or medium-sized drug molecules and allows for more sophisticated setups, for example, quantum mechanics/molecular mechanics and minimum energy crossing point calculations.

Role of Explicit Solvation in Computational Modeling of Chemical Reactions: Mechanism of Cu(I) Transfer Between Thiolate-Based Chelators in Water

Solvation plays important roles in controlling the thermodynamic and kinetic aspects of chemical reactions. The conventional approaches to treat solvation via electronic structure methods are likely to become inadequate, when the reacting solutes have strong electrostatic and hydrogen bonding interactions with the solvent and undergo significant structural changes during the course of the reaction. In this article, we present evidence of such solvent and structural effects in the computational study of the Cu(I) transfer reaction between thiolate-based chelators dithiobutylamine (DTBA) and dithiotheritol (DTT) in water, inspired from biological copper trafficking phenomena. We propose a general solution to the problem by combining classical molecular dynamics (MD) simulations of the bulk system and static quantum chemistry calculations. The fluctuating solvation shell was estimated from MD, and energetics was assessed by averaging QM energies of a series of molecular clusters constructed from the MD snapshots. Applying this approach, we propose a reaction pathway with estimates of relative intermediate stabilities and barriers, which suggest the overall reaction to be reversible in nature and likely to go through both two and three coordinated intermediates, confirming previous studies of similar protein analogues. An interesting fact that emerged from our study was the strong indication that the rate-determining step is the deprotonation of initial thiol bound Cu(I) complex, without involving any Cu(I)-S bonds. The proposed method will lead to a better treatment of solvations, and these mechanistic insights will aid our understanding of biological copper(I) trafficking.

Improving Quantum Chemical Solvation Models by Dynamic Radii Adjustment for Continuum Solvation (DRACO)

We present the Dynamic Radii Adjustment for COntinuum solvation (DRACO) approach, which employs precomputed atomic partial charges and coordination numbers of the solute atoms to improve the solute cavity. As such, DRACO is compatible with major solvation models, improving their performance significantly and robustly at virtually no extra cost, especially for charged solutes. Combined with the purely electrostatic CPCM and COSMO models, DRACO reduces the mean absolute deviation (MAD) of the solvation free energy by up to 4.5 kcal mol-1 (67%) for a large data set of polar and ionic solutes. Even in combination with the highly empirical universal solvation model (SMD), DRACO substantially reduces the MAD for charged solutes by up to 1.5 kcal mol-1 (39%), while neutral solutes are slightly improved (0.2 kcal mol-1 or 16%). We present an interface of DRACO with two computationally efficient atomic charge models that enables fully automated, out-of-the-box calculations with the widely used program packages Orca and TurboMole.

Computational Design of an Electro-Organocatalyst for Conversion of CO2 into Formaldehyde

Density functional theory calculations employing a hybrid implicit/explicit solvation method were used to explore a new strategy for electrochemical conversion of CO2 using an electro-organocatalyst. A particular structural motif is identified that consists of an electron-rich vicinal enediamine (>N-C═C-N<) backbone, which is capable of activating CO2 by the formation of a C-C bond while subsequently facilitating the transfer of electrons from a chemically inert cathode to ultimately produce formaldehyde. Unlike transition metal-based electrocatalysts, the electro-organocatalyst is not constrained by scaling relations between the formation energies of activated CO2 and adsorbed CO, nor is it expected to be active for the competing hydrogen evolution reaction. The rate-limiting steps are found to occur during two proton-coupled electron transfer (PCET) sequences and are associated with the transfer of a proton from a proton transfer mediator to a carbon atom on the electro-organocatalyst. The difficulty of this step in the second PCET sequence necessitates an electrode potential of -0.85 V vs RHE to achieve the maximum turnover frequency. In addition, it is postulated that the electro-organocatalyst should also be capable of forming long-chain aldehydes by successively carrying out reductive aldol condensation to grow the alkyl chain one carbon at a time.

Recent developments and applications of reference interaction site model self-consistent field with constrained spatial electron density (RISM-SCF-cSED): A hybrid model of quantum chemistry and integral equation theory of molecular liquids

The significance of solvent effects in electronic structure calculations has long been noted, and various methods have been developed to consider this effect. The reference interaction site model self-consistent field with constrained spatial electron density (RISM-SCF-cSED) is a hybrid model that combines the integral equation theory of molecular liquids with quantum chemistry. This method can consider the statistically convergent solvent distribution at a significantly lower cost than molecular dynamics simulations. Because the RISM theory explicitly considers the solvent structure, it performs well for systems where hydrogen bonds are formed between the solute and solvent molecules, which is a challenge for continuum solvent models. Taking advantage of being founded on the variational principle, theoretical developments have been made in calculating various properties and incorporating electron correlation effects. In this review, we organize the theoretical aspects of RISM-SCF-cSED and its distinctions from other hybrid methods involving integral equation theories. Furthermore, we carefully present its progress in terms of theoretical developments and recent applications.

Voltage prediction of vanadium redox flow batteries from first principles

Global energy demand has been increasing for decades, which has created a necessity for large scale energy storage solutions for renewable energy sources. We studied the voltage of vanadium redox flow batteries (VRFBs) with density functional theory (DFT) and a newly developed technique usingab initiomolecular dynamics (AIMD). DFT was used to create cluster models to calculate the voltage of VRFBs. However, DFT is not suited for capturing the dynamics and interactions in a liquid electrolyte, leading to the need for AIMD, which is capable of accurately modeling such things. The molarities and densities of all systems were carefully considered to match experimental conditions. With the use of AIMD, we calculated a voltage of 1.23 V, which compares well with the experimental value of 1.26 V. The techniques developed using AIMD for voltage calculations will be useful for the investigation of potential future battery technologies or as a screening process for additives to make improvements to currently available batteries.

Experimental Compilation and Computation of Hydration Free Energies for Ionic Solutes

Although charged solutes are common in many chemical systems, traditional solvation models perform poorly in calculating solvation energies of ions. One major obstacle is the scarcity of experimental data for solvated ions. In this study, we release an experiment-based aqueous ionic solvation energy data set, IonSolv-Aq, that contains hydration free energies for 118 anions and 155 cations, more than 2 times larger than the set of hydration free energies for singly charged ions contained in the 2012 Minnesota Solvation Database commonly used in benchmarking studies. We discuss sources of systematic uncertainty in the data set and use the data to examine the accuracy of popular implicit solvation models COSMO-RS and SMD for predicting solvation free energies of singly charged ionic solutes in water. Our results indicate that most SMD and COSMO-RS modeling errors for ionic solutes are systematic and correctable with empirical parameters. We discuss two systematic offsets: one across all ions and one that depends on the functional group of the ionization site. After correcting for these offsets, solvation energies of singly charged ions are predicted using COSMO-RS to 3.1 kcal mol-1 MAE against a challenging test set and 1.7 kcal mol-1 MAE (about 3% relative error) with a filtered test set. The performance of SMD is similar, with MAE against those same test sets of 2.7 and 1.7 kcal mol-1. These results underscore the importance of compiling larger experimental data sets to improve solvation model parametrization and fairly assess performance.

Modelling solute-solvent interactions in VCD spectra analysis with the micro-solvation approach

Vibrational circular dichroism (VCD) spectroscopy has become an important part of the (stereo-)chemists' toolbox as a reliable method for the determination of absolute configurations. Being the chiroptical version of infrared spectroscopy, it has also been recognized as being very sensitive to conformational changes and intermolecular interactions. This sensitivity originates from the fact that the VCD spectra of individual conformers are often more different than their IR spectra, so that changes in conformational distributions or band positions and intensities become more pronounced. What is an advantage for studies focussing on intermolecular interactions can, however, quickly turn into a major obstacle during AC determinations: solute-solvent interactions can have a strong influence on spectral signatures and they must be accurately treated when simulating VCD and IR spectra. In this perspective, we showcase selected examples which exhibit particularly pronounced solvent effects. It is demonstrated that it is typically sufficient to model solute-solvent interactions by placing single solvent molecules near hydrogen bonding sites of the solute and subsequently use the optimized structures for spectra simulations. This micro-solvation approach works reasonably well for medium-sized, not too conformationally flexible molecules. We thus also discuss its limitations and outline the next steps that method development needs to take in order to further improve the workflows for VCD spectra predictions.

First hyperpolarizability of the di-8-ANEPPS and DR1 nonlinear optical chromophores in solution. An experimental and multi-scale theoretical chemistry study

The solvent effects on the linear and second-order nonlinear optical properties of an aminonaphtylethenylpyridinium (ANEP) dye are investigated by combining experimental and theoretical chemistry methods. On the one hand, deep near infrared (NIR) hyper-Rayleigh scattering (HRS) measurements (1840-1950 nm) are performed on solutions of di-8-ANEPPS in deuterated chloroform, dimethylformamide, and dimethylsulfoxide to determine their first hyperpolarizablity (βHRS). For the first time, these HRS experiments are carried out in the picosecond regime in the deep NIR with very moderate (≤3 mW) average input power, providing a good signal-to-noise ratio and avoiding solvent thermal effects. Moreover, the frequency dispersion of βHRS is investigated for Disperse Red 1 (DR1), a dye commonly used as HRS external reference. On the other hand, these are compared with computational chemistry results obtained by using a sequential molecular dynamics (MD) then quantum mechanics (QM) approach. The MD method allows accounting for the dynamical nature of the molecular structures. Then, the QM part is based on TDDFT/M06-2X/6-311+G* calculations using solvation models ranging from continuum to discrete ones. Measurements report a decrease of the βHRS of di-8-ANEPPS in more polar solvents and these effects are reproduced by the different solvation models. For di-8-ANEPPS and DR1, comparisons show that the use of a hybrid solvation model, combining the description of the solvent molecules around the probe by point charges with a continuum model, already achieves quasi quantitative agreement with experiment. These results are further improved by using a polarizable embedding that includes the atomic polarizabilities in the solvent description.

3D-Printed Tumor-on-a-Chip Model for Investigating the Effect of Matrix Stiffness on Glioblastoma Tumor Invasion

Glioblastoma multiform (GBM) tumor progression has been recognized to be correlated with extracellular matrix (ECM) stiffness. Dynamic variation of tumor ECM is primarily regulated by a family of enzymes which induce remodeling and degradation. In this paper, we investigated the effect of matrix stiffness on the invasion pattern of human glioblastoma tumoroids. A 3D-printed tumor-on-a-chip platform was utilized to culture human glioblastoma tumoroids with the capability of evaluating the effect of stiffness on tumor progression. To induce variations in the stiffness of the collagen matrix, different concentrations of collagenase were added, thereby creating an inhomogeneous collagen concentration. To better understand the mechanisms involved in GBM invasion, an in silico hybrid mathematical model was used to predict the evolution of a tumor in an inhomogeneous environment, providing the ability to study multiple dynamic interacting variables. The model consists of a continuum reaction-diffusion model for the growth of tumoroids and a discrete model to capture the migration of single cells into the surrounding tissue. Results revealed that tumoroids exhibit two distinct patterns of invasion in response to the concentration of collagenase, namely ring-type and finger-type patterns. Moreover, higher concentrations of collagenase resulted in greater invasion lengths, confirming the strong dependency of tumor behavior on the stiffness of the surrounding matrix. The agreement between the experimental results and the model's predictions demonstrates the advantages of this approach in investigating the impact of various extracellular matrix characteristics on tumor growth and invasion.

Computational approaches to delivery of anticancer drugs with multidimensional nanomaterials

Functionalized nanotubes (NTs), nanosheets, nanorods, and porous organometallic scaffolds are potential in vivo carriers for cancer therapeutics. Precise delivery through these agents depends on factors like hydrophobicity, payload capacity, bulk/surface adsorption, orientation of molecules inside the host matrix, bonding, and nonbonding interactions. Herein, we summarize advances in simulation techniques, which are extremely valuable in initial geometry optimization and evaluation of the loading and unloading behavior of encapsulated drug molecules. Computational methods broadly involve the use of quantum and classical mechanics for studying the behavior of molecular properties. Combining theoretical processes with experimental techniques, such as X-ray crystallography, NMR spectroscopy, and bioassays, can provide a more comprehensive understanding of the structure and function of biological molecules. This integrated approach has led to numerous breakthroughs in drug discovery, enzyme design, and the study of complex biological processes. This short review provides an overview of results and challenges described from erstwhile investigations on the molecular interaction of anticancer drugs with nanocarriers of different aspect ratios.

Guiding Principles for the Rational Design of Hybrid Materials: Use of DFT Methodology for Evaluating Non-Covalent Interactions in a Uranyl Tetrahalide Model System

Together with the synthesis and experimental characterization of 14 hybrid materials containing [UO2 X4 ]2- (X=Cl- and Br- ) and organic cations, we report on novel methods for determining correlation trends in their formation enthalpy (ΔHf ) and observed vibrational signatures. ΔHf values were analyzed through isothermal acid calorimetry and a Density Functional Theory+Thermodynamics (DFT+T) approach with results showing good agreement between theory and experiment. Three factors (packing efficiency, cation protonation enthalpy, and hydrogen bonding energy [E H , norm total ${{E}_{H,{\rm { norm}}}^{{\rm { total}}}}$ ]) were assessed as descriptors for trends in ΔHf . Results demonstrated a strong correlation betweenE H , norm total ${E_{{\rm{H}},{\rm{norm}}}^{{\rm{total}}} }$ and ΔHf , highlighting the importance of hydrogen bonding networks in determining the relative stability of solid-state hybrid materials. Lastly, we investigate how hydrogen bonding networks affect the vibrational characteristics of uranyl solid-state materials using experimental Raman and IR spectroscopy and theoretical bond orders and find that hydrogen bonding can red-shift U≡O stretching modes. Overall, the tightly integrated experimental and theoretical studies presented here bridge the trends in macroscopic thermodynamic energies and spectroscopic features with molecular-level details of the geometry and electronic structure. This modeling framework forms a basis for exploring 3D hydrogen bonding as a tunable design feature in the pursuit of supramolecular materials by rational design.

Solv: An Alternative Continuum Model Implementation Based on Fixed Atomic Charges, Scaled Particle Theory, and the Atom-Atom Potential Method

An alternative continuum model implementation is reported. The electrostatic contribution to the solvation Gibbs free energy utilizes the noniterative conductor-like screening model of Vyboishchikov and Voityuk (DOI: 10.1002/jcc.26531) based on the fixed partial atomic charges. The nonelectrostatic solute-solvent dispersion-repulsion energy is calculated through the Caillet-Claverie atom-atom potential method employing the grid-based approach. The nonelectrostatic cavitation energy is computed within the scaled particle theory (SPT) formalism with the solute hard-sphere radius obtained via the Pierotti-Claverie (PC) scheme, from the solute molecular surface (SPT-S) or volume (SPT-V). The solvent hard-sphere radius is derived through the fitting to the experimental total solvation free energies of 2530 neutral species in 92 solvents. Application of the model to reproduce both the absolute and relative (reaction net) solvation free energies indicates that the SPT-V approach based on the CM5 charges is the best performer. The method is suggested for the solvation free energy calculation in the nonaqueous solvents.

Kinetics, mechanism, and tautomerism in ametryn acid hydrolysis: From molecular structure to environmental impacts

The excessive use of pesticides and the demand for environmentally friendly compounds have driven the focus to detailed studies of the environmental destination of these compounds. Degradation by hydrolysis of pesticides, when released into the soil, can result in the formation of metabolites with potentially adverse effects on the environment. Moving in this direction, we investigated the mechanism of acid hydrolysis of the herbicide ametryn (AMT) and predicted the toxicities of metabolites through experimental and theoretical approaches. The formation of ionized hydroxyatrazine (HA) occurs with the release of the SCH₃- group and the addition of H₃O⁺ to the triazine ring. The tautomerization reactions privileged the conversion of AMT into HA. Furthermore, the ionized HA is stabilized by an intramolecular reaction that provides the molecule in two tautomeric states. Experimentally, the hydrolysis of AMT was obtained under acidic conditions and at room temperature with HA as the main product. HA was isolated in a solid state through its crystallization as organic counterions. The mechanism of conversion of AMT to HA and the experimental investigation of the reaction kinetics allowed us to determine the dissociation of CH₃SH as the rate-controlling step in the degradation process that culminates in a half-life between 7 and 24 months under typical acid soil conditions of the Brazilian Midwest - region with strong agricultural and livestock vocation. The keto and hydroxy metabolites showed substantial thermodynamic stability and a decrease in toxicity compared to AMT. We hope that this comprehensive study will support the understanding of the degradation of s-triazine-based pesticides.

Investigation of substituent effect on O–C bond dissociation enthalpy of methoxy group in meta- and para-substituted anisoles

This paper is focused on the theoretical investigation of O-C Bond Dissociation Enthalpy (BDE) of methoxy OCH₃ group in 15 meta- and 15 para-substituted anisoles in gas phase, non-polar environment, and water. Density Functional Theory (DFT) calculations were carried out using M06-2X functional and 6-311++G(d,p) basis set. Obtained BDEs were correlated with Brown and Okamoto σ_p⁺ and Hammett σ_m constants representing commonly used descriptors of electron-donating or electron-withdrawing substituent effect. Obtained linear dependences allow the prediction of substituent effect on BDE using σ_p⁺ and σ_m constants. Calculated reaction enthalpies were also compared with available experimental and theoretical ab initio G4 values. Found results suggest that employed method may provide reliable thermochemistry data for demethylation of naturally occurring (poly)phenolic compounds, as well. In all studied environments, substituent induced changes in O-C BDE can be considered equal to those observed for the dissociation of phenolic O-H bond of substituted phenols.

Ab Initio Metadynamics Simulations of Hexafluoroisopropanol Solvent Effects: Synergistic Role of Solvent H-Bonding Networks and Solvent-Solute C-H/π Interactions

The solvent effects in Friedel-Crafts cycloalkylation of epoxides and Cope rearrangement of aldimines were investigated by using ab initio molecular dynamics simulations. Explicit molecular treatments were applied for both reactants and solvents. The reaction mechanisms were elucidated via free energy calculations based on metadynamics simulations. The results reveal that both reactions proceed in a concerted fashion. Key solvent-substrate interactions are identified from the structures of transition states with explicit solvent molecules. The remarkable promotion effect of hexafluoroisopropanol solvent is ascribed to the synergistic effect of H-bonding networks and C-H/π interactions with substrates.

Protonated Porphyrins: Bifunctional Catalysts for the Metal-Free Synthesis of N-Alkyl-Oxazolidinones

The protonation of commercially available porphyrin ligands yields a class of bifunctional catalysts able to promote the synthesis of N-alkyl oxazolidinones by CO₂ cycloaddition to corresponding aziridines. The catalytic system does not require the presence of any Lewis base or additive, and shows interesting features both in terms of cost effectiveness and eco-compatibility. The metal-free methodology is active even with a low catalytic loading of 1 % mol, and the chemical stability of the protonated porphyrin allowed it to be recycled three times without any decrease in performance. In addition, a DFT study was performed in order to suggest how a simple protonated porphyrin can mediate CO₂ cycloaddition to aziridines to yield oxazolidinones.

Understanding the Liquid States of Cyclic Hydrocarbons Containing N, O, and S Atoms via the 3D-RISM-KH Molecular Solvation Theory

The 3D-reference interaction site model (3D-RISM) molecular solvation theory in combination with the Kovalenko-Hirata (KH) closure is extended to seven heterocyclic liquids to understand their liquid states and to test the performance of the theory in solvation free energy (SFE) calculations of solutes in select solvents. The computed solvent site distribution profiles were compared with the all-atom molecular dynamics (MD) simulations, showing comparable performances. The computational results were compared against the structural parameters for liquids, whenever available, as well as against the experimental SFEs. The liquids are found to have local ordered structures held together via weak interactions in both the RISM and MD simulations. The 3D-RISM-KH computed SFEs are in good agreement with the benchmark values for the tetrahydrothiophene-S,S-dioxide, and showed comparatively larger deviations in the case of the SFEs in the tetrahydrofuran continuum.

Conformational energies of microsolvated Na+ clusters with protic and aprotic solvents from GFNn-xTB methods

Performance of contemporary tight-binding semiempirical GFNn-xTB methods for the conformational energies of singly charged sodium clusters Na⁺ (S)_n (n = 4-8) with 3 protic and 8 aprotic solvents is examined against the reference RI-MP2/CBS method. The median Pearson correlation coefficients of ρ = 0.84 (GFN2-xTB) and ρ = 0.82 (GFN1-xTB) do not give the clear preference to any tested approach. GFN1-xTB method demonstrates more stable performance than its GFN2-xTB successor with the average mean absolute errors (MAEs)/mean signed errors (MSEs) of 1.2/0.2 and 2.3/1.6 kcal mol^-1 , respectively. Conformational energies produced by the computationally efficient DFT functional PBE and double-ζ basis set complemented with -D3(BJ) dispersion correction are suitable for the preliminary sampling (median ρ = 0.93), but should be used with a caution for the calculations of the average ensemble properties (MAE/MSE = 1.7/1.1 kcal mol^-1 ). Higher-ranking PBE0-D3(BJ) and ωB97M-V with triple-ζ basis sets yield significantly lower MAEs/MSEs of 0.55/0.20 and 0.51/0.23 kcal mol^-1 , respectively.

Octanol-Water Partition Coefficients of Fluorinated Drug Molecules with Continuum Solvation Models

In this work, we have examined the efficiency of continuum solvation models, used with density functional theory methods, in calculating octanol-water partition coefficients (logP) of 56 fluorine containing drug molecules. The solvation model based on density model computed logP values that are in good agreement with the benchmark values. The conductor-like polarizable continuum models computed results have issues in predicting correct trend, often with reversal of sign from benchmark. The choice of basis set does not show significant effect, and the selection of atomic radii affects geometry convergence during calculations.

SN2 versus E2 reactions in a complex microsolvated environment: theoretical analysis of the equilibrium and activation steps of a nucleophilic fluorination

The reactivity of the fluoride ion towards alkyl halides is highly dependent on the solvating environment. In polar aprotic solvents with large counter-ions is highly reactive and produces substantial E2 product, whereas in polar protic solvents leads to slow kinetics and high selectivity for S_N2 reactions. The use of a more complex environment with stoichiometric addition of tert-butanol to acetonitrile solvent is able to module the reactivity and selectivity of tetrabutylammonium fluoride (TBAF). In the present work, we have performed a detailed theoretical analysis of this complex reaction system by density functional theory, continuum solvation model, and including explicit tert-butanol molecules. A kinetic model based on the free energy profile was also used to predict the reactivity and selectivity. The results indicated that the TBAF(tert-butanol) complex plays the key role to increase the S_N2 selectivity, whereas higher aggregates are not relevant. The E2 product is formed exclusively via free TBAF, because the solvating tert-butanol in the TBAF(tert-butanol) complex inhibits the E2 pathway. Our analysis suggests that diols or tetraols could produce an improved selectivity.

Automated Molecular Cluster Growing for Explicit Solvation by Efficient Force Field and Tight Binding Methods

An automated and broadly applicable workflow for the description of solvation effects in an explicit manner is introduced. This method, termed quantum cluster growth (QCG), is based on the semiempirical GFN2-xTB/GFN-FF methods, enabling efficient geometry optimizations and MD simulations. Fast structure generation is provided using the intermolecular force field xTB-IFF. Additionally, the approach uses an efficient implicit solvation model for the electrostatic embedding of the growing clusters. The novel QCG procedure presents a robust cluster generation tool for subsequent application of higher-level (e.g., DFT) methods to study solvation effects on molecular geometries explicitly or to average spectroscopic properties over cluster ensembles. Furthermore, the computation of the solvation free energy with a supermolecular approach can be carried out with QCG. The underlying growing process is physically motivated by computing the leading-order solute-solvent interactions first and can account for conformational and chemical changes due to solvation for low-energy barrier processes. The conformational space is explored with the NCI-MTD algorithm as implemented in the CREST program, using a combination of metadynamics and MD simulations. QCG with GFN2-xTB yields realistic solution geometries and reasonable solvation free energies for various systems without introducing many empirical parameters. Computed IR spectra of some solutes with QCG show a better match to the experimental data compared to well-established implicit solvation models.

Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system.

Solvation Free Energies in Subsystem Density Functional Theory

For many chemical processes the accurate description of solvent effects are vitally important. Here, we describe a hybrid ansatz for the explicit quantum mechanical description of solute-solvent and solvent-solvent interactions based on subsystem density functional theory and continuum solvation schemes. Since explicit solvent molecules may compromise the scalability of the model and transferability of the predicted solvent effect, we aim to retain both, for different solutes as well as for different solvents. The key for the transferability is the consistent subsystem decomposition of solute and solvent. The key for the scalability is the performance of subsystem DFT for increasing numbers of subsystems. We investigate molecular dynamics and stationary point sampling of solvent configurations and compare the resulting (Gibbs) free energies to experiment and theoretical methods. We can show that with our hybrid model reaction barriers and reaction energies are accurately reproduced compared to experimental data.

Computer Prediction of pK a Values in Small Molecules and Proteins

Accurately determining the acid dissociation constants (K _a or their logarithmic form, pK _a) of small molecules and large biomolecules has proven to be pivotal for the study different biological processes and developing new drugs. This Viewpoint summarizes some of the most common methodologies and recent advances described for pK _a prediction using computational techniques when experimental values are not easily accessible such as in proteins and/or for the screening of large libraries of new compounds.

Molecular Insights on Solvent Effects in Organic Reactions as Obtained through Computational Chemistry Tools

Molecular understanding of the role of protic solvents in a gamut of organic transformations can be developed using density functional and ab initio computational studies focused on the reaction mechanism. Inclusion of explicit solvent molecules in the vital TSs has been proven to be valuable toward improving the energetic estimates of organocatalytic as well as transition-metal-catalyzed organic reactions. Herein, we provide an overview of the importance of an explicit-implicit solvation model using a number of interesting examples.

Probing Interfacial Effects on Ionization Energies: The Surprising Banality of Anion-Water Hydrogen Bonding at the Air/Water Interface

Liquid microjet photoelectron spectroscopy is an increasingly common technique to measure vertical ionization energies (VIEs) of aqueous solutes, but the interpretation of these experiments is subject to questions regarding sensitivity to bulk versus interfacial solvation environments. We have computed aqueous-phase VIEs for a set of inorganic anions, using a combination of molecular dynamics simulations and electronic structure calculations, with results that are in excellent agreement with experiment regardless of whether the simulation data are restricted to ions at the air/water interface or to those in bulk aqueous solution. Although the computed VIEs are sensitive to ion-water hydrogen bonding, we find that the short-range solvation structure is sufficiently similar in both environments that it proves impossible to discriminate between the two on the basis of the VIE, a conclusion that has important implications for the interpretation of liquid-phase photoelectron spectroscopy. More generally, analysis of the simulation data suggests that the surface activity of soft anions is largely a second or third solvation shell effect, arising from disruption of water-water hydrogen bonds and not from significant changes in first-shell anion-water hydrogen bonding.

Theoretical Insights into Excited-State Intermolecular Proton Transfers of 2,7-Diazaindole in Water Using a Microsolvation Approach

The detailed excited-state intermolecular proton transfer (ESInterPT) mechanism of 2,7-diazaindole with water wires consisting of either one or two shells [2,7-DAI(H₂O)_n; n = 1-5] has been theoretically explored by time-dependent density functional theory using microsolvation with an implicit solvent model. On the basis of the excited-state potential energy surfaces along the proton transfer (PT) coordinates, among all 2,7-DAI(H₂O)_n, the multiple ESInterPT of 2,7-DAI(H₂O)₂₊₃ through the first hydration shell (inner circuit) is the most easy process to occur with the lowest PT barrier and a highly exothermic reaction. The lowest PT barrier resulted from the outer three waters pushing the inner circuit waters to be much closer to 2,7-DAI, leading to the enhanced intermolecular hydrogen-bonding strength of the inner two waters. Moreover, on-the-fly dynamic simulations show that the multiple ESInterPT mechanism of 2,7-DAI(H₂O)₂₊₃ is the triple PT in a stepwise mechanism with the highest PT probability. This solvation effect using microsolvation and dynamic simulation is a cost-effect approach to reveal the solvent-assisted multiple proton relay of chromophores based on excited-state proton transfer.

Mechanisms of a Cyclobutane-Fused Lactone Hydrolysis in Alkaline and Acidic Conditions

Searching for functional polyesters with stability and degradability is important due to their potential applications in biomedical supplies, biomass fuel, and environmental protection. Recently, a cyclobutane-fused lactone (CBL) polymer was experimentally found to have superior stability and controllable degradability through hydrolysis reactions after activation by mechanical force. In order to provide a theoretical basis for developing new functional degradable polyesters, in this work, we performed a detailed quantum chemical study of the alkaline and acidic hydrolysis of CBL using dispersion-corrected density functional theory (DFT-D3) and mixed implicit/explicit solvent models. Various possible hydrolysis mechanisms were found: B_AC2 and B_AL2 in the alkaline condition and A_AC2, A_AL2, and A_AL1 in the acidic condition. Our calculations indicated that CBL favors the B_AC2 and A_AC2 mechanisms in alkaline and acidic conditions, respectively. In addition, we found that incorporating explicit water solvent molecules is highly necessary because of their strong hydrogen-bonding with reactant/intermediate/product molecules.

Quantum Chemical Microsolvation by Automated Water Placement

We developed a quantitative approach to quantum chemical microsolvation. Key in our methodology is the automatic placement of individual solvent molecules based on the free energy solvation thermodynamics derived from molecular dynamics (MD) simulations and grid inhomogeneous solvation theory (GIST). This protocol enabled us to rigorously define the number, position, and orientation of individual solvent molecules and to determine their interaction with the solute based on physical quantities. The generated solute-solvent clusters served as an input for subsequent quantum chemical investigations. We showcased the applicability, scope, and limitations of this computational approach for a number of small molecules, including urea, 2-aminobenzothiazole, (+)-syn-benzotriborneol, benzoic acid, and helicene. Our results show excellent agreement with the available ab initio molecular dynamics data and experimental results.

Quantifying Uncertainties in Solvation Procedures for Modeling Aqueous Phase Reaction Mechanisms

Computational quantum chemistry 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 nontrivial 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), charge-asymmetric nonlocally determined local-electric (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 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 to renewable energy catalysis mechanisms. For this system, quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulations almost exactly reproduced energy profiles from 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 counterion. 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 lessens these errors. This work closes with recommended procedures for treating solvation in future computational efforts in studying renewable energy catalysis mechanisms.

Computational Methods in Heterogeneous Catalysis

The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. We finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.

Prediction of Solvation Free Energies of Ionic Solutes in Neutral Solvents

The prediction of solvation free energies is essential for a variety of applications. Solvation free energies of neutral systems can be predicted quite accurately. The accuracy of predictions for solvation free energies of ionic solutes dissolved in neutral solvents, however, has been reported to be worse by at least 1 order of magnitude. In this study, the performance of three approaches for solvation free energy prediction of several hundred ions dissolved in neutral solvents is evaluated. The applied methods are COSMO-RS, cluster continuum model (CCM) together with COSMO-RS, and COSMO-RS-ES. It is emphasized that the reference data for model evaluation are subject to large uncertainties stemming from the impossibility to measure the so-called elusive absolute free energies of solvation of a single ion. Consequently, such uncertainty must be considered during the evaluation of prediction methods. Therefore, a straightforward approach to account for the underlying uncertainty is applied here. Hereby, it is revealed that the true performance of the method is better than what is often reported. The average absolute deviation (AAD) of COSMO-RS is calculated to be 2.3 kcal mol^-1, while applying the CCM and COSMO-RS-ES each results in AADs of 2.0 kcal mol^-1. This accuracy allows for qualitative assessment of solvation free energy-dependent quantities, such as reaction rate constants.

Fast and accurate calculation of hydration energies of molecules and ions

An accurate and efficient method for calculation of hydration free energy of ions and neutral molecules is presented.

Accurate pKa Evaluations for Complex Bio-Organic Molecules in Aqueous Media

Despite the numerous computational efforts on estimating acid dissociation constant (pK_a's), an accurate estimation of pK_a's of bio-organic molecules in the aqueous medium is still a challenge. The major difficulty lies in the accurate description of the aqueous environment and the cost and accuracy of quantum mechanical (QM) methods. Herein, we report a well-defined quantum chemical protocol for accurately calculating pK_a's of a wide range of bio-organic molecules in aqueous media. The performance of our method has been assessed using test sets containing molecules with a range of sizes and a variety of functional groups, including alcohols, phenols, amines, and carboxylic acids, and obtained an impressive mean absolute accuracy of 0.5 pK_a units. For the smaller molecules, we use a high-level QM method (CBS-QB3) and a calibrated explicit-implicit solvation model that yields accurate pK_a values for a range of functional groups. For the larger molecules, we combine this approach with an efficient error-cancellation scheme that eliminates the systematic errors in different density functional methods to yield accurate pK_a values for simple to complex molecular systems. Our protocol is efficient, applicable to large molecules, covers all the common functional groups present in bio-organic molecules, and should find widespread applications in diverse research areas including drug-protein binding, catalysis, and chemical synthesis.