Structure and dynamics in solutions – the core electron perspective

Ida Josefsson c Ida Josefsson, Stockholm University 2015

ISBN 978-91-7649-258-1

Printed in Sweden by Holmbergs, Malmö 2015 Distributor: Department of Physics, Stockholm University List of Papers

The following papers, referred to in the text by their Roman numerals, are included in this thesis.

− − PAPER I: Solvent Dependence of the Electronic Structure of I and I3 Susanna K. Eriksson, Ida Josefsson, Niklas Ottosson, Gunnar Öhrwall, Olle Björneholm, Hans Siegbahn, Anders Hagfeldt, Michael Odelius, and Håkan Rensmo, The Journal of Physical Chemistry B, 118, 3164–3174 (2014). DOI: 10.1021/jp500533n

PAPER II: Collective hydrogen-bond dynamics dictates the electronic − structure of aqueous I3 Ida Josefsson, Susanna K. Eriksson, Niklas Ottosson, Gunnar Öhrwall, Hans Siegbahn, Anders Hagfeldt, Håkan Rensmo, Olle Björneholm, and Michael Odelius, Physical Chemistry Chemi- cal Physics, 15, 20189–20196 (2013). DOI: 10.1039/c3cp52866a

− PAPER III: Solvent-Dependent Structure of the I3 Ion Derived from Pho- toelectron Spectroscopy and Ab Initio Molecular Dynamics Simulations Naresh K. Jena, Ida Josefsson, Susanna K. Eriksson, Anders Hagfeldt, Hans Siegbahn, Olle Björneholm, Håkan Rensmo, and Michael Odelius. Chemistry – A European Journal, 21, 4049–4055 (2015). DOI: 10.1002/chem.201405549

PAPER IV: Solvation Structure Around Ruthenium(II) Tris(bipyridine) in Lithium Halide Solutions Ida Josefsson, Susanna K. Eriksson, Håkan Rensmo, and Michael Odelius. In manuscript. PAPER V: Ab Initio Calculations of X-ray Spectra: Atomic Multiplet and Molecular Orbital Effects in a Multiconfigurational SCF Approach to the L-Edge Spectra of Transition Metal Com- plexes Ida Josefsson, Kristjan Kunnus, Simon Schreck, Alexander Föh- lisch, Frank de Groot, Philippe Wernet, and Michael Odelius, The Journal of Physical Chemistry Letters, 3, 3565–3570 (2012). DOI: 10.1021/jz301479j

PAPER VI: From Ligand Fields to Molecular Orbitals: Probing the Lo- cal Valence Electronic Structure of Ni2+ in Aqueous Solu- tion with Resonant Inelastic X-ray Scattering Kristjan Kunnus, Ida Josefsson, Simon Schreck, Wilson Quevedo, Piter S. Miedema, Simone Techert, Frank M. F. de Groot, Michael Odelius, Philippe Wernet, and Alexander Föhlisch, The Journal of Physical Chemistry B, 117, 16512–16521 (2013). DOI: 10.1021/jp4100813

PAPER VII: Orbital-specific mapping of the ligand exchange dynamics of Fe(CO)5 in solution. Philippe Wernet, Kristjan Kunnus, Ida Josefsson, Ivan Rajkovic, Wilson Quevedo, Martin Beye, Simon Schreck, Sebastian Grü- bel, Mirko Scholz, Dennis Nordlund, Wenkai Zhang, Robert W. Hartsock, William F. Schlotter, Joshua J. Turner, Brian Kennedy, Franz Hennies, Frank M. F. de Groot, Kelly J. Gaffney, Simone Techert, Michael Odelius, and Alexander Föhlisch. Nature, 520, 78–81 (2015). DOI: 10.1038/nature14296

PAPER VIII: Mechanistic insight into the ultrafast ligand addition and spin crossover reactions following Fe(CO)5 photodissocia- tion in ethanol. Kristjan Kunnus, Ida Josefsson, Ivan Rajkovic, Simon Schreck, Wilson Quevedo, Martin Beye, Christian Weniger, Sebastian Grübel, Mirko Scholz, Dennis Nordlund, Wenkai Zhang, Robert W. Hartsock, Kelly J. Gaffney, William F. Schlotter, Joshua J. Turner, Brian Kennedy, Franz Hennies, Frank M. F. de Groot, Simone Techert, Michael Odelius, Philippe Wernet, and Alexan- der Föhlisch. Submitted to Structural Dynamics.

Reprints were made with permission from the publishers. Comments on my own contribution

Paper I: I participated in designing the study, carried out all the calculations and part of the analysis, and wrote parts of the manuscript.

Paper II: I participated in designing the study, performed the spectrum calcu- lations, wrote the program for geometry sampling, and had the main responsi- bility for the manuscript.

Paper III: I participated in formulating the problem, performed calibrating cal- culations, and participated in writing the manuscript.

Paper IV: I participated in designing the study, had the main responsibility for the calculations, analysis, and writing of the manuscript.

Paper V and VI: I participated in the development of the computational scheme, carried out part of the calculations and analysis, and wrote parts of the manuscript for Paper V.

Paper VII and VIII: I performed the bulk of the calculations for the spectrum simulations and energetics and participated in the analysis and writing of the manuscript.

Paper I, II, and V were included in my licentiate thesis [1] and parts of the background and results in this thesis were described there also.

Contents

List of Papers iii

Comments on my own contribution v

Abbreviations ix

1 Introduction 11 1.1 Energy from the sun ...... 11 1.2 Core-level spectroscopy ...... 13 1.3 Calculations of core-level spectra ...... 14 1.4 Aim of this thesis ...... 14

2 Computational framework 17 2.1 The Born–Oppenheimer approximation ...... 17 2.2 Electronic structure methods ...... 18 2.2.1 Solving the electronic Schrödinger equation ...... 19 2.2.2 Molecular orbitals and the basis set approximation . . 20 2.2.3 Electron correlation ...... 21 2.3 Multiconfigurational theory ...... 22 2.3.1 Perturbation theory ...... 24 2.4 Relativistic effects ...... 25 2.5 Simulations of solutions ...... 26 2.5.1 Molecular dynamics ...... 27 2.5.2 Solvation models ...... 29

3 Concepts in spectroscopy 31 3.1 Core and valence electronic levels ...... 31 3.2 Photoelectron spectroscopy ...... 32 3.2.1 Chemical shifts in core-level spectra ...... 34 3.2.2 Satellites in photoelectron spectra ...... 35 3.3 X-ray absorption spectroscopy ...... 35 3.4 Core hole decay ...... 35 3.5 Peak intensities and spectral line shape ...... 36 3.5.1 Linewidths and shapes of x-ray spectra ...... 36 3.6 Resonant inelastic x-ray scattering ...... 37 3.6.1 Transition probabilities for second order processes . . 38 3.7 Time-resolved spectroscopy ...... 38

4 Summary of results 41 − − 4.1 Solvation and electronic structure of I and I3 ...... 41 4.1.1 Solvent-induced binding energy shifts of I− ...... 42 − 4.1.2 Geometry of I3 in solution ...... 43 2+ 4.2 [Ru(bpy)3] in lithium halide solution ...... 47 4.3 Electronic structure of transition metal complexes ...... 51 4.3.1 Ni2+ in aqueous solution ...... 53 4.4 Probing changes in the electronic structure of transition metal complexes ...... 56

5 Conclusions 61

Populärvetenskaplig sammanfattning lxv

Acknowledgements lxvii

References lxix Abbreviations

AO Atomic orbital CASPT2 Second-order perturbation theory with CASSCF reference function CASSCF Complete active space self-consistent field CI Configuration interaction DFT Density functional theory HF Hartree–Fock HOMO Highest occupied molecular orbital LF Ligand field LMCT Ligand-to-metal charge transfer LUMO Lowest unoccupied molecular orbital MD Molecular dynamics MLCT Metal-to-ligand charge transfer MO Molecular orbital NEXAFS Near-edge x-ray absorption fine structure PCM Polarizable continuum model PES Photoelectron spectroscopy RAS Restricted active space RDF Radial distribution function RIXS Resonant inelastic x-ray scattering SCF Self-consistent field SDF Spatial distribution function SIBES Solvent-induced binding energy shift UV–Vis Ultraviolet–visible XAS X-ray absorption spectroscopy XPS X-ray photoelectron spectroscopy

1. Introduction

Much effort is spent on the development of clean and inexpensive applications for energy production. Theoretical calculations give the possibility to describe the systems and processes in very fine details and fill an important function for the fundamental understanding of the systems. In this thesis, computational methods are used to study the electronic and solvent structure of model sys- tems, and give insight in the molecular details, which can be of relevance for energy applications.

1.1 Energy from the sun

Our society today is entirely dependent on easily accessible energy. Fossil fuels still provide over 80 percent of the energy consumed in the world [2]. The problems associated with this are the substantial impact of the fossil fuels on the environment and the fact that the resources are finite. In order to cover the growing world energy consumption, it is desirable to understand and develop renewable energy sources as a supplement and eventually replacement. The sunlight reaching the Earth’s surface in one hour is more than the world’s entire need for energy over the next year [3], but despite its abundancy, solar energy accounts only for a small fraction of the world energy supply [2]. A chemical system used for solar energy conversion must absorb sunlight irradiating it, and convert the electromagnetic radiation to an energy form that can be used to perform some kind of work. Solar radiation reaching the Earth’s surface has its strongest output range in the visible light region of the electro- magnetic spectrum. At these wavelengths, light interacts the most strongly with the outer shell electrons, called valence electrons, in matter. Sunlight in- teracting with the system changes the valence electronic structure by exciting the absorbing molecule to a higher energy state. When the excited state re- laxes to a lower energy state, reactions important for the energy conversion process can take place. Knowledge of the fundamental chemical processes are essential for the understanding of photochemical applications. Many of these processes take place in electrolyte solutions. Photoelectrochemical systems have been studied as highly interesting ap- plications for solar energy conversion and storage for more than 40 years [4– 12 complexes ruthenium primarily dyes, based Metal found. are complexes metal reactions. chemical catalyze to used be elec- can dye an that molecule a species creates absorbing reactive which the excites a of electron, sunlight generates excitation an reactions, off of photocatalytic gives In absorption it current. which cell, trical from solar state molecular a to the en- molecule In chemical and into 9] energy [8; [10]. solar energy ergy of electrical conversion into for energy splitting solar water of photocatalytic conversion for cells solar ular semiconductor. the in electrons the of h aiu htvlaeta a egnrtdi eemndb h redox cell. the the by in determined is current generated M or be potential potential can electrode that photovoltage in maximum 1.1. change The Figure a pho- in effect of shown processes type are one These conversion in energy processes for light-induced transport application The a toelectrochemical solution. electrochem- as the via acting in mediated reactions are solvent charges ical a finally, and, with carriers contact charge electrolyte-based for in an medium In are photoproducts separated. are the charges device, transfer the electron state photoex- through photoexcited the and the In created, a from is surface. be pair semiconductor may electron–hole a an absorber to process, attached The citation molecule, dye wavelength. a appropriate or of solid, sunlight cell photoelectrochemical of the absorption the in and process is conversion system energy the the irradiating of light step by primary induced is reaction photochemical A 7]. otenurlgon tt yacpiga lcrnfo neeto donating electron an arrow). from (blue electron interface solution an the accepting at by M S band species state conduction ground S the molecule neutral into oxidized the The injected to arrow). is (green electron semiconductor a an of state, CB S excited to the S From state arrow). ground the cell. from photoelectrochemical cited a in Processes 1.1: Figure

ttecr fmn fslreeg ovrinapiain,transition applications, conversion energy solar of many of core the At molec- are context this in research energy-related for subjects important Two Free energy + Mo h eo opei h lcrlt n h em ee E level Fermi the and electrolyte the in couple redox the of /M E CB/CB F − ∗ yasrto flgtwt energy with light of absorption by hν S S ∗ + /S /S + oeuei photoex- is molecule A + M + srdcdback reduced is /M h ν (red F with bipyridine ligands, have been used for absorbing sunlight in molecular solar cells since the early 90s, in combination with the iodide/triiodide redox couple for regeneration of the oxidized dye [11; 12]. Electrolytes with transi- tion metal complexes have also been reported as promising alternatives to the iodide/triiodide redox mediator [13]. In photoelectrochemical water splitting cells, solvated complexes with metal centers such as ruthenium, cobalt, or iron can be used as photocatalysts for hydrogen production [14–16]. In order to design complexes for efficient energy conversion applications, we need a fundamental understanding of the electronic and molecular structure of the materials involved in the energy conversion processes. Solute–solvent interactions in the electrolyte influence the energy conversion processes, and studies of the structure and dynamics in solution can give insight in the role of the solvent and other ions present in the solution. This can then be used for choosing a solvent and electrolyte composition that gives optimal performance and stability of energy applications. In short, understanding of transition metal complexes and solvent interactions in electrolytes is essential for developing photoelectrochemical systems. An ultimate goal is to reach such understand- ing and to be able to manipulate the system at a fine, atomic, level. In principle, theoretical calculations are able to provide the answers, but it is necessary to validate the theoretical models against experimental measurements. For this purpose, the results obtained using spectroscopic techniques for characteriza- tion of the material can be compared with theoretical spectra. The full system and its complex processes are difficult to model, but simulations of prototype systems give important information of interactions in solution.

1.2 Core-level spectroscopy

Every element in the periodic table has a set of characteristic binding energies of its electrons. For the inner shell, or core, electrons, these are well separated and centered around the atomic nuclei, but in a compound consisting of several atoms, the valence electrons, forming bonds, are delocalized over the molecule and have close-lying energies. By letting radiation from a light source with much shorter wavelengths than visible light illuminate a material and interact with the inner shell elec- trons, the material can be characterized with atomic selectivity. In spectroscopy, the excited state energies, and the probability of creating them at a specific pho- ton energy, is measured to give a fingerprint of the atoms present in the sample. Techniques using short-wavelength radiation to create excited states by inter- action with the inner-shell electrons are referred to as core-level spectroscopy, and can be used to study the chemical state, bonding and local structure around a specific atomic site. The spectroscopic techniques can be classified accord-

13 ing to what is measured in the experiment. Photoelectron spectroscopy uses x-ray photons with a fixed energy to release electrons from the material. The intensity of the emitted electrons is measured as a function of their kinetic en- ergy. In x-ray absorption spectroscopy, the x-ray energy is scanned instead of being kept fixed, and the intensity of absorbed x-rays is measured.

1.3 Calculations of core-level spectra

Recent years’ development of new light sources has made it possible to pro- duce experimental spectra that are resolved into very fine details containing information on the electronic and molecular structure and that call for high- level theoretical methods for their interpretation. Hence, there is a need to establish accurate theoretical approaches for spectrum simulations, with suf- ficiently realistic models of the systems studied. The computational method must describe both the initial state of the system and states resulting from in- teraction with the light of a specific wavelength irradiating the sample, as well as the spectroscopic process, accurately. X-ray spectroscopy poses its partic- ular challenges, as the x-rays can interact with the core electrons close to the atomic nucleus, which are subject to relativistic effects that have to be included in the theoretical description, to reproduce the experimental spectra. When the time evolution of a system is studied, it is crucial that the the- oretical method is suitable for modeling light–matter interactions even during processes where bond lengths and angles change and large charge redistribu- tions occur. Bonds in a molecule may break and reform, and the short-lived spectra are obtained only from an accurate description of both the initial and photoexcited states of such geometrically distorted molecular structures. It is therefore desirable that the method does not rely on empirical or fitting param- eters obtained under certain conditions, but that the interactions influencing the spectrum are included from first principles.

1.4 Aim of this thesis

The long-term aim of this thesis is to create insight in how solvent and ion composition affect light-driven processes in energy conversion devices based on liquid electrolytes. In order to gain a detailed understanding of the work- ing components, the specific goal has been to characterize model systems of general relevance for energy applications on a fundamental molecular level. The primary characterization tools used in this work are high level quantum chemistry and molecular dynamics simulations, employed for the purpose of interpreting core-level spectra: photoelectron spectroscopy and x-ray absorp-

14 tion/resonant scattering, methods that are both atom specific and sensitive to the chemical environment. This thesis focuses especially on accurate calculations of core level elec- tronic spectra, including relativistic effects, of transition metal compounds and iodine systems in solutions, but also on the solution molecular structure and dynamics. For the description of the structure of the solution and its time- dependent behavior, we have used molecular dynamics simulations, which include configurational sampling, needed for liquids and disordered systems. The electronic structure methods used in the spectrum calculations were orig- inally developed for valence excited states and are known to yield accurate results. They are however also capable of addressing x-ray induced core level excitations, and a strong collaboration between theory and experiment has been fundamental for verifying the reliability of the computed spectra.

15 16 2. Computational framework

In order to describe a chemical system, either an isolated atom or molecule, or many interacting molecules, the mathematical form for the forces acting between the particles, as well as the form for the time evolution, must be de- fined. If the differential equations describing the system could be solved, all its chemical properties and processes would be known. The fundamental interaction controlling the properties of a molecule in its chemical environment is the Coulomb interaction between the charged parti- cles constituting the system: nuclei and electrons. The form for the equations of motion depends on the particles’ mass and velocity: for heavy particles moving at slow speed, Newton’s equations apply, but for light particles, quan- tum mechanics is needed. At high velocities, relativistic effects become im- portant. The application of quantum mechanics onto a chemical problem is known as quantum chemistry. It is however impossible to separate the degrees of free- dom for the internal motion of more than two interacting particles and solve the equations exactly. For any chemical system larger than the hydrogen atom, the scientist must resort to numerical solutions, which at best can be refined to the desired degree of accuracy. The choice of basic particles in the system is a tradeoff between the level at which its properties can be obtained and what is computationally feasible. Atoms and molecules can essentially be described with classical mechanics, but the details of the electronic distribution are not captured. The wave-like nature of the much lighter electrons can only be de- scribed with quantum mechanics, which is computationally more demanding, and consequently limited to smaller systems.

2.1 The Born–Oppenheimer approximation

Although the variables in the equations of motion are not exactly separable, an approximate separation of variables is often possible through physical proper- ties. Due to the large difference in nuclear and electronic masses, their motion can usually be considered to occur on different timescales. In spectroscopy, the consequence of the mass difference between electrons and nuclei is that elec- tronic and nuclear energies are measured in different regions of the electromag-

17 netic spectrum: Typical spacings between electronic energies are in the x-ray to ultraviolet energy range, while vibrational energies, associated with nuclear motion, are usually separated by energies in the infrared region. Molecular rotational energies lie even closer, with separations in the microwave range. The Hamiltonian operator H, representing the energy of a molecule, is a sum of kinetic and potential energy operators, describing the kinetic energy of all the particles in the system and the electrostatic interaction between them:

H = Te + TN + VeN + Vee + VNN, (2.1) where Te and TN are the kinetic energy operators for the electrons and nuclei respectively, VeN contains the electrostatic attraction between electrons and nuclei, Vee the electrostatic repulsion between electrons, and VNN the elec- trostatic repulsion between the nuclei. The only term which contains both the electronic and nuclear coordinates, and thus prevents the exact separation of the molecular Hamiltonian into electronic and nuclear contributions, is the electron–nuclear potential energy operator VeN. The Born–Oppenheimer ap- proximation [17] uses the assumption that electronic and nuclear motion can be separated to form an approximate Hamiltonian that acts solely on the elec- tronic positions for a fixed nuclear geometry, so that TN = 0:

Hel = Te + VeN + Vee + VNN. (2.2)

The role of the stationary nuclei is to generate an electrostatic potential in which the electrons move. By varying the nuclear coordinates in Equation 2.2, a so called electronic potential energy surface is obtained. The optimal geom- etry of a molecule is found at the minimum of the potential energy surface.

2.2 Electronic structure methods

The wavefunction describing a system is found by solving the time-dependent Schrödinger equation [18]:

d H|Ψi = ih¯ |Ψi. (2.3) dt The Schrödinger equation is the fundamental equation in quantum mechan- ics and describes how the state |Ψ(t)i changes in time, through the Hamilto- nian operator H, given in Equation 2.1. Often, physical properties that remain constant over time are treated. They are described by the time-independent Schrödinger equation: H|ψi = E|ψi, (2.4)

18 where ψ are eigenstates of the Hamiltonian. The total energy of the system in a particular state is given by the corresponding eigenvalue E. Based on the Born–Oppenheimer approximation, the total wavefunction Ψ of the system can be factorized into a wavefunction ψ(r;R), associated with the electronic motion, and a wavefunction ξ(R), describing the motion of the nuclei: Ψ(r,R) = ψ(r;R)ξ(R), (2.5) where r is the collection of all the electronic positions and R the nuclear posi- tions. In the electronic wavefunction and the corresponding energy eigenval- ues, the positions of the nuclei enter as a parameter rather than a variable. This is equivalent to the assumption that the very light electrons move in a fixed nuclear framework. The electronic wavefunction and corresponding energy are found by solving the electronic Schrödinger equation using the electronic Hamiltonian in Equation 2.2 for fixed nuclear coordinates R. The electronic potential energy surface determines the nuclear motion, and solving the nu- clear wavefunction on the electronic surface yields a set of rotational and vi- brational levels. Methods intended for solving the electronic Schrödinger equation are re- ferred to as electronic structure methods. Ab initio methods introduce no em- pirical or fitting parameters in the calculations, but are based entirely on first principles. Their advantage is their generality, but they often come with a large need for computational power.

2.2.1 Solving the electronic Schrödinger equation Two of the terms in the electronic Hamiltonian, namely the kinetic energy operator and the electron–nucleus attraction, act on one electron at a time. The electron–electron repulsion operator, however, contains the positions of pairs of electrons. The complex interactions of a many-electron system can be simplified into single-particle problems through the independent particle model, assuming that each electron moves in the average field of the other electrons. In the independent particle model, the Schrödinger equation for the N-electron system reduces to N uncoupled one-electron equations. The one- electron wavefunctions satisfying the equations are called spin orbitals χi and the corresponding eigenvalues εi are the orbital energies. The spin orbital is a function of the electronic spatial and spin coordinates χi = χi(xa,ya,za,ωa) = χi(xa). Since electrons are fermions, the total wave- function must change sign upon interchange of any two electronic coordinates. In the Hartree–Fock (HF) method [19; 20], the antisymmetry criterion is met by expressing the wavefunction for the N-electron system is as a Slater de- terminant [21], which is an antisymmetrized product of N one-electron spin

19 orbitals χi(xa):

χ1(1) χ2(1) ... χN(1)

1 χ1(2) χ2(2) ... χN(2) = √ , (2.6) ψ . . .. . N . . . .

χ1(N) χ2(N) ... χN(N) with the electron coordinates in rows and orbitals in columns. In order to de- scribe the stationary states of the system as Slater determinants, the energy is required to be stationary with respect to variation of the spin orbitals. Accord- ing to the variational principle, the determinant giving the lowest energy is the solution closest to the exact wavefunction of the ground state. In other words, the spin orbitals should be chosen such that they minimize the expectation value of the Hamiltonian. If a spin-free Hamiltonian is used, the total energy is determined by the spatial functions and the explicit reference to the spin function in the orbitals can be omitted. The role of the spin is only to give the wavefunction the correct permutation symmetry. [22] From now on, I am going to refer to the spatial part of the orbitals as molecular orbitals (MOs), each holding at most two electrons with opposite spins. The MOs for the spin-free Hamiltonian are found by solving the eigenvalue problem for the effective one-electron Fock operator

N fi = hi + ∑(j j − k j), (2.7) j where the one-electron operator hi describes the electrons’ kinetic energy and the electron–nuclei potential energy. The electron–electron repulsion is con- tained in the two-electron j j and k j operators: The Coulomb operator j j gives the electrostatic interaction of an electron in orbital φi with the average charge distribution from the others, while the exchange operator k j is a purely non- classical term—it arises from the antisymmetry conditions and prevents elec- trons with parallel spins from occupying the same position in space. Since the Coulomb and exchange terms in the Fock operator depend on all the occupied orbitals, the equations are solved iteratively, starting from an ini- tial set of N orbitals that are stepwise corrected. A solution where the orbitals found construct a Fock operator for which these orbitals are the eigenfunc- tions is called self-consistent. The HF method is sometimes referred to as the self-consistent field (SCF) method.

2.2.2 Molecular orbitals and the basis set approximation In most calculations, the unknown MOs are expanded in a finite basis set of known functions. A set of functions ϕα localized at the nuclei is often chosen

20 as a basis, and each MO is expressed as a linear combination of these atomic orbitals (AOs) M φi = ∑ cαiϕα , (2.8) α=1 where M is the number of basis functions, combined into M MOs. Not all basis sets are localized on the nuclei, however. In principle, any type of function ϕα can be used; another common type of basis set has plane waves as basis functions. The unknown coefficients cαi are calculated iteratively in the SCF procedure. The ground state wavefunction is optimized for the N occupied orbitals, with the lowest orbital energies, included in the Slater determinant. The remaining M − N MOs are referred to as virtual orbitals. The frontier orbitals, the highest occupied (HOMO) and lowest unoccu- pied (LUMO) molecular orbitals, are the most likely to be involved in and change in chemical reactions. For that reason, they are particularly interesting in photochemical studies.

2.2.3 Electron correlation

The single-determinant description of the wavefunction in the HF method lacks the flexibility to account for explicit electron–electron interactions other than that of same-spin electrons, captured in the exchange term. The devia- tion of the HF energy with respect to the exact energy defines the correlation energy [23]. Physically it means that the electrons are on average too close to each other. The correlation effects are often divided into short-range dynamic and long-range static electron correlation, although the distinction is not abso- lute. In contrast to wavefunction based methods like HF, density functional the- ory (DFT) uses the electron density as the fundamental property. According to the Hohenberg–Kohn theorems [24], the ground state properties are uniquely determined by the electron density ρ, which is a function of the three spa- tial coordinates. The energy is a so called functional, a function of another function, and contains a term for the kinetic energy of the non-interacting electrons, the nuclear–nuclear and nuclear–electron potential energies, and the electron–electron repulsion, similar to the HF energy. In addition, the DFT formulation of the electronic energy functional contains a contribution, the exchange–correlation energy, which effectively adds a correction for explicit electron–electron interactions that HF lacks. The calculations are often done in the Kohn–Sham formulation [25], with equations similar to HF. Since the exact exchange–correlation functional is not known, various approximations are used, with the result that a whole range of functionals is available. In this

21 thesis, DFT was used for calculating forces in the ab initio molecular dynamics simulations described in Section 2.5.1. Correlation effects causing a large separation between electrons in a pair, such as when electrons in a dissociating bond localize on different atoms, are important when several electronic configurations become nearly degenerate, i.e. are associated with the same energy. In such cases, a wavefunction built up by several determinants is needed to give a qualitatively correct description of the electronic structure. This mixing of electronic configurations is impor- tant in transition metal compounds, where many electronic levels often have similar energies and there are strong overlaps between metal and ligand va- lence orbitals. Excited states, also, require a multi-determinant description of the wavefunction. Any exact N-electron wavefunction can be expanded in an infinite number of determinants: ∞ Ψ = a0ΦHF + ∑aSΦS + ∑aDΦD + ... + ∑aNΦN = ∑ akΦk, (2.9) S D N k=0 where all possible ways of arranging the electrons in the orbitals that are empty in the HF wavefunction are included as singly (S), doubly (D), etc. excited configurations. Provided that the basis set is complete, the solution is exact. Consequently, a better approximation of the wavefunction Ψ can be formed by adding excited configurations to the HF determinant ΦHF in Equation 2.6. The configuration interaction method (CI) [26] uses a set of orthonormal MOs that are first obtained from a HF calculation and optimizes the weight ak of each determinant to an energy minimum, keeping the orbitals fixed. To reduce the computational cost, the series of determinants is usually truncated to contain excitations up to a given level (S, D, etc.). The number of solutions is equal to the number of coefficients solved for. In addition to the ground state wave- function and energy, an excited state solution for every excited configuration is hence obtained in the CI.

2.3 Multiconfigurational theory

In some cases, static correlation effects strongly affect the electron density of a molecule, influencing for example the polarity in a chemical bond. This modifies the MOs involved, so that a predetermined set of orbitals may not describe the wavefunction sufficiently well. The complete active space SCF (CASSCF) method [27] was developed for taking the most important determi- nats into account. It optimizes not only the coefficients ak for the determinants in Equation 2.9, but also the basis functions coefficients cαi in Equation 2.8 for the set of MOs building up the determinants.

22 The complete space of MOs is divided into three subspaces: inactive or- bitals that are all doubly occupied, active orbitals, and secondary orbitals that are all empty. A full CI wavefunction is generated within the active space by letting all possible configurations that can be obtained from electron per- mutations consistent with the number of electrons and spin multiplicity in the active orbitals contribute to the wavefunction. At the same time, the orbital co- efficients are optimized via all possible rotations between the inactive–active, active–virtual, and inactive–virtual orbitals. The number of determinants grows rapidly with the number of active or- bitals included, which makes CASSCF a computationally challenging method. Particularly difficult is the case when the number of electrons in the active space is close to the number of active orbitals, since the number of ways to arrange the active electrons is maximal. To reduce the computational cost, the restricted active space (RAS) SCF method [28] partitions the active space into subspaces with certain restrictions on the occupation numbers, and thus limits the number of excited configurations included. The electronic structure calcu- lations described in Paper I–III and V–VI are multiconfigurational calculations, performed with the Molcas-7 software package [29]. The RAS orbitals in a calculation of the ground state, valence-excited 2+ states, and core-excited states of the [Ni(H2O)6] complex are shown in Fig- ure 2.1. The first subspace, RAS1, is selected to comprise the three Ni 2p core orbitals. The RAS1 orbitals would be doubly occupied in the HF, but in this particular RASSCF calculation, one hole is allowed. RAS2 consists of the or- bitals of nominal Ni 3d character with no restrictions on the occupation. The remaining occupied orbitals are left inactive. The inactive orbital coefficients are optimized in the CASSCF procedure, but excitations from inactive orbitals are not allowed. The possible excitations can be separated into two types: (1) configurations with one hole in RAS1, and an “extra” electron in RAS2 and (2) configura- tions with RAS1 fully occupied. The first case corresponds to core excitations 2p→3d (with a single core hole), and the second case includes all valence exci- tations corresponding to pure d-d transitions. The dominant configuration for the ground state is the one shown in Figure 2.1, with eight electrons populating the “3d” MOs in a high-spin fashion. However, the ground state wavefunction also contains small contributions from excited configurations, achieved by op- timizing all the CI coefficients ak specifically for this state. The orbital opti- mization of the multiconfigurational wavefunction allows both occupied and unoccupied water ligand orbitals to mix in with the nominal Ni 3d orbitals. In the calculations in this work, the energies are calculated using a single set of orbitals, optimized for the energy average of all included states of a given spatial and spin symmetry (state-averaging).

23 ∗ 2b2 H2O ∗ Valence excitation 4a1 eg Ni 3d RAS2 t2g 1b 1 Core excitation H2O 3a1 1b2 H2O 2a1 Ni 3p Ni 3s

H2O 1a1 Ni 2p RAS1 Ni 2s

Ni 1s

2+ Figure 2.1: Molecular orbital diagram of [Ni(H2O)6] . The active space in the RASSCF calculation is divided into the RAS1 and RAS2 subspaces with 14 electrons in 3+5 MOs. In octahedral symmetry, the five Ni 3d orbitals are split into two eg and three t2g orbitals. The water orbital notation is shown in Figure 3.1.

With the active space in Figure 2.1, neither metal-to-ligand charge trans- fer (MLCT) nor ligand-to-metal charge transfer (LMCT) can occur. A third subspace (RAS3), with water orbitals that are empty in the HF and permits a limited number of electrons, can be introduced to enable MLCT excitations from the occupied Ni orbitals to the unoccupied ligand orbitals. Similarly, the active space can be extended by adding occupied ligand orbitals and thus take LMCT excitations into account.

2.3.1 Perturbation theory

The added flexibility in the wavefunction in the CAS(RAS)SCF approach mainly recovers the static correlation. The remaining dynamical correlation can be in- cluded either perturbatively or with subsequent multireference CI calculations [30; 31]. We chose to work with many-body perturbation theory, with the general idea that the solution only differs slightly from the simpler, already solved problem that constitutes the “reference”, and can be added as a pertur- bation. The Hamiltonian of the N-electron wavefunction is then partitioned into a reference and a perturbation Hamiltonian [32]. In second order per- turbation theory, the perturbation Hamiltonian is a two-electron operator. All

24 combinations where two electrons from orbitals that are occupied in the ref- erence wavefunction are excited to virtual orbitals are taken into account in the correction to the energy. The most popular multi-reference perturbation approach is the CASPT2 method [33], which uses a CASSCF reference wave- function. The extension of the method to a RASSCF reference wave function is denoted RASPT2 [34]. In the CASPT2/RASPT2 calculations of multiple states in the present work, multistate CASPT2 [35], where the included states are allowed to mix, has been used.

2.4 Relativistic effects

The Schrödinger equation (Equation 2.3) does not take the consequences of the finite speed of light, affecting both orbital sizes and shapes, into account. Also, magnetic interactions due to the electron spin, spin–orbit coupling, is a relativistic effect. Relativistic corrections affect the chemistry of light elements less, but for heavier elements, the effects are important. The relativistic wave equation for a free electron—the Dirac equation—is a four-dimensional equation [36]. In addition to two spin degrees of freedom, the Hamiltonian contains two components arising from the electron–positron coupling. The Hamiltonian of the N-electron system is assumed to be a sum of such one-electron terms (and potential energy operators). Solving the full four-component equation is however computationally very demanding. In a Douglas–Kroll–Hess transformation [37; 38], the wavefunction is reduced to two components. The relativistic calculations in this thesis have been calcu- lated according to the Douglas–Kroll–Hess scheme implemented in Molcas, which partitions the relativistic effects into a spin-free (scalar) and a spin– orbit part: In the first step, a set of multiconfigurational and correlated states (RASSCF or RASPT2) is computed, via a scalar Hamiltonian. The spin–orbit Hamiltonian for this set of wavefunctions is approximated by a one-electron effective Hamiltonian, within the mean-field model [39], and is calculated in a subsequent step [40]. In Figure 2.2, the method for calculating core-level photoelectron spec- − tra of I3 is presented. The energies of the spin-free and spin–orbit states of − neutral I3 with a single 4d core hole are shown, relative to ground-state I3 . The 4d orbitals are atomic like and localized on the respective nuclei. The states can be distinguished by the site on which the core hole is localized: cen- ter or terminal. Since the set of 4d orbitals on each atom is associated with five ml quantum numbers, there are in total 15 possible electron configurations with one 4d core hole. The corresponding states are characterized by the Λ quantum number, the projection of the orbital angular momentum along the molecular axis. The origin of the different levels is discussed in further detail

25 CASPT2 CASPT2+SO

50.33 Ω = 1/2 50.41 Ω = 3/2 50.41 Ω = 1/2 50.44 Ω = 3/2 50.48 Ω = 5/2 50.63 Ω = 5/2 50.91(1) Λ = 0 51.03(2) Λ = 1 51.03(2) Λ = 1 51.05(1) Λ = 0 51.11(2) Λ = 2 51.26(2) Λ = 2

51.91 Ω = 1/2 51.98 Ω = 1/2 51.99 Ω = 5/2 52.04 Ω = 3/2 52.15 Ω = 3/2 52.16 Ω = 3/2 52.28 Ω = 1/2

52.62(2) Λ = 2

52.83(2) Λ = 1 52.95(1) Λ = 0

53.61 Ω = 3/2

53.82 Ω = 1/2

− Figure 2.2: Energies of isolated I3 relative to the I3 anion. Blue lines represent states with a 4d electron removed from the central iodine atom and red lines states with the core hole on either of the terminal sites. The energies (in eV) to the left are spin-free CASPT2 states, including scalar relativistic effects. The degeneracy is given in parentheses. To the right, the splitting of the levels due to spin–orbit coupling is shown. in Section 4.1. Calculating the spin–orbit part of the Douglas–Kroll Hamilto- nian, with the spin-free states as a basis—letting the spin and orbital momenta couple—leads to a splitting of the 4d level of almost 1.6 eV.

2.5 Simulations of solutions

So far, the system has been an idealized, static, model with molecular geome- tries optimized to an energy minimum without any interaction with surround- ing molecules. In reality, the problem contains both dynamics and environ- mental effects and any property of the system, such as its total energy, depends on where the atoms or molecules are found in space and how fast and in what

26 direction they are moving at a specific time. A system composed by N particles is thus characterized by the position and momentum of each particle. A par- ticular combination of positions and momenta represents a point in the phase space. Due to the interaction between the particles, the properties of the system fluctuate over time. If the minima on the potential energy surface are found, the properties can be calculated using statistical mechanics. Experimental mea- surements of properties of liquids and solutions are however made on systems with huge numbers of atoms or molecules, with many minima in the potential energy surfaces. With quantum chemistry it is possible to find the configura- tions of atoms giving minima in a potential energy surface only for small or ordered systems, but by generating representative configurations from a man- ageable number of atoms and molecules, simulations can predict properties with reasonable computational effort for disordered systems such as liquids. There are two main techniques for sampling phase space configurations. Molecular dynamics (MD), used in this thesis, simulates the dynamical behav- ior of the system over time. Provided that the time interval is long enough, the time averages of the system’s properties take the value of the average, mea- sured in experiment. Monte Carlo simulations, on the other hand, generates configurations randomly, according to a probability distribution representative for the physics allowed in the system. Rather than letting the system evolve in time, the statistical average of the sought property is calculated over the visited configurations. For a sufficiently large number of configurations generated, the average is going to be the same as the one found in the time domain. All the experiments in Paper I–VIII were done in solution. In the following section, MD simulations of solutions and analysis of the simulated trajectories are treated.

2.5.1 Molecular dynamics

MD simulations rely on the Born–Oppenheimer approximation separating the motion of nuclei and electrons. The fundamental particle in the simulations is the atom, or sometimes even molecular fragments. The electrons are not explicitly described, but are included as a single parametric potential energy surface. The atoms are assumed to obey classical dynamics and the time evolu- tion of the system is obtained by numerical integration of Newton’s equations of motion d m x˙ = F = −∇ U, (2.10) i dt i i i where Fi is the force on particle i, mi its mass, x˙i its velocity, and ∇iU the gradient of the potential energy. After calculating the resulting force acting on

27 an atom due to its neighbors, all particles move under the constant force for a short timestep. The forces are then recalculated for the new positions. In order to compute the forces in a classical MD simulation, a force field with parameters describing the intermolecular and intramolecular interactions is required. Often, the Lennard-Jones potential [41] is used for modeling the pairwise van der Waals interactions between atoms, and a Coulomb potential where each atom is represented by a point charge for the electrostatic contribu- tion to the intermolecular interactions. Bending and stretching of molecules, the intramolecular interactions, can be modeled as harmonic potentials. In ad- dition, suitable initial and boundary conditions for the simulations have to be chosen.

Ab initio molecular dynamics

The force fields used in classical MD are usually based on empirical data or independent electronic structure calculations, and the predefined potential does not allow for changes in the electronic structure, such as when bonds break and form. Ab initio MD does not use a parameterized force field, but the calculation of the forces is based on quantum chemistry. Since the av- erage electronic energy is calculated for the configuration of atoms in every timestep, also more complex chemical systems can be described with ab inito MD. Two ab initio MD methods are Born–Oppenheimer and Car–Parrinello MD. In Born–Oppenheimer MD the wavefunction is optimized to the ground state in every timestep [42]. After an initial optimization of the wavefunc- tion, Car-Parrinello MD lets the wavefunction evolve simultaneously with the changes of the nuclear positions, by mapping the quantum/classical problem onto a purely classical one. The expansion coefficients of the wavefunction are treated as dynamical variables, and through this procedure, the compu- tationally expensive wavefunction optimization iterations are avoided, as the wavefunction is kept close to the ground state. The computational drawback is that Car–Parrinello MD requires a very short timestep, and hence a larger number of iterations. [43]

Information from MD simulations

An MD simulation generates a trajectory with the time evolution of the particle positions and velocities and provides information of both averages of structural properties and dynamic quantities. For a measure of the local structure around a specific atom type, the trajectories can be analyzed in terms of radial dis- tribution functions (RDFs). The RDF g(r) gives the probability of finding an atom in a thin spherical shell at the distance r from another atom, relative to

28 I − O I − H g(r)

2 3 4 5 6 Distance / Å Figure 2.3: I–water radial distribution functions for I− in aqueous solution. Thick lines corresponds to the I–O RDF and thin lines to I–H RDF. The first iodide–hydrogen maximum at 2.6 Å interatomic separation results from hydro- gen bonding. a uniform particle distribution. The structure factor of materials, measured in x-ray and neutron scattering experiments, is directly related to the RDF. Figure 2.3 shows ion–water RDFs for I− in aqueous solution. The RDF maxima correspond to the distances from the ion at which the water oxygen and hydrogen concentration on average is high during the simulation, and are hence directly related to the hydration shells around the ions. As expected for an anion, the I–H RDF in Figure 4.4 shows that the water hydrogen is coor- dinating the iodide ion in aqueous solution, with a well-defined RDF maxi- mum at a typical hydrogen bond length of 2.6 Å and the oxygen peak about 1 Å outside this maximum. We shall return to the triiodide ion in solution in Chapter 4.1. The description of the local structure of a molecular system is limited to the radial dependence in the RDF, but a spatial distribution function (SDF) resolves the information into spatial details. The SDF spans both the radial and angular coordinates of the interatomic separation vector and gives a three- dimensional distribution of a particle type with respect to another molecule. [44] Usually, the SDF is represented as a isosurface, with regions of the same in- tensity plotted in a three-dimensional coordinate system.

2.5.2 Solvation models A solute placed in a solvent causes the solvent dipoles to redistribute them- selves to adjust to the solute charge. The charge distribution within the solvent molecules also changes, i.e. they are polarized. The effect is screening of the solvent charge in solution as compared to vacuum. Solvent effects can

29 essentially be introduced in electronic structure calculations in two ways: by considering explicit solvent molecules or by implicit modeling of the solvent’s influence on the solute. In order to study the influence from the solvent on the electronic structure of the solute, small solute–solvent clusters were extracted from the MD trajectories. Quantum chemistry calculations of the geometries with explicit solvent molecules could then be performed on the geometries representing the distribution of configurations. Continuum models such as the Born model [45] and the Polarizable con- tinuum model (PCM) [46] instead include solvent effects implicitly through macroscopic properties of the solvent. The Born model treats the solute as a point charge, placed inside a spherical cavity in a structureless continuum with the dielectric constant ε, representative for the solvent’s ability to screen charges. The higher the dielectric constant, the more the effective charge is reduced. In PCM, the solute is also placed in a cavity in a structureless polarizable medium representing the solvent. The solute is treated with quantum mechan- ics. The electric field around a charge in solution is weakened due to polariza- tion of the solvent and the distribution of solvent dipoles. In the PCM model, point charges on the cavity surface represent the reaction field created due to the polarization of the solvent in the presence of the solute. The reaction field in turn perturbs the solute and by adding the reaction field perturbation in the Hamiltonian, the Schrödinger equation can be solved self-consistently. The solute–solvent interactions in electronic spectra are described in more detail in Section 3.2.1.

30 3. Concepts in spectroscopy

Spectroscopy is about studying matter’s interaction with light. Since every chemical element absorbs light at certain wavelengths, and only the lowest transitions depend strongly on the formation of chemical bonds, the response of the system when it is illuminated with photons with a known energy gives information about the atoms and molecules present in the sample. The results presented in this thesis are based on spectroscopic techniques using x-ray ra- diation to excite the system from the initial state |0i to a final state | f i.

3.1 Core and valence electronic levels

The electronic structure of a molecule is divided into core and valence orbitals. Inner-shell, or core, electrons are not involved in chemical bonding, but have atomic character. The core-level binding energy, the energy required to release a core electron from the material, lies in the x-ray region of the electromagnetic spectrum. Valence orbitals are delocalized over the molecule and lower energy is needed to ionize the molecule from the valence: Typical binding energies are in the ultraviolet–visible (UV–Vis) range of the electromagnetic spectrum and they are more closely spaced than the well-separated core levels. To exemplify, Figure 3.1 shows the orbitals of the water molecule and the electronic binding energies associated with them. The local nature of the electronic core levels allows for studying the elec- tronic structure, chemical bonding, and dynamics in electron transfer processes with element and site specificity, using core-level spectroscopic techniques. By absorption of x-ray radiation, a core electron is promoted to an occupied level, which can thus be coupled to the original core level at a particular atom. This feature is particularly useful for accessing the unoccupied levels of the elec- tronic valence of a solvated compound, which often overlap strongly with the more intense excitations in the solvent valence in the UV–Vis region. The x- ray absorption processes are shown schematically in a one-electron picture in Figure 3.2.

31 Atomic orbitals Molecular orbitals Binding energy (eV)

H 1s 2b2 O 2py

H 1s

4a1 O 2pz

1b1 O 2px 12.6 [48]

H 1s 3a1 14.8 [48] O 2pz

H 1s 1b2 O 2py 18.6 [48]

H 1s 2a O 2s 1 32.6 [48]

1a O 1s 1 533 [47]

Figure 3.1: Molecular orbitals of the water molecule. In the ground state, the five lowest orbitals are occupied. The lowest orbital is a core orbital, localized at the oxygen atom, and does not contribute to the bonding. The four highest occupied orbitals are valence orbitals. The two lowest unoccupied orbitals are antibonding between O and H. The orbitals have symmetry labels within the C2v point group.

3.2 Photoelectron spectroscopy

Photoelectron spectroscopy (PES) is based on ionization of the material by photons with sufficiently high energy hν hitting its surface. According to the photoelectric law [49; 50], the sum of the energy required to release the elec- tron from the material (the binding energy, BE) and the kinetic energy (KE) of the leaving photoelectron equals that of the incident photons:

hν = BE + KE. (3.1)

The photoionization process can be considered an electronic transition at fixed molecular geometry, from the initial state |0i with N electrons, to a final state | f i with N − 1 bound electrons and a non-interacting photoelectron. The

32 XPS hν A i ii

B XAS

Figure 3.2: Excitation processes identified in core-level spectroscopy. Ab- sorption of an x-ray photon with energy hν can induce (A) emission of a core- level photoelectron (i) if the photon energy hν is higher than the binding energy (Section 3.2). The combination of core-level photoemission and valence excita- tion (ii) results in shake-up satellites in the spectrum (Section 3.2.2). If the photon energy is smaller than the binding energy and matches an absorption edge (B), a transition to an empty state can occur (Section 3.3). binding energy is the energy difference between the two states

BE = E f − E0. (3.2)

This is not a one-electron quantity, but includes the relaxation of the electronic structure due to the presence of the created hole. In an x-ray photoelectron spectroscopy (XPS) experiment, the binding energies associated with the ener- gies of the detected photoelectrons at a given x-ray photon energy give rise to a spectrum that is a fingerprint of the occupied electronic levels in the material. The electronic transition is usually assumed to be vertical. It occurs on a short timescale in comparison to the nuclear motion, so that the binding energy does not contain nuclear relaxation effects. However, the ion can be created in a vibrationally excited state, with a geometry different from the ground state. This leads to variations in the binding energy and accordingly broadens the spectral line.

33 LiI (aq) Gas Solvated Gas Solvated Li2+ I Intensity / Arb. units gas gas 62 60 58 56 54 52 50 solv BE BE BE solv Gas (theor.) BE

Li+ I− Intensity / Arb. units 77 75 73 52 50 48 46 Binding energy / eV

Figure 3.3: Solvation effects on the Li+ and I− binding energies. Left: Sol- vation of the Li+ and I− ions shifts the core-level peaks in the photoelectron spectrum. Due to spin–orbit coupling, the I 4d peak is split into a doublet, cor- responding to the P3/2 and P5/2 final states. Right: Upon ionization (q → q + 1), the electrostatic stabilization of Li+ due to solvation increases, but vanishes for − I , leading to opposite signs of the binding energy shift SIBES = BEsolv −BEgas.

3.2.1 Chemical shifts in core-level spectra

Although the core electrons do not take part in chemical bonds, the core level binding energies of a specific atom are altered by its chemical environment, which adds site-specific information to the spectrum. This chemical shift is an intramolecular effect, arising due to the different screening of the nucleus by the valence charge distribution on chemically inequivalent atoms of the same element. Binding energies are also affected by intermolecular interactions. In spec- tra of ions dissolved in a solvent, solute–solvent interactions shift the ion bind- ing energies with respect to the gas phase. This solvent-induced binding energy shift (SIBES) originates from solvent polarization as a response to ionization and solvent-induced polarization of the solute and is negative for a cation but positive for an anion. Figure 3.3 illustrates the initial and final state effects on the SIBES of oppositely charged ions. In the case of a solvated cation, the electrostatic interaction between solute and solvent increases when the photo- electron leaves, resulting in a lower binding energy than in the gas phase. In contrast, the anion–solvent electrostatic interaction decreases, shown as SIBES towards higher binding energy.

34 3.2.2 Satellites in photoelectron spectra The sudden change in screening when a core electron is emitted from the sys- tem can induce a transition with a valence excitation and core ionization oc- curing simultaneously. The photoelectron is therefore detected at lower kinetic energy. The resulting structure, appearing at higher binding energy than the corresponding main peak in the photoelectron spectrum, is known as a shake- up satellite. Double-ionization of the ion by a valence electron accompanying the leaving core photoelectron is called a shake-off process.

3.3 X-ray absorption spectroscopy

If the incident photon energy is lower than the electronic binding energy of a level in the material, a transition can occur to an excited state, with a core hole being created and empty electronic levels populated. In contrast to an XPS experiment at fixed photon energy, where the photoelectron intensity is recorded as a function of the kinetic energy, x-ray absorption spectroscopy (XAS) measures the intensity of absorbed x-rays as a function of the photon energy. Similar to XPS, the absorption spectrum has strong features at spe- cific photon energies for all elements and oxidation states. These resonances correspond to transitions from the initial state |0i to bound core-excited states | f i. Thus XAS probes the unoccupied electronic structure, mapping it onto the absorbing atom. The XAS region close to an absorption edge is very sensitive to the nearest neighbors of the absorbing site, and the chemical shifts and fine structure above the edge contains information about the local bonding envi- ronment. The energy region close to an absorption edge is probed with near edge x-ray absorption fine structure (NEXAFS) spectroscopy. At excitation energies > 30 eV above the ionization limit, a weaker fine structure, caused by backscattering of the emitted electron off neighboring atoms arises. This energy region is usually denoted the extended x-ray absorption fine structure (EXAFS) region and gives information of the interatomic distances.

3.4 Core hole decay

The core hole, created through absorption of an x-ray photon, has a short life- time and typically decays on the femtosecond timescale. The core vacancy is filled by a valence electron and the excess energy is released either via au- toionization, where a valence electron is emitted (the Auger effect), or emitted as x-ray radiation (fluorescence). For light elements, Auger decay dominates, while fluorescence is the preferred decay mechanism at higher atomic num- bers.

35 3.5 Peak intensities and spectral line shape

The intensity of a particular line in a spectrum is directly related to the proba- bility for photon absorption or emission. An external electromagnetic field can initiate an electronic transition in an atom or a molecule, both via electric and magnetic interactions. The transition probability for the electronic transition |0i → | f i depends on the transition moment matrix element

M0 f = h f |W|0i, (3.3) where W is the operator describing the interaction between the field and the atom or molecule. If the photon energy Ω matches the energy difference be- tween the two states E f −E0 and M0 f is nonzero, the transition can occur with the transition probability w0 f given by Fermi’s golden rule [51]:

2 w0 f ∝ |M0 f | δ(E f − E0 − Ω). (3.4)

The most important type of interaction is the electric dipole interaction, where the oscillating electric field of the radiation perturbs the system due to the inter- action with its charge distribution, thus changing the total angular momentum by one unit. For the calculated 2p → 3d spectra in this work, only dipole transitions are considered.

3.5.1 Linewidths and shapes of x-ray spectra

The XAS resolution is limited by the intrinsic lifetime. Due to the time–energy uncertainty relation, the final state energy is only known up to the accuracy de- termined by the lifetime of the final core-excited state. The finite lifetime of the excited state results in a Lorentzian broadening of the spectral line, the natural broadening. The shorter the lifetime, the larger the Lorentzian linewidth. Con- figurational broadening, which can be seen as small chemical shifts caused by geometry fluctuations, and experimental resolution also affect the linewidth by a Gaussian distribution of the energies. Other effects that may give a Gaussian contribution to the spectrum, although usually small, are vibronic coupling and fine structure. The total peak shape is typically given by a Voigt func- tion, a convolution of the different broadening mechanisms of Gaussian and Lorentzian character.

36 Total energy

Em ω Ω

Ef E0

Figure 3.4: The RIXS process. The molecule is excited from its initial state |0i to an intermediate state with a core hole |mi by absorption of a photon with energy Ω. The metastable state |mi decays to the final state | f i under emission of a photon with energy ω. The dashed arrow represents the elastic scattering when Ω = ω, and the solid represents decay to a valence-excited final state. The energy left in the system (loss) is given by Ω − ω. (Adapted from Ref. [52].)

3.6 Resonant inelastic x-ray scattering

In resonant inelastic x-ray scattering (RIXS) spectroscopy, the photon energy is scanned across an absorption edge, and the intensity of x-rays emitted in the fluorescence process is detected as a function of the incident energy. From energy conservation it follows that the secondary photon is emitted with an energy

ω = Ω − ω f 0, (3.5)

where Ω is the incident photon energy and ω f 0 the energy transfer in the tran- sition |0i → | f i. Elastic scattering of the photon (ω = Ω) gives rise to a feature at zero energy transfer in the spectrum, corresponding to elastic decay of the core-excited state |mi back to the initial state: |0i → |mi → |0i. This process is indicated with a dashed arrow in the scheme in Figure 3.4. However, sev- eral decay channels are possible, with the final state | f i being valence-excited (the solid decay arrow in Figure 3.4). Since the final state energy is higher than the initial ground state, these transitions appear as peaks at ω f 0 > 0. The corresponding peaks in the spectrum correspond exactly to valence excitation energies. Thus, RIXS can be used to probe the electronic valence, with atom- specificity, due to the spatial localization of the intermediate core-excited state.

37 3.6.1 Transition probabilities for second order processes The RIXS process is more involved than the one-photon XAS and XPS pro- cesses. The absorption of a photon with energy Ω and emission of a pho- ton with energy ω in Figure 3.4 should be considered a single-step scattering event rather than separable absorption and emission, and the first-order term in Equation 3.4 is not suitable for describing the transition probability. The Kramers–Heisenberg dispersion formula [53] gives an expression for the scat- tering amplitude Ff (Ω) to the final state | f i:

2 Ω − ω − iΓ |F (Ω)|2 = ω ω D0† D k0 k (3.6) f ∑ k f k0 f k k0 2 2 k (Ω − ωk0) + Γk with the intermediate–final and intermediate–initial state energy differences 0† ωk f and ωk0 (Ek − E f and E f − E0 in Figure 3.4). D f k and Dk0 give the transi- tion probabilities, defined as the projection of the electronic dipole moment µ of the molecule onto the electric field vectors of the incident and emitted light respectively. The sum runs over all the possible intermediate states and allows the decay channels from different intermediate states to a given final state to interfere through the square modulus of the scattering amplitude. The RIXS intensity is a function of both the incident and emitted photons and is obtained 2 as a sum of |Ff | over all final states:

(ω−Ω+ω )2 Ω Γ f 1 − f 0 I( , ) |F |2 · · √ e γ2 . (3.7) Ω ω ∝ ∑ f 2 2 ω f π((ω − Ω + ω f 0) + Γ f ) πγ

The parameters Γk in Equation 3.6 and Γ f in Equation 3.7 are the Lorentzian broadening parameters due to the intermediate state |ki and final state | f i life- times. In addition to a Lorentzian function, Equation 3.7 also contains a Gaus- sian contribution from experimental and configurational broadening, the width controlled by γ. In this thesis, interference effects and the polarization depen- dence was neglected in the RIXS spectrum calculations, and also the influence of the nuclear dynamics in the core-excited state.

3.7 Time-resolved spectroscopy

At equilibrium, chemical reactions typically occur on the millisecond time scale. Electronically excited states, however, decay within femtoseconds, and by photoexcitation, reactions can be triggered on this short time scale. In order to study the behavior of a photochemical system after absorption of sunlight— is the system stable or does it form reaction products, and are intermediate

38 states involved in the relaxation path?—the events have to be followed with femtosecond resolution. This is possible in ultrafast pump–probe experiments, where the reaction is initiated with a a short laser pulse (‘pump’) and changes in the electronic structure of the system are probed at well-defined time delays in the femtosecond regime with a second laser pulse. X-ray probes, such as XPS or RIXS, give an element and chemically specific perspective on changes in the electronic structure. These “molecular movies”, adding the dimension of time to the spectra, are created using free-electron lasers or synchrotron radiation as light sources. In order to model and interpret the time-resolved spectra, it is important to be able to simulate spectra for configurations along a chemical reaction.

39 40 4. Summary of results

The discussion of the results in this chapter is divided into four parts. The first − − section treats the solvent dependence of the electronic structure of I and I3 in solution, studied with a combination of MD simulations and theoretical spec- trum calculations and XPS experiments of the solutions. In the second section, the solvation structure of a ruthenium complex in lithium halide solutions, sim- ulated with classical MD, is analyzed. The two last sections cover studies of the electronic structure of transition metal complexes, starting by demonstrat- ing the multiconfigurational SCF approach to calculating core-level spectra on Ni2+ ions in aqueous solution and assigning the details in experimental XAS and RIXS spectra, and finally showing how changes in time-dependent RIXS spectra of an iron complex in ethanol solution can be attributed to changes in electronic spin and molecular geometry during a reaction.

− − 4.1 Solvation and electronic structure of I and I3

− − In the first dye-sensitized solar cells from the beginning of the 90’s, the I /I3 redox couple was used as the hole transporting medium [8; 54] and this has since been the most widely used electrolyte. Iodine based systems are also important for many applications in medicine and biology [55–57]. For the understanding of the redox mechanisms, knowledge abouth the fundamental solvation phenomena and the energies involved is useful. In Paper I–III, we have used quantum chemistry, MD, and XPS to study the iodine 4d electronic − − structure of I and I3 , solvated in various solvents. XPS has been used before − for investigating the electronic structure of I3 in solution, then with the main focus on the spectroscopic features [58]. The combination of multiconfigu- rational quantum chemistry calculations and MD simulations, together with experiments measuring photoelectron spectra by irradiating a liquid jet of the sample solution with x-ray radiation, give insight into the microscopic solva- tion details. All the studied solvents were polar, but with different ability to form hydrogen bonds. We observe a large dependence on the local solvent structure in the solva- − − − tion energies of I and I3 . For the I3 molecular structure, short-range interac- tions are important and can cause I–I bond distortions.

41 AcCN EtOH Water Gas (theo.)

SIBES Intensity / arb. units

58 56 54 52 50 48 Binding energy / eV

Figure 4.1: I 4d spectra of LiI in solution. The difference between the bind- ing energies in solution (experimental) and the gas phase energy (calculated) is denoted SIBES, solvent-induced binding energy shift. The largest SIBES is ob- served for aqueous LiI and the smallest for acetonitrile solution.

4.1.1 Solvent-induced binding energy shifts of I−

Solvation of the I− ions causes a shift of the core-level binding energies, as de- scribed in Section 3.2.1. The magnitude of the binding energy shift in solution varies with the solvent: Down the series water → ethanol → acetonitrile, the I 4d photoelectron spectra in Figure 4.1 show a decreased SIBES. This trend is connected with the type of interaction in the solution: Water and ethanol form hydrogen bonds to the ion, while acetonitrile is a polar solvent without hydrogen bonds. Strong hydrogen bonding leads to a large solvation energy, and consequently large core-level SIBES towards lower binding energy for the anion (see Section 3.2.1). The solvent structure is important for the stabilization of the ion: The I 4d SIBES of I− dissolved in ethanol, which forms hydrogen-bonded chains or clusters, is weaker than in aqueous solution. A simple electrostatic argument, based on a single constant ε characterizing the solvent ability to screen elec-

42 Table 4.1: Experimental and calculated solvent-induced I 4d electron binding energy shifts (SIBES) in water, acetonitrile, and ethanol. The theoretical values are obtained within the PCM model at the CASPT2+SO level of theory and with CASSCF+SO calculations of cluster configurations including the first and and up to the second solvent shell, sampled from MD simulations of LiI in solution.

SIBES Water Ethanol Acetonitrile Experimental 4.2 3.6 3.4 Born 3.09 3.00 3.04 PCM 5.33 5.18 5.25 Cluster: 1 shell 2.80 ± 0.40 1.47 ± 0.37 1.36 ± 0.14 Cluster: 2 shells 3.84 ± 0.27 trostatic charges, fails to capture the SIBES trend for the series of solvents. The SIBES predicted with the Born model for a cavity radius of 2.30 Å in Ta- ble 4.1 is almost the same for all three solvents. Similarly to the Born model, PCM gives essentially the same SIBES for the three solvents (Table 4.1) and also overestimates the shift somewhat. Calculations of clusters with explicit solvent molecules take the short-range solute–solvent interactions such as hy- drogen bonding into account and reproduces the relative energy ordering of the shifts. The main challenge with this approach is however to treat clusters suf- ficiently large to describe the solvation in bulk at the high QC level, and even with two hydration shells included, the SIBES in Table 4.1 does not converge to the experimental value. The experimental SIBES is derived from the difference between the bind- ing energy measured in liquid experiments and gas-phase CASPT2+SO calcu- lated values. The active space in the CASSCF/CASPT2 calculations consisted of the 4d orbitals and the 5s and 5p valence, with the orbitals optimized for the energy average of the 4d orbitals.

− 4.1.2 Geometry of I3 in solution − In its ground state, the gas-phase I3 is symmetric, and the bond length of the isolated molecular ion is optimized to 2.91 Å with CASPT2 including spin– orbit coupling. Most of the electron density is localized at the terminal sites, which essentially share the net negative charge (-1). In Chapter 2, it was shown − that the core-level binding energies of I3 in Figure 2.2 originating from pho- toemission from core orbitals on the central iodine atom were distinguishable from those where photoemission occured from one of the terminal atoms. The reason for the binding energy difference is the excess of valence charge on the terminal iodine atoms, that results in less strongly bound core electrons on the terminal iodine sites. The 4d core holes on the two equivalent terminal atoms

43 a) MD/CASSCF b) c) EXP Total I − ∆ − 3 r I3 (g) MD LiI 0.55 Å − I2(g) I3 (aq) MD CASSCF 0.52 Å H2O 0.32 Å

0.29 Å CASSCF − I3 (g) OPT 0.25 Å AcCN 0.16 Å Intensity / Arb. units 0.14 Å Terminal 0.10 Å EXP Center

0.10 Å EtOH EtOH

0.05 Å 60 58 56 54 52 60 58 56 54 52 60 58 56 54 52 Energy / eV Energy / eV Energy / eV

− Figure 4.2: I 4d spectra of I3 . (a) CASSCF+SO I 4d photoelectron spectra of − I3 in 10 different configurations, ordered according to bond length symmetry. (b) Top: Average of the spectra in (a), of the isolated ion (red) and surrounded by a layer of explicit water molecules (violet). Middle: Calculated spectrum − of optimized I3 , showing lines arising from photoemission on the center and − terminal atoms separately. Bottom: Experimental spectrum of I3 dissolved in − ethanol, decomposed into terminal and center contributions. (c) Experimental I3 spectra in water (top), acetonitrile (middle), and ethanol (bottom). give rise to degenerate states, but with the hole localized on either of the two terminal sites. − What is then the effect of solvation of I3 ? In Paper II and III, water, − methanol, ethanol and acetonitrile solutions containing I3 are studied with quantum chemistry, MD, and XPS. The local structure of the solvent affects not − only the magnitude of the solute SIBES, but also the I3 geometry, and we fo- cus in particular on the strong coupling between the structural rearrangement − of the solvent and the solute dynamics in aqueous I3 , leading to molecular symmetry breaking. − Previous studies show that I3 is linear and symmetric when dissolved in polar solvents, such as acetonitrile, but is distorted in hydrogen bonding sol- vents [59; 60]. The experimental acetonitrile I 4d spectrum can easily be de- composed into terminal and center contributions, consistent with the respective

44 4.0

left right long short 3.8

3.6

3.4

3.2

I−I distance / Å 3.0

2.8

2.6 0 10 20 30 40 Time / ps Distribution

− Figure 4.3: MD simulation results for I3 in aqueous solution. The time evo- lution in the I–I bond lengths contains periods of a pronounced asymmetry, high- lighted by sampling of the longest and shortest I–I bond. contributions calculated for a symmetric molecular ion (CASSCF+SO), in the middle figure in panel b. The spectrum from ethanol solution can be deconvo- luted in the same manner and is shown under the theoretical spectrum in panel b in Figure 4.2. Water’s strong hydrogen bonding ability, however, leads to large bond − length fluctuations of the I3 ion in aqueous solution. Figure 4.3 shows the bond length distribution during a Car–Parrinello MD simulation of LiI3(aq) and includes extremely distorted geometries, with I–I distances well over the typical covalent bond. The geometry distortions are associated with polariza- − tion of the I3 ion: In the observed partial dissociation, the major fraction of the negative charge is localized at the partially detached iodine, with very little change in the center atom charge. Hence, the core electron binding energies of a strongly distorted triiodide ion can be expected to shift with respect to the gas-phase optimized configuration. The spectra in panel a in Figure 4.2 − are calculated for isolated I3 , with geometries sampled from the MD simula- tion of the solution, and show that the degeneracy of the terminal I 4d levels is lifted, shifting the peaks in opposite directions with increasing bond length asymmetry. In Figure 4.4, water–triiodide RDFs are decomposed into separate RDFs for each of the iodine atoms: the center atom and the iodine atoms at the longest and shortest distance from the center iodine in each timestep. The hy- drogen RDF for the iodine at the longest separation (”long”), which is also the more negative side of the molecule, has a pronounced maximum that coincides with the first maximum of the iodide ion. This indicates that the solvation of − the terminal iodine at the largest I–I separation in I3 is similar to the solvation

45 I − O I − H Iterminal,short Icenter Iterminal,long

I−(aq)

− g(r) I3 (aq)

− I3 (aq)

2 3 4 5 6 Distance / Å Figure 4.4: RDFs between water oxygen and hydrogen and iodine in aque- − − ous I and I3 . Thick lines corresponds to I–O and thin lines to I–H RDFs. − The water–I3 RDF is analyzed with respect to the contribution from each iodine atomic site, with the terminal contributions labeled according to their distance to the central atom. of I−. The signal of hydrogen bonding between iodine and water is absent in the corresponding RDFs for the central atom and the closest iodine. From this we understand that the charge localization is also correlated with the solvent polarization. The geometry distortions, linked with the rearrangement of the water molecules in the hydrogen bond network, can explain the fact that the experimental photoelectron spectrum of aqueous triiodide, shown in panel c in Figure 4.3 (top), is not easily decomposed as in the other solvents. The dis- − tortion of the I3 molecule is markedly correlated with the solvent’s hydrogen bonding strength. Figure 4.5 shows the partial atomic charge on each of the io- dine sites at 1000 timesteps during CPMD simulations of each of the solutions. The negative charge on a terminal site increases almost linearly with the bond asymmetry ∆RI−I. Water displays strong hydrogen bonding, and in aqueous − solutions, the I3 asymmetry is also the most pronounced. For ethanol, the ef- fect from hydrogen bonding on the geometry is not significant, and ethanol and acetonitrile solutions have similar distributions of the terminal atomic charges. The maximum ∆RI−I is about 0.4 Å in both solvents. Methanol also forms hy- drogen bonds, and the asymmetry distribution is an intermediate case between

46 0 0 I −0.2 center −0.2 Iterminal,short −0.4 Iterminal,long −0.4

−0.6 −0.6

Löwdin charges − Löwdin charges − I3 in acetonitrile I3 in water −0.8 −0.8 0 0.2 0.4 0.6 0.8 1 1.2 0 0.2 0.4 0.6 0.8 1 1.2 ∆ ∆ RI−I / Å RI−I / Å

0 0

−0.2 −0.2

−0.4 −0.4

−0.6 −0.6 Löwdin charges − Löwdin charges − I3 in ethanol I3 in methanol −0.8 −0.8 0 0.2 0.4 0.6 0.8 1 1.2 0 0.2 0.4 0.6 0.8 1 1.2 ∆ ∆ RI−I / Å RI−I / Å

− Figure 4.5: Partial atomic charges of solvated I3 , sampled from ab initio MD simulations. The charge on the terminal iodine atoms (Iterminal,short and Iterminal,long) is directly proportional to the bond length asymmetry ∆RI−I. The asymmetry distribution is the broadest for water, which displays strong hydrogen bonding. water and etanol/acetonitrile. − The asymmetry of the I3 ion may favor iodide polymerization in aqueous solution, and so be important for the stability of photoelectrochemical cells containing iodide based electrolytes as water impurities may speed up the aging process, due to polymerization. The coupled solute–solvent dynamics could also influence the cell performance through the effect of large geometry − distortions on the interactions between I3 and dye or semiconductor surface.

2+ 4.2 [Ru(bpy)3] in lithium halide solution

As a result of their partially filled d orbitals, transition metal atoms or ions readily form coordination complexes by binding ligands covalently to the metal center. Since metal complexes often absorb well in the visible region of the electromagnetic spectrum, they are used in many applications capturing solar energy. Ruthenium-based dyes with bipyridine ligands have proven both ef- ficient and stable and have traditionally been used as photosensitizers in dye- − − sensitized solar cells, together with the I /I3 redox couple as the hole con- ducting medium. When the metal complex is illuminated by visible light it can undergo an electronic transition to an excited state. The photoexcited dye

47 2.5 9 18 Ru−I Ru−I Ru−I Ru−Cl 8 Ru−Cl 16 Ru−Cl 2 H2O Ru−O 7 AcCN Ru−N 14 EtOH Ru−O Ru−O Ru−N Ru−O 6 12 1.5 ) 5 10 r

(

g 4 8 1 3 6 0.5 2 4 1 2 0 0 0 4 6 8 10 12 14 4 6 8 10 12 14 4 6 8 10 12 14 r / Å r / Å r / Å

Figure 4.6: RDFs between Ru and halide ions in solution. The maxima cor- respond to regions with high I− (violet) or Cl− (green) concentration with re- 2+ spect to the Ru center of [Ru(bpy)3] . The dashed lines represent solvent oxy- gen/nitrogen. injects an electron into an electron conductor. After photooxidation, the dye returns to the initial state by oxidizing an iodide ion in the solution. The details of the regeneration process are not fully understood, but it has been shown that it involves complexation of the dye cation and I−, and in order to understand the mechanism and optimize the working performance, insight in the interac- tion between the dye and counterions in solution is needed. We have studied 2+ the interaction between the [Ru(bpy)3] prototype complex and halide anions in water, ethanol, and acetonitrile solutions using classical MD simulations. In the Born model [45], the electrostatic free energy change needed to solvate an ion with charge Zie and radius ri in a solvent with the dielectric constant ε is given by 2 2   Zi e 1 ∆Gelstat = − − 1 , (4.1) 8πε0ri ε where ε0 is the vacuum permittivity. In this model, the ion is represented by a point charge in a sphere with radius ri. The inverse r dependence in Equa- tion 4.1 reflects the fact that an ion with a smaller radius has higher surface charge density than an ion with the same charge but larger radius, and hence interacts more strongly with the solvent. The electrostatic interaction between ions in solution is reduced as a result of solvent polarization and the orientational distribution of solvent dipoles due to the presence of the solvated ions. The local structure around the ruthenium complex can be analyzed in terms of RDFs (see Section 2.5.1). Increased con- − − 2+ centrations of I and Cl with respect to [Ru(bpy)3] are caused by attractive electrostatic interactions between the negatively charged halide ions and the positively charged metal complex. The maximum g(r) in the Ru–halide RDFs in Figure 4.6 increases with decreasing dielectric constant ε of the medium, in

48 2+ Figure 4.7: Snapshots from MD simulation of [Ru(bpy)3] in aqueous solu- 2+ tion. Water molecules in the first hydration shell of [Ru(bpy)3] form ordered chains between the bipyridine ligands (left). The second hydration shell mainly covers the bipyridine ligands (right).

the order H2O(ε = 78) < AcCN (ε = 37) < EtOH (ε = 25). Large values of g(r) can be interpreted as ion pairing occuring easily. 2+ In the [Ru(bpy)3] complex, the ruthenium atom carries most of the pos- itive charge and three bipyridine ligands are coordinating to the ruthenium center. This gives the ion a peculiar solvation structure: The molecules in the first solvation layer align themselves in a symmetrical pattern in the spacing between the ligands, shown for water in Figure 4.7, with water and ethanol oxygen and acetonitrile nitrogen coordinating the metal. The second maxi- mum in the Ru–solvent RDFs in Figure 4.6 is pronounced, which shows that a single solvation shell does not screen the charge of the Ru(II) complex suf- ficiently, but a second solvation layer is formed further out from the metal, mainly above the bipyridine ligands. The Ru–halide RDFs in the various solvents in Figure 4.6 differ also with respect to the ratio between the maxima in a given solution. In water, the Ru–I RDF has two well-defined maxima: the first between the two water shells, and the second in the outer region of the second solvation layer. In contrast, the only region with significantly enhanced Cl− density with respect to the bulk concentration in aqueous solution is outside the second hydration shell. The reason is the strong interaction between the small Cl− ion and water; Cl− binds strongly to its own hydration shell and the effective size of the anion results in a very low probability for entering in between the ligands. SDFs are useful for 2+ visualizing the three-dimensional solvation details around [Ru(bpy)3] . The SDFs of water oxygen and halide anions with respect to the metal complex

49 Figure 4.8: Spatial distribution functions of water and halide ions with re- 2+ spect to [Ru(bpy)3] in aqueous solution. Water oxygen and hydrogen are shown in red and white respectively. The I− density (violet) is high between the bipyridine ligands, above the first hydration shell, while the Cl− concentra- tion is very low at that distance. Both anion types are found outside the second hydration shell above the ligands with high probability. in Figure 4.8 show that it leads to spatially different regions of high relative concentration of aqueous I− and Cl− ions. I− is found immediately outside the hydrogen-bonded water chain between the ligands, at the Ru–I distance for the first maximum in the RDF in Figure 4.6 (H2O). A second region with large g(r) is found about 8 Å from the Ru center, outside the second hydration layer above the pyridine rings. In contrast, the relative Cl− concentration in the interligand spacing is much lower than the average in solution. As a conse- quence of the presence of I− in the outer boundary of the first hydration shell, the first maximum between Ru and water oxygen in Figure 4.6 is slightly lower in the solution containing I− than the solution with Cl−; the average number of water molecules in the first hydration shell is lower. Since the dielectric constants of acetonitrile and ethanol are lower than the dielectric constant of water, the solvent–halide interaction is weaker. Due to the weaker solvation shell of Cl− in acetonitrile and ethanol than in water, the Ru–Cl RDF in these solvents in Figure 4.6 has a maximum between the 2+ [Ru(bpy)3] solvation shells, a maximum that is absent in aqueous solution. The second maximum, outside the outer solvation shell, is however several times higher than the first. The SDFs in Figure 4.9 (shown for acetonitrile so- lution only) reveal that the anions access the region inside the second solvation shell only along the molecular C3 axis, which can be attributed to the bulky solvent molecules in the first solvation shell occupying the volume between

50 Figure 4.9: Spatial distribution functions of water and halide ions with re- 2+ spect to [Ru(bpy)3] in aqueous solution. The acetonitrile nitrogen distribu- 2+ tion (blue) is used to show the solvation shell of [Ru(bpy)3] . The region of − − high I (violet) and Cl (green) density along the C3 axis corresponds to the first maximum in the Ru–halide (AcCN) RDF in Figure 4.7. The high density regions above the bipyridine ligands correspond to the second RDF maximum.

2+ the ligands. In conclusion, halide ions associating with the [Ru(bpy)3] com- plex in acetonitrile and ethanol reside at spatially different sites than ions in aqueous solution. The interaction with the complex is stronger, but in order to form a solvent-shared Ru(II)–halide pair, the halide ions are limited to a relatively small solid angle. In many cases, a redox reaction involving an oxidized metal complex is one of the key reactions in the photoelectrochemical system. Electron trans- fer processes are much faster than ion transport in the solution and in order to facilitate electron transfer, the electron donating species should often reside at the reaction site. For that reason, fundamental studies of the solvent depen- dence of the interaction between the metal complex and other solvated ions at a molecular structure level are important for understanding electron transfer processes.

4.3 Electronic structure of transition metal complexes

The energetically lowest electronic excitations in a transition metal spectrum typically arise from ligand field (LF) excitations within the d orbitals on the metal center, followed by charge transfer excitations where electron density is transfered from the metal center to the ligands (MLCT), or from the ligands to the metal center (LMCT). Spectroscopic techniques, inducing electronic tran- sitions into the unoccupied valence states, give direct information of the energy and symmetry of the empty molecular orbitals and can be used for identifying

51 0.07 3d’

0.07 CO π∗

Fe 3d 0.05

1.93 Fe 3d

1.93 CO σ

1.97 CO ligand

Figure 4.10: Fe 3d orbitals of Fe(CO)5. The highest occupied orbitals of Fe(CO)5 have Fe 3d character and are occupied by 8 electrons (red box). An extra d shell in the active space (blue box) is usually needed to correct for the strong correlation of the 3d electrons. The occupation numbers of the orbitals are given to the left. different chemical species and molecular hybridization. This section treats L- edge spectra of first row transition metal complexes, where excitations from the 2p core orbitals to the partially empty 3d valence occur. Ab initio calculations reproducing core level spectra of transition metal compounds must include the necessary physics in the description of the sys- tem. The partial occupation of d orbitals is associated with strong correlation effects, and in multiconfigurational calculations of first row transition metals where the five partially occupied 3d orbitals contain more than five electrons, a large fraction of the correlation can be included by introducing an additional d shell [61]. In total, the valence orbitals included in the active space should be the ones involved in covalent bonding to the metal center [62]. The effect is particularly important for transitions where the occupation of the metal 3d orbitals changes, such as in charge transfer excitations. The occupation of the orbitals in the active space of Fe(CO)5 including the 3d orbitals and an extra set of d orbitals shown in Figure 4.10 shows that the 3d orbitals are pairwise correlated with orbitals of the same type in the additional shell, with one of the orbitals being essentially doubly occupied, the other empty. For that reason, the second shell actually comprises one of the occupied orbitals with mostly ligand character for correlation with the 3d HOMO as well as four empty d

52 orbitals for correlation with the occupied Fe 3d orbitals. The orbitals in Fig- ure 4.10 are orbitals from a state-average RASSCF calculation, obtained as the vectors diagonalizing the state-average density matrix within the active sub- space. The occupation numbers of the orbitals are the corresponding (pseudo-) eigenvalues of the density matrix, and each orbital has a maximal occupation number of 2.00. As a result of the strong spin–orbit coupling in the core, the L-edge splits into the L3 edge with the total angular momentum quantum number of the 2p core hole j = 3/2 and L2 with j = 1/2. The pure multiplet RASSCF states must hence be coupled to form 2p core hole states with j = 3/2 and j = 1/2.

4.3.1 Ni2+ in aqueous solution

This section summarizes the results in Paper V and VI. It presents L-edge XAS and RIXS calculations of hydrated Ni2+ based on a multiconfigurational RASSCF wavefunction. XAS and RIXS spectroscopy provide rich information about the electronic valence in the presence of a core hole. The coupling between the spin and angular momenta of the core hole and the partly filled d orbitals, give rise to multiplet effects in transition metal L-edge spectra. Calculations that repro- duce experimental spectra, and thus can serve as an appropriate basis for their interpretation, must handle multiplet effects and chemical interactions prop- erly. Direct comparison of our calculated spectra with experiment shows that the RAS approach is highly reliable for 2p spectroscopy of 3d complexes. Hydrated Ni2+ ions form complexes by binding six water molecules. The 2+ 8 [Ni(H2O)6] complex has a high-spin d ground state electron configura- tion and is octahedrally coordinated by the water ligands. The XA spectra in Figure 4.11 were calculated with the RAS partitioning described in Sec- tion 2.3 (Figure 2.1), and spin-free relativistic effects were treated by a scalar Douglas–Kroll Hamiltonian combined with a relativistic all-electron (ANO- RCC) VTZP basis set [63; 64]. This active space allows for core excitations leading to a [(2p)5,(3d)9] electron configuration and spin–orbit coupling effects were computed between all resulting singlet and triplet states. The large multiplet splitting of the 2p x-ray absorption edge (2p → 3d) is caused by the strong spin–orbit coupling of the 2p5 configuration, i.e. the core hole. The method reproduces the features in both edges, and the domi- nating core-level spin–orbit splitting in the 2p XA spectrum agrees well with experiment. The additional multiplets within the respective edge arise due to core–valence (2p3d) electron–electron interactions. In order to compensate for limitations in the RASSCF wavefunction, the spectrum in Figure 4.11 is shifted by -3.70 eV for comparison with experiment. A large part of the ad hoc

53 EXP RASPT2 RASSCF XA intensity

850 855 860 865 870 875 Excitation energy [eV]

Figure 4.11: L-edge spectra of hydrated Ni2+. RASSCF and RASPT2 calcu- 2+ 5 9 lated XA spectra of [Ni(H2O)6] , including all [(2p) ,(3d) ] core-excited con- figurations, are evaluated against the experimental spectrum of NiCl2(aq). correction is needed as a result of dynamic correlation effects. After treating the correlation perturbatively with RASPT2, a smaller shift of the excitation energies, -1.85 eV, could be used. In the low-energy (L3) peak, final core-excited states with the total core hole angular momentum j = 3/2 dominate, while states with 2p angular mo- mentum j = 1/2 give rise to the (L2) peak above 870 eV. Upon closer exami- nation of each edge, we find that the XA resonance at the low-binding energy side has mainly triplet character. This implies that final states with parallel 2p core hole and 3d electron spins are stabilized with respect to the singlet states (opposite spins) appearing at higher excitation energies. We can analyze the valence further by studying the states resulting from fluorescent decay of the core hole. Equation 3.5 is illustrated schematically in Figure 4.12. Each core excited state has its particular set of decay chan- nels from the intermediate state in the RIXS process to final valence excited states. The energy difference between the x-rays absorbed and emitted in the RIXS process corresponds to the energy of the final, possibly valence excited state, relative to the ground state. The calculations give explicit access to each electronic state; guided by the extracted information, we can both assign the lines in the XAS spectrum, and describe the electronic character of every final valence state resulting from RIXS at a specific absorbed photon energy. The RASPT2 spectra in panel a and b in Figure 4.12 are obtained from the same calculation as the previous XA spectra, without including ligand orbitals in the active space. The possible electron permutations in the 3d orbitals correspond 6 2 5 3 4 4 to three different configurations: (t2g) (eg) , (t2g) (eg) , and (t2g) (eg) . The peaks at zero energy loss in the RIXS map originate from resonant

54 850 855 860 865 870 875

∗ 5 Valence 2b2 a) H2O ∗ excitation 4a1 0 eg Energy Energy loss [eV] Ni 3d RAS2 loss XAS t2g b)

1b1 H2O 3a1 XA Intensity 1b2 1 850 855 860 865 870 875 H2O 2a1 c) 0 Ni 3p 15 Ni 3s -1

H2O 1a1 X-ray 10 -2 absorption Ni 2p RAS1 -3 5 Ni 2s Energy loss [eV] -4

-5 Logarithmic RIXS Intensity Ni 1s 0 -6 850 855 860 865 870 875 Excitation energy [eV]

2+ Figure 4.12: Core excitation and fluorescent decay of [Ni(H2O)6] . (a) RIXS map, with the intensity as a function of the x-ray absorption energy and the associated energy loss, and (b) the corresponding XA spectrum from RASPT2 calculation including [(2p)6,(3d)8] and [(2p)5,(3d)9] configurations. (c) Charge- transfer states are included by extending the active space.

3 elastic decay from the core-excited intermediate back to the A2g ground state. Analysis of the L3 edge RIXS shows that the XA resonance at 853 eV, which has triplet character, decays with high intensity to two peaks at 0.9 eV and 3 2.9 eV loss. The peaks originate from decay to the T2g valence excited state, 5 3 3 essentially described by the (t2g) (eg) configuration, and to T1g, respectively. These two states are formally equivalent to the final states resulting from the 3 3 3 3 optical transitions A2g → T2g and A2g → T1g in UV–Vis spectroscopy [65]. Since RIXS is a second-order process and the spin multiplicities in the valence mix in the intermediate core-excited state, final valence states that are optically spin-forbidden may also be reached. The XA peak at 856 eV has dominantly singlet character and decays therefore with high probability to singlet final states. In the RIXS spectrum in panel c, the active space has been extended, and the contribution from charge-transfer excitations arises at an energy loss above 10 eV. Here, two occupied water orbitals have been added to RAS2, thus en- abling transfer of electrons to the metal centered 3d orbitals (LMCT). A third subspace (RAS3), consisting of three unoccupied ligand orbitals, is also in- cluded. Since one electron is now allowed in RAS3, MLCT as single excita- tions to the unoccupied ligand orbitals is taken into account. Information about photochemical processes is found in the time evolution of the nuclear geometry and valence electronic structure. With this method, also XA and RIXS spectra of distorted geometries and transient electronic

55 states can be modeled, and used in the analysis of time-resolved experiments that probe changes in the electronic structure with atomic site selectivity on the femtosecond timescale.

4.4 Probing changes in the electronic structure of transi- tion metal complexes

The photochemical processes in transition metal complexes involve complex electronic and nuclear dynamics occuring on a subpicosecond timescale. In- sight into these processes at a fundamental molecular level can increase our un- derstanding of the chemical reactivity of the complexes and make it possible to model and understand photoinduced phenomena such as electron transfer in photovoltaic devices and the processes at the reaction sites in biochemical systems. New time-resolved x-ray sources, like free-electron lasers, allow us to study excited state dynamics using RIXS. However, both experimental and theoretical techniques must be investigated before addressing real problems in energy applications. The Fe(CO)5 complex has long been studied as a model photocatalyst [66; 67]. The complex has a rich reaction landscape and shows how time-resolved RIXS can be used to follow changes in the electronic structure during a reac- tion. Since Fe(CO)5 has 18 valence electrons, it is chemically inactive. After absorption of light in the visible region, a CO ligand is however removed from the the MLCT excited complex, creating the highly reactive Fe(CO)4, with only 16 valence electrons. Fe(CO)4 readily saturates the electron deficiency by binding to a ligand. It has been shown, that the gas phase Fe(CO)4 photofragment is created in a singlet state, and that further fragmentation into Fe(CO)3 is a much more probable process than subsequent triplet creation [68]. In solution, however, the reactivity of Fe(CO)4 towards the solvent may lead to a different reaction route. Triplet Fe(CO)4 has been observed in solutions. Several possible disso- ciation pathways have been proposed: Along the triplet pathway, the photoex- cited Fe(CO)5 i) relaxes to a singlet ligand field state that ii) converts to a triplet 3 and iii) dissociates into a Fe(CO)4 triplet state B2, while in the singlet path- way, Fe(CO)5 i) relaxes to a singlet ligand field state and ii) dissociates into a Fe(CO)4 singlet state. The Fe(CO)4 can then undergo an electronic transition 3 to the B2 state. In another possible scenario, Fe(CO)5 dissociates from the MLCT state without prior electronic relaxation, and forms a MLCT Fe(CO)4 3 photoproduct that then relaxes to B2 state. In order to investigate in what electronic state the Fe(CO)4 photoproduct is created and on what timescale, Fe(CO)5 in ethanol solution was pumped with

56 Fe(CO)5 Optical laser pump L-edge RIXS probe

2π∗

∗ dσ

dπ

2p

Figure 4.13: Ground state electron configuration of Fe(CO)5 and pump and probe processes. Fe(CO)5 in its initial state is pumped with an optical laser pulse of 266 nm. The system is probed with RIXS across the L3 edge at well-defined time intervals, in order to follow changes in the electronic structure.

266 nm femtosecond laser pulses to form a photoexcited MLCT state that dis- sociated into Fe(CO)4. The electronic structure of the system was probed with a RIXS pulse, scanning the incident x-ray energy over the Fe L3 edge and mea- suring the fluorescent decay at well-defined time delays after photoexcitation. The changes in the RIXS map during the experiment correspond to changes in the valence electronic structure, originating from Fe–CO bond dissociation, relaxation of excited electronic states, and solvent bonding to the undercoor- dinated Fe(CO)4. A set of RASSCF spectra, calculated for various electronic spin states and molecular geometries, was needed to interpret the changes in the RIXS map in terms of ligand dissociation/association and electronic tran- sitions. Upon CO removal from Fe(CO)5, the HOMO–LUMO gap decreases, and the lowest core-excited intermediate state—the core-excited states are denoted |mi in Figure 3.4—is shifted to lower excitation energy with respect to the ground state. The lowest Fe(CO)5 resonance is observed at 709.5 eV in Fig- ure 4.14. The calculated Fe(CO)4 spectrum shows that this first resonace is redshifted with respect to the saturated Fe(CO)5. In addition, the lowest in- elastic energy loss channel, corresponding to the lowest valence excitation en- ergy is shifted to lower energy by 4 eV. If the system is probed with RIXS, starting from an initial valence excited state, negative energy transfer is possi- ble. In the fluorescent decay to final states | f i that are lower in energy, either lower lying valence excited states or the ground state |0i, a photon with higher energy than the incident x-ray beam is then emitted. Since the excited state singlet gives rise to negative energy loss, its contributions to the RIXS spec- trum can be distinguished from the lowest singlet state with the same geometry, where the lowest possible energy loss is zero. For triplet Fe(CO)4, additional decay channels are possible with respect to the singlet initial state, and the

57 Experiment 15

Fe(CO)5 in EtOH Fe(CO)5 Fe(CO)4-EtOH 10

5

Energy loss / eV 0

705 710 715 705 710 715 705 710 715

15 15

Fe(CO)4 singlet Fe(CO)4 singlet Fe(CO)4 triplet 10 excited 10

5 5

Energy loss / eV 0 0

705 710 715 705 710 715 705 710 715 Exc. energy / eV Exc. energy / eV Exc. energy / eV

Figure 4.14: RIXS spectra of Fe(CO)5 and some potential photoproducts. The experimental spectrum of Fe(CO)5 in ethanol solution is measured across the L3 edge. The theoretical spectra are calculated using RASSCF, including spin–orbit coupling. triplet species has a broader peak in the incident energy direction. Saturation of the Fe(CO)4, by ligation with an ethanol molecule, again shifts the lowest core-excited resonance and the lowest valence excitation to higher binding en- ergy and we are not able to distinguish the contribution from Fe(CO)5 in the RIXS spectrum from the contribution from Fe(CO)4–EtOH complexes. Both the molecular geometry and the spin state affect the electronic valence levels, and hence the characteristic features in the spectrum. The differences in the calculated RIXS spectrum for different spin states and coordination are how- ever more pronounced than the differences caused by variations in the molec- ular geometry.

The excited singlet Fe(CO)4 was observed in the experimental RIXS map within the time resolution of the experiment, indicating fast dissociation along the singlet pathway. After a few hundreds of femtoseconds, features charac- teristic for the saturated carbonyl and for the triplet Fe(CO)4 appeared simul- taneously, and along with decay of the singlet Fe(CO)4 peak. These features remained constant during the entire experiment, up to 3 ps after photoexcita- tion of the Fe(CO)5 complex. Calculations of possible reaction products were essential for the interpre- tation of the time-resolved RIXS spectra. Based on the changes in the time-

58 resolved RIXS map and comparison with the set of theoretical RIXS spectra for the possible products, the reaction pathway for Fe(CO)4 in ethanol can be described as two parallel processes in which the excited singlet state Fe(CO)4 is either converted to a stable triplet state or saturated by binding a CO or ethanol molecule. Through the sensitivity to the Fe 3d character of the electronic states, femtosecond time-resolved transition metal L-edge RIXS provides rich in- sights into the complex photochemical dynamics. Aided by high-level quan- tum chemistry calculations, changes in coordination of the metal center can be resolved, and the states involved can be characterized with respect to their spin and orbital character.

59 60 5. Conclusions

In this thesis, the solvent interaction of solvated species relevant for photoelec- trochemical energy conversion applications have been studied using high level quantum chemistry and molecular dynamics simulations in combination with x-ray spectroscopy. Photoelectrochemical devices for solar energy conversion are complex systems, where the choice of molecules absorbing sunlight as well as the solvent and electrolyte composition determine the performance. X-ray spectra contain the detailed, atomic-level, knowledge of the mate- rials that is desired for tuning the properties of the building blocks to give optimal efficiency and stability of the working device. For the interpretation of the features in the experimental data, theoretical calculations is a power- ful tool, given that a reliable and sufficiently accurate computational model is used. The details of the electronic structure that become available with the de- velopment of new light sources, in particular the possibility to follow photoin- duced reactions during the process, call for more advanced electronic structure methods to aid the interpretation of the spectra. An important goal with this project is to use such high-level quantum chemistry methods for x-ray spec- trum calculations of relevant systems to investigate the method’s applicability and reliablity. The results presented in this thesis show the direct effect of the solvent on the molecular structure and energy levels, which has implications for energy applications. For example, the solvation structure around ions in solution affects ion–ion interactions and can have large influence on electron transfer processes. The interaction between the components in photoelectro- chemical systems can also be affected by solvent-induced geometry distortion effects. Many energy-related applications contain transition metal complexes. In this work, the solvent structure about the solvated prototype light-absorbing metal complex and the distribution of iodide and chloride ions in different sol- vents have been studied with molecular dynamics. The simulations showed that iodide ions interact closely with the ruthenium complex, while only an − 2+ outer-shell solvent separated complex is formed between Cl and [Ru(bpy)3] in aqueous solution due to the strong hydration of the chloride ion. This has consequences for electron transfer processes between halide ions in solution and the metal complex, and future studies can address the electrolyte compo- 2+ sition and solvent effect on the [Ru(bpy)3] electronic structure with electron

61 spectroscopic methods. − − In a study of I and I3 in solution, the short-range solute–solvent in- teractions were shown to be important for the solvation energies. Measured core-level XPS binding energy shifts in different solvents cannot be explained merely with the macroscopic dielectric constant of the solvent, since the spe- cific, microscopic, effects such as the hydrogen bonding between the solvent and the ion are neglected. Modeling changes in core level binding energies with electronic structure methods is however computationally challenging, as it may be necessary to introduce explicit solvent molecules in order to account for local effects, while the number of solvent molecules has to be sufficiently large to represent the macroscopic properties of the solvent correctly. Due to − the strong polarizability of the I3 ion, hydrogen bond interactions with the solvent significantly affect the ion geometry, which in turn has consequences for the binding energies. The information of solvation structure and dynamics from MD simulations is valuable for understanding how the combination of materials influence the electrochemical reactions. The electronic structure of transition metal complexes is usually not well described with the wavefunction expressed as a single determinant. In this work, the multiconfigurational RASSCF method has been used for calculat- ing electronic spectra. The wavefunction is expanded in a selected space of molecular orbitals, and with this approach, multiplet and molecular orbital ef- fects in the spectra are treated correctly. Hydrated Ni2+ can be treated as an 2+ octahedral [Ni(H2O6)] coordination complex with 8 electrons in the valence 3d shell, and is well suited as a test case for XAS and RIXS calculations. Even with a small active space, including only the most important orbitals for describing transition to ligand field excited states, the multiconfigurational cal- culations reproduced the splittings and intensities observed in the experimental XA spectrum. To gain insight in the bonding and structure, the ligand field states ob- served in XAS can be probed in detail with with RIXS. In particular, time- resolved RIXS provides information of photoinduced reactions as it allows for following changes in the electronic structure with high time resolution. The rich reaction landscape of the Fe(CO)5 catalyst makes the system interesting for time-resolved studies. We have investigated the solvent influence on the reaction pathway using time-resolved RIXS in combination with electronic structure calculations. A computational model that has proven accurate and reliable, has the power of predicting material properties before experiments are performed. The close collaboration between theory and experiment has been essential for the evalua- tion of the theoretical methods in this work. In summary, we have studied sys- tems relevant for energy applications at a fundamental level, combining theo-

62 retical modeling with x-ray spectroscopic techniques and the results presented in this thesis show that it is possible to address relevant issues using multi- configurational methods. Spectra of ground state geometries of both metal complexes and electrolyte ions were analyzed and, importantly, also distorted geometries and optically excited metal complexes could be modeled using the RASSCF method. This makes it possible to identify short-lived intermediate states in time-resolved x-ray spectra and thus follow photochemical processes.

63 64 Populärvetenskaplig sammanfattning

Eftersom jordytan under bara en timme tar emot solljus motsvarande världens nuvarande energiförbrukning under ett helt år, förstår man att solljus som ener- gikälla har enorm potential, även om långt ifrån hela denna gigantiska ener- giresurs är möjlig att ta tillvara. Idag utgörs en blygsam andel av världens totala energikonsumtion av solenergi och att i större utsträckning omvandla solenergin till användbar elektrisk eller kemisk energi är därför eftersträvans- värt. Den största delen av solstrålningen som träffar jordytan är synligt ljus. Elektromagnetisk strålning vid dessa våglängder växelverkar framför allt med valenselektroner i materia, det vill säga med elektroner i de yttersta elektronska- len. Dessa är de elektroner som delas av flera atomer och på så sätt skapar kemiska bindingar i molekylen. Solljus som träffar en molekyl kan växelverka med denna genom att avge energi, varvid molekylen går över till högre elektro- niskt tillstånd. När molekylen sedan går tillbaka till ett lägre energitillstånd, är det möjligt för de reaktioner som är avgörande för den önskade energiomvand- lingen att äga rum. I över 40 år har man studerat fotoelektrokemiska system som potentiella tillämpningar för att omvandla och lagra solenergi. När solljus träffar cellen sker först en kemisk reaktion och sedan genomgår fotoprodukterna ytterligare reaktioner i elektrolytlösningen som omger dem. Exempel på sådana tillämp- ningar är molekylära solceller som omvandlar solenergi till elektrisk energi och vattensplittning som genom att imitera fotosyntesen lagrar solenergin i form av kemisk energi. Den beståndsdel som absorberar solljus kan vara en molekyl på en halvledaryta som i sig inte växelverkar med solstrålningen. I många av dessa system förekommer övergångsmetallkomplex. Övergångsme- taller bildar gärna komplex genom att binda till sig ligander. Metallkomplexen har ofta klara färger, vilket är ett kännetecken på deras förmåga att absorbera synligt ljus. För att kunna utveckla system för omvandling och lagring av solenergi behövs en grundläggande förståelse av de ingående komponenterna på atomär nivå. Hur energinivåerna i de olika delarna ligger i förhållande till varandra, liksom molekylär struktur och valet av omgivande lösningsmedel och olika joner i elektrolytlösningen påverkar prestandan. Den fundamentala utvecklingen i fysik, med upptäckten av elektronen 1897, och beskrivningen av atomen som en tung, positivt laddad, kärna omgiven av lätta, negativt laddade, elektroner som måste befinna sig i vissa skal runt kär- nan, ledde till en ny vetenskap för att förstå kemisk bindning och processer. All kemi handlar i grunden om samspelet mellan dessa elektriskt laddade partiklar, som utgör byggstenarna i materia. Med hjälp av spektroskopi, där elektromag- netisk strålning får växelverka med det material som ska undersökas, kan den kemiska sammansättningen i provet och deras egenskaper undersökas i detalj. Strålningens våglängd avgör vilka elektronskal som påverkas och strålning med olika våglängder ger därför information om provet som undersöks. Rönt- genstrålning växelverkar med elektroner som befinner sig nära atomkärnorna och kan därför visa hur specifika atomer bidrar till materialets egenskaper. I princip kan vilken kemisk reaktion som helst beskrivas med hjälp av en enda grundläggande ekvation, Schrödingerekvationen. Denna är för kvantme- kaniken vad Newtons andra lag är för den klassiska fysiken och beskriver hur ett kvantmekaniskt tillstånd beter sig över tiden. För alla molekyler med mer än en elektron är dock Schrödingerekvationen omöjlig att lösa exakt. Beräknings- kemisten använder sig därför av modeller som ger ungefärliga, men tillräckligt korrekta, beskrivningar av verkligheten. De senaste årtiondenas utveckling av snabba beräkningsdatorer har gett helt nya möjligheter att tillämpa modeller- na på komplicerade kemiska system och visualisera processerna i detalj. Valet av modell blir alltid en avvägning mellan noggrannhet och den datorkraft som krävs för att åstadkomma resultat. På grund av den lätta elektronens våglika na- tur, krävs kvantmekanik för att modellera elektronstrukturen i molekyler och material. Användandet av kvantmekanik för att lösa ett kemiskt problem kallas kvantkemi. För ett komplicerat system med många atomer eller molekyler är det omöjligt att åstadkomma en fullständig kvantmekanisk beskrivning, men ofta kan atomers och molekylers struktur och dynamik simuleras tillräckligt väl med klassisk mekanik. I den här avhandlingen används avancerade kvantkemiska metoder för att beräkna röntgenspektra för molekyler som är relevanta i energitillämpningar. Dessutom simuleras effekterna från omgivande lösningsmedel med hjälp av molekyldynamiksimuleringar, där principerna från klassisk fysik används. För att tolka de experimentella resultaten, behövs teoretiska beräkningar som kan återskapa detaljerna i spektrumet. Eftersom utvecklingen av nya strålkällor lett till att spektroskopiska metoder kan fånga allt finare detaljer, är det viktigt att undersöka dessa mer avancerade metoder för att simulera spektra. Acknowledgements

Without the assistance of my two dedicated and encouraging supervisors, this thesis would not exist. Michael Odelius was the one who introduced me to the field of computational chemistry. He has given ever-patient support and has always had time to share his scientific knowledge and experience. Håkan Rensmo taught me a lot about spectroscopy and energy applications. Unwa- veringly, he has spread motivation in our projects. Thank you both! Ulf Wahlgren has made an important contribution through many valuable discussions and advice on the calculations. It is impossible to mention everybody who has participated in the various projects. I am grateful for the nice collaboration with you all. Susanna Kaufmann Eriksson at Uppsala University was a key person in our joint projects early on, and through our close teamwork for several years I got insight in the work behind the final spectra. My very first contact with x-ray spectroscopy and liquid jet experiments in Uppsala was probably what started it all, and Hans Siegbahn, Olle Björneholm, and Niklas Ottosson have been helpful with informative discussions. The numerous email conversations with Alexander Föhlisch, Philippe Wer- net, and Kristjan Kunnus at Helmholtz-Zentrum Berlin have been truly illumi- nating and essential for the exchange of ideas in a rewarding collaboration. In a more recent collaboration with Oliver Schalk and Melanie Mucke, I have learned more of interesting experiments and physics. During these years, I have really enjoyed working with the members of the QCMD group: Thomas, Naresh, Emelie, Sher, Jesper, and Aleksandra — both on solving everyday things, big and small, and in particular projects. I also have many great colleagues at Fysikum, who have shared their views on various practical matters, as well as more specific scientific input. At the final stage of the thesis process, my sister Stina has been an invalu- able help by spending many hours spotting innumerable linguistic errors and missing characters in the text. Thank you all!

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