Quantum chemical studies of reactive species in water

In this thesis, quantum chemical methods have been applied to elucidate the thermodynamics and the kinetics of reactions involving reactive species in water. Due to their high reactivity in water, many transient species are difficult to study by experimental means only. Here, quantum chemical models are used to provide a deeper insight into the chemical nature and aqueous behaviors of such species. In the first chapter, I investigate the gas phase electronic structure and the thermodynamics of inorganic chloramines, bromamines, and bromochloramines, collectively termed halamines. The halamines are halogen oxidants that arise from reactions between ammonia and hypohalous acids during water disinfection processes, and these reactive species are implicated in the formation of disinfection byproducts that are harmful to human health. Despite their relevance in both drinking water chemistry and in biochemistry, the stabilities and speciation of these molecules are difficult to investigate by experimental means. To accurately predict the electronic structures and gas phase thermodynamic properties of halamines, I design a computational protocol, TA14, based on the high-quality Weizmann and Feller-Peterson-Dixon composite methods. TA14 combines a systematic sequence of wave function theory calculations, including the evaluations of dynamical and static electron correlation (CCSDTQ), core/valence electron correlation contributions, scalar and spin-orbit relativistic contributions, and VPT2 anharmonic vibrations. Using TA14, I successfully assess the gas phase total atomization energies, free enthalpies of formation, and Gibbs free energies of formation of halamines within uncertainty bounds of 1-3 kJ/mol. Analysis of the energy components contributing to total atomization energies of halamines reveals that N-Cl and N-Br bonds are held together mostly or entirely by electron correlation forces, with small or even negative Hartree Fock contributions. For example, the Hartree Fock component of the total atomization energy is negative for both NBr3 and NBr2Cl, implying that these molecules would be predicted as unstable without accounting for dynamical electron correlation. Reported thermochemical data enable the determination of equilibrium constants for reactions involving halamines, opening possibilities for more quantitative studies of the chemistry of these poorly understood compounds. In the second chapter, I evaluate the aqueous equilibria and speciation of halamines. I combine theoretical benchmark-quality gas phase Gibbs free energies of formation (chapter 2) with the computed Gibbs free energies of solvation, thereby obtaining aqueous phase Gibbs free energies of formation for halamines. The 'half-and-half' solvation approach, based on averaging the estimates of SMD implicit solvent model and the cluster-continuum solvent model, produces an average error of 3.3 kJ/mol in the free energies of solvation for a set of structurally related molecules containing H, N, O, and Cl. Taking into consideration the combined uncertainties of the computed gas free energy of formation values and the computed free energy of solvation values, we assign an uncertainty of 6-7 kJ/mol to the theoretical standard Gibbs free energies of formation in aqueous phase of halamines. Aqueous Gibbs free energies of formation values are key thermodynamic properties for investigating chemical processes involving halamines during drinking water treatment. The newly reported thermodynamic data can be used to determine the stabilities (reaction equilibria) of halamines in water. Based on our estimated uncertainties of 6-7 kJ/mol in the computed aqueous free energy of formation values of halamines, we expect roughly 1 order-of-magnitude uncertainty in the aqueous equilibrium constants for the reactions leading to the production of halamines in water. ...

Predicting aqueous speciation of environmentally relevant halogen oxidants: chloramines, bromamines, and bromochloramines

Jeremy Samuel Arey, Daniela Trogolo

Chloramines, bromamines, and bromochloramines are halogen-containing oxidants that arise from the reaction between ammonia and hypohalous acids during the disinfection of drinking and wastewaters. Although involved in the formation of toxic disinfection byproducts, these molecules are difficult to study by experimental means, and their speciation remains poorly defined. To bridge this gap, we successfully designed a benchmark level computational method, called TA14, adapted from the Weizmann theory and the Feller-Peterson-Dixon procedures, able to establish the thermodynamics of these species in gas phase. Our composite method combines a systematic sequence of wavefunction theory calculations (up to CCSDTQ), relativistic effects, diagonal Born-Oppenheimer corrections, and anharmonic vibrational modes. Free energies of aqueous solvation were modeled with the SMD implicit solvation model together with the cluster-continuum approach developed by Bryantsev in 2008. This combined solvation model allowed us to evaluate the effects of aqueous solvation on halamine formation and decomposition. These gas phase and solution phase thermodynamic data are used to predict aqueous equilibrium constants describing the formation reactions of chloramines, bromamines, and bromochloramines. Based on the comparisons with the available experimental data, we propose uncertainties ranging from 1 to 2 logarithm units for computed aqueous equilibrium constants. These newly reported estimates of reaction thermodynamics will enable us to assess the formation rate constants of these reactive halogenated species, leading to more accurate predictions of speciation of halamines during water treatment.

2015

Applications of Artificial Intelligence to Computational Chemistry

Nicholas John Browning

The calculation of the electronic structure of chemical systems, necessitates computationally expensive approximations to the time-independent electronic Schrödinger equation in order to yield static properties in good agreement with experimental results. These methods can also be coupled with molecular dynamics, to provide a first principles description of thermodynamic properties, dynamics and chemical reactions. Evidently, the cost of the underlying electronic structure method limits the time frame over which a system can be studied, and hence, certain chemical processes may be out-of-reach using a particular method. Furthermore, when one is interested in designing new molecules with interesting properties, a systematic enumeration of an inordinately large chemical space is typically required. The combination of both expensive electronic structure calculations and large chemical spaces results in an insurmountable barrier in computational cost. The application of artificial intelligence (AI) in computational chemistry has, over the past 20 years, seen an explosion in interest and scope with respect to these two issues. Intelligent algorithms capable of efficiently sampling chemical spaces, coupled with machine learning (ML) techniques to cheapen the calculation of electronic structure evaluations, enable both rapid throughput to search for new molecules with particular properties and in the case of ML, an increase in the timescales that can be simulated via molecular dynamics. In this thesis, computer programs have been developed that enable the application of AI algorithms to chemical and biological problems. In particular, a versatile evolutionary algorithm toolbox called EVOLVE has been developed. As a first test-case study, genetic algorithms were used to efficiently sample the vast chemical sequence space of an isolated ¿-helical peptide, from which insights are gained to rationalise the stability of particular genetically optimised peptides in a variety of implicit solvent environments. Genetic algorithms were then applied to the compositional optimisation of training sets used in machine learning models of molecular properties. The resulting optimal training sets are shown to significantly reduce out-of-sample errors on all thermodynamic and electronic properties considered. Furthermore, they reveal that there are systematic trends in the distribution of these optimally-representative molecules. Inspired by the success of machine learning, an ML-enhanced multiple time step approach for performing accurate ab initio molecular dynamics was developed. Two schemes representing different force partitioning were investigated. In the first scheme, the ML method provides an estimation of the slow (high level) force components acting on a system, while in the second, the ML forces are added to the fast (low level) components and a high level ab initio method is used to correct the error induced by the ML model. In both schemes significant overall speedups are obtained with respect to standard Velocity-Verlet integration, all-the-while maintaining the accuracy of the high level ab initio method.

EPFL2019

Computational Quantum Chemical Studies on Radicals

Peter Rudolf Tentscher

Radicals play an important role in many areas of chemistry, such as atmospheric, aquatic, polymer, and biological, to name a few. Radicals are often highly reactive species which are short-lived and therefore harder to study by experimental techniques. In principle, computational quantum chemistry enables the study of arbitrary chemical species, including elusive radicals. However, the approximate quantum chemical methods which are used for production simulations need to be validated for the type of problem in question. First, it is necessary to validate that highly accurate reference methods commonly applied to closed-shell systems are equally applicable to radicals. I show that the “gold standard” for closed-shell systems (coupled cluster with singles, doubles, and perturbative triples excitations (CCSD(T))) can produce molecular geometries and vibrational frequencies suitable for (sub-)kJ/mol thermochemistry for radical species as well. However, additional diagnosis is necessary, especially for vibrational frequency calculations. Coupled cluster methods are then used to compute benchmark binding energies between small radicals and water or hydrogen fluoride as a proxy to the aqueous condensed phase. I find that many common density functional theory (DFT) methods cannot reproduce these binding energies to within chemical accuracy (1 kcal/mol). However, some functionals, for example MPW1K and BHandHLYP, perform better than others. If more accurate ab initio methods are computationally too demanding for the system of interest, these DFT methods should be used for (micro-)solvated radicals. Complexes of radicals with polar solvent are found to be more strongly bound than expected. This can not be explained by dispersive and electrostatic interactions alone. Using natural bond orbitals, I show that additional donor-acceptor interactions may be responsible for the strong intermolecular binding observed. One of the most fundamental processes involving aqueous organic radicals is the one-electron oxidation of closed-shell organics. I study the vertical ionization of neutral organics. That is, the ionization is faster than the reorganization of the solvent (and solute), and the conformation is assumed to be unchanged during the ionization process. I find that the difference between the gas-phase and aqueous-phase vertical ionization energy, ∆VIE = VIEaq − VIEgas, ranges from ≈ 0 to -1.0 eV for small aromatic compounds. The differences in ∆VIE between different compounds seem to be caused by the solvent structures of the ≈ 70 water molecules closest to the solute. In natural surface waters, oxidized organics arise through the reaction of photochemically created radicals with organic molecules already present in the water column. One example for such a reaction is the oxidation of sulfonamide antibiotics. I show that upon oxidation of sulfadiazine and related compounds, an aniline radical cation is formed. The reactivity of this oxidized species is strikingly different from its reduced counterpart: the barrier for a nucleophilic attack on the aniline ring is drastically lowered, and a fast rearrangement reaction can take place. I demonstrate that current quantum chemical protocols are suitable for mechanistic studies of solvated radicals, and I successfully apply them to such problems. To achieve chemical accuracy for quantum computational protocols, further developments are necessary. To validate novel approaches, the benchmark data presented in this thesis may be used.