Beyond Scattering – What More Can Be Learned from Pulsed Kev Ion Beams?

Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1945

Beyond scattering – what more can be learned from pulsed keV ion beams?

SVENJA LOHMANN

ACTA UNIVERSITATIS UPSALIENSIS ISSN 1651-6214 ISBN 978-91-513-0964-4 UPPSALA urn:nbn:se:uu:diva-409892 2020 Dissertation presented at Uppsala University to be publicly examined in Polhelmsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, Friday, 12 June 2020 at 09:15 for the degree of Doctor of Philosophy. The examination will be conducted in English. Faculty examiner: Professor Andreas Wucher (University of Duisburg-Essen, Faculty of Physics).

Abstract Lohmann, S. 2020. Beyond scattering – what more can be learned from pulsed keV ion beams? Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1945. 90 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0964-4.

Interactions of energetic ions with matter govern processes as diverse as the influence of solar wind, hadron therapy for cancer treatment and plasma-wall interactions in fusion devices, and are used for controlled manipulation of materials properties as well as analytical methods. The scattering of ions from target nuclei and electrons does not only lead to energy deposition, but can induce the emission of different secondary particles including electrons, photons, sputtered target ions and neutrals as well as nuclear reaction products. In the medium-energy regime (ion energies between several ten to a few hundred keV), ions are expected to primarily interact with valence electrons. Dynamic electronic excitations are, however, not understood in full detail, and remain an active field of experimental and theoretical research. In addition, whereas scattered ions are employed for high-resolution depth profiling in medium energy ion scattering (MEIS), research on secondary particle emission in this regime is scarce. This thesis explores possibilities to experimentally study ion-solid interactions in the medium- energy regime beyond a backscattering approach. The capability for detection of electrons, photons and sputtered ions was integrated into the time-of-flight (ToF-) MEIS set-up at Uppsala University. Additionally, transmission of ions in combination with crystalline samples was employed to study impact-parameter dependent electronic excitations. In all cases, the use of pulsed ion beams with nanosecond pulse widths proves to be imperative for achieving energy measurements with sufficient resolution as well as low doses for non-destructive interactions even with sensitive samples. Trajectory-dependent energy loss of various ions in Si(100) was studied. For all ions heavier than protons, experimental evidence shows that, if close collisions are not suppressed by channelling, consequent charge-exchange events increase the mean charge state of the ion and heavily influence the experienced energy loss. Furthermore, measurements of electron emission are presented. For medium-energy ions, electrons emitted in forward direction from carbon foils exhibit energies between 10 and 400 eV. Scaling with ion velocity indicates binary collisions as the primary energy transfer mechanism. Detected photons also have energies of a few eV, i.e. on the order of typical valence transitions in solids. For photon emission, pronounced chemical matrix effects are observed. Finally, the sputtering process at medium energies was studied. Target bulk constituents exhibit similar behaviour as known from established methods at lower energies, i.e. sputtering by nuclear collision cascades. In contrast, the desorption of surface species seems to be governed by electronic energy transfer mechanisms.

Keywords: Charge exchange, Deep UV photons, Electron emission, Silicon, Sputtering, TOF- MEIS

Svenja Lohmann, Department of Physics and Astronomy, Applied Nuclear Physics, Box 516, Uppsala University, SE-751 20 Uppsala, Sweden.

ISSN 1651-6214 ISBN 978-91-513-0964-4 urn:nbn:se:uu:diva-409892 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-409892) List of Papers

This thesis is based on the following papers, which are referred to in the text by their Roman numerals.

I. Disparate energy scaling of trajectory-dependent electronic excitations for slow protons and He ions S. Lohmann, and D. Primetzhofer. Phys. Rev. Lett., 124: 096601. 2020.

II. Trajectory-dependent electronic excitations by light and heavy ions around and below the Bohr velocity S. Lohmann, R. Holenák,ˇ and D. Primetzhofer. In manuscript form.

III. Assessing electron emission induced by pulsed ion beams: a time-of- ﬂight approach S. Lohmann, A. Niggas, V. Charnay, R. Holenák,ˇ and D. Primetzhofer. Manuscript submitted for publication.

IV. Analysis of photon emission induced by light and heavy ions in time- of-ﬂight medium energy ion scattering S. Lohmann, M. A. Sortica, V. Paneta, and D. Primetzhofer. Nucl. In- strum. Methods Phys. Res., Sect. B, 417: 75–8. 2018.

V. Ion-induced particle desorption in time-of-ﬂight medium energy ion scattering S. Lohmann, and D. Primetzhofer. Nucl. Instrum. Methods Phys. Res., Sect. B, 423: 22–26. 2018.

Reprints were made with permission from the publishers.

iii My contributions to the included papers:

Paper I I participated in planning the study, conducted all experiments and analysed the data. I interpreted the results together with my supervisor and wrote the initial manuscript.

Paper II I was involved in planning this study. I measured parts of the data and assisted with the remaining experiments. I did the analysis, interpreted the results together with the other authors and wrote the manuscript.

Paper III I was involved in planning the study and in making necessary changes to the set-up. I conducted the experiments together with co-authors. I analysed all data and interpreted them together with the other authors. I wrote the manuscript.

Paper IV I manufactured the Au samples and conducted the majority of experiments. I analysed the data, interpreted the results in discussion with the other authors and wrote the manuscript.

Paper V I was involved in planning the experiments and implemented necessary ad- justments for secondary ion detection. I performed the measurements and analysed the data. I interpreted the results together with my supervisor and wrote the manuscript.

iv Related publications with my authorship not included in this thesis:

VI. Electronic energy-loss mechanisms for H, He, and Ne in TiN M. A. Sortica, V. Paneta, B. Bruckner, S. Lohmann, M. Hans, T. Nyberg, P. Bauer and D. Primetzhofer. Phys. Rev. A, 96(3): 032703. 2017.

VII. On the Z1-dependence of electronic stopping in TiN M. A. Sortica, V. Paneta, B. Bruckner, S. Lohmann, T. Nyberg, P. Bauer, and D. Primetzhofer. Sci. Rep., 9(1): 176. 2019.

VIII. A versatile time-of-ﬂight medium-energy ion scattering setup using multiple delay-line detectors M. A. Sortica, M. K. Linnarsson, D. Wessman, S. Lohmann, and D. Primetzhofer. Nucl. Instrum. Methods Phys. Res., Sect. B, 463: 16–20. 2020.

IX. Contrast modes in a 3D ion transmission approach at keV energies R. Holenák,ˇ S. Lohmann, and D. Primetzhofer. Manuscript submitted for publication.

v My contributions to the non-included papers:

Paper VI I conducted some of the experiments, contributed to the analysis and critically revised the manuscript.

Paper VII I helped with some of the measurements and contributed to the analysis. I critically revised the manuscript.

Paper VIII I was responsible for the development of transmission experiments and for the integration of mass spectrometry and electron detection into the set-up. I was also involved in improving in-situ sample cleaning methods. I revised the manuscript.

Paper IX I was involved in planning this study and contributed the experimental data. I helped interpret the results and critically revised the manuscript.

vi Contents

List of Papers ...... iii

Abbreviations ...... x

1 Introduction ...... 1

2 Ion-solid interactions ...... 5

2.1 Binary collisions ...... 5

2.2 Scattering in the solid: channelling and blocking ...... 7

2.3 The role of electrons ...... 9

2.3.1 Screening ...... 9

2.3.2 Stopping models ...... 10

2.3.3 Charge-exchange processes ...... 13

2.4 Ion-induced emission phenomena ...... 16

2.4.1 General concepts ...... 16

2.4.2 Electron emission ...... 16

2.4.3 Photon emission ...... 19

2.4.4 Sputtering and desorption ...... 20

3 Experimental set-up and methods ...... 23

3.1 Medium energy ion scattering ...... 23

3.1.1 General set-up ...... 23

3.1.2 Detection of secondary particles ...... 26

3.2 Sample preparation ...... 28

3.3 Sample characterisation ...... 29

3.4 Data evaluation ...... 31

3.4.1 Energy determination ...... 31

3.4.2 Secondary particle yields ...... 33

vii 4 Results ...... 35

4.1 Trajectory-dependent electronic excitations by ions in Si(100) .. 35

4.1.1 Introduction ...... 35

4.1.2 Summary of results ...... 36

4.2 Measuring electron energies with a ToF set-up ...... 40

4.2.1 Introduction ...... 40

4.2.2 Summary of results ...... 41

4.3 Ion-induced photon emission ...... 44

4.3.1 Introduction ...... 44

4.3.2 Summary of results ...... 45

4.4 Secondary ion mass spectrometry with medium-energy ions ..... 49

4.4.1 Introduction ...... 49

4.4.2 Summary of results ...... 50

5 Conclusions ...... 57

6 Sammanfattning på svenska (Summary in Swedish) ...... 59

Acknowledgements ...... 61

References ...... 63

viii Abbreviations

AES Auger Electron Spectroscopy DFT Density Functional Theory EDX Energy Dispersive X-ray spectroscopy ERDA Elastic Recoil Detection Analysis ESCA Electron Spectroscopy for Chemical Analysis FWHM Full Width at Half Maximum HIM Helium Ion Microscope IBA Ion Beam Analysis IMFP Inelastic Mean Free Path LEIS Low Energy Ion Scattering MALDI Matrix-Assisted Laser Desorption/Ionisation MC Monte Carlo MCP MicroChannel Plate MEIS Medium Energy Ion Scattering OAR Open Area Ratio PDMS Plasma Desorption Mass Spectrometry PIXE Particle Induced X-ray Emission RBS Rutherford Backscattering Spectrometry ROI Region Of Interest SIMS Secondary Ion Mass Spectrometry SNMS Secondary Neutral Mass Spectrometry TD-DFT Time-Dependent Density Functional Theory ToF Time-of-Flight UHV Ultra-High Vacuum UPS Ultraviolet Photoelectron Spectroscopy UV UltraViolet XPS X-ray Photoelectron Spectroscopy ZBL Ziegler-Biersack-Littmark

This list does not include abbreviations that are names of speciﬁc hardware, software or simulation codes.

1. Introduction

Between 1908 and 1913 a series of experiments were conducted at the Univer- sity of Manchester that would revolutionise the picture of the atom. Under the direction of Ernest Rutherford, Hans Geiger and Ernest Marsden studied the passage of alpha particles through matter [1–4]. They found that a small fraction of alpha particles was scattered at angles larger than 90° - an observation that was incompatible with the prevailing model of the atom assuming a ho- mogeneous distribution of positive and negative charges. Rutherford not only famously postulated the existence of the atomic nucleus, i.e. the concentration of all positive charge carriers in a small volume in the centre of the atom, but also deduced the scattering probability and its dependence on scattering angle, atomic charge, foil thickness and projectile velocity [5]. In his deduction he assumed the scattering of point charges by the Coulomb force - undisturbed by the surrounding electrons. He, furthermore, found the probability for multiple large-angle scattering events to be vanishingly small. Whereas these findings could well reproduce Geiger’s and Marsden’s experiments, that employed alpha particles with MeV energies and thin metallic foils, they are by no means universal. We can only speculate what would have happened if the available source of penetrating radiation had much lower energies, where screening by electrons can no longer be neglected, or if the used samples had been single crystals, where impinging ions might be subject to channelling and blocking effects by the crystal lattice. The structure of the atom is now as far as possible understood, but the interaction of ions with matter still leaves some open questions. This thesis aims to contribute to this research with a focus on ions with keV energies. Whereas Geiger and Marsden were confined to take a naturally occurring energetic ion, i.e. a radioactive decay product, as their probe, the development of accelerators allowed the experimentalist to (more or less) freely chose ion species and energy spanning many orders of magnitude. First mainly built due to the interest in nuclear physics, accelerators therefore soon became a tool for studying ion-matter interactions [6]. As already seen in the Geiger-Marsden experiments, ions can scatter elastically with atomic nuclei. Additionally, they scatter inelastically with target electrons, and, as they excite and ionise atoms, they can cause the emission of photons and secondary electrons. If the ion energy is sufficiently high, nuclear reactions can be induced, which in turn lead to the ejection of ions, neutrals and gamma rays. Energetic ions can furthermore modify materials. They can be implanted, cause defects in the atomic structure, and induce the emission of sample material (sputtering). All these

1 1. Introduction ion-matter interactions are not only of interest for fundamental research but they are also the backbone of several technological applications. Examples are the treatment of cancer with protons and carbon ions [7], the use of sputtering in deposition processes [8] or of targeted implantations to modify the characteristics of semiconductors [9]. Also, ion beam based methods for materials science have been developed. Ion beam analysis (IBA) denotes a family of typically non-destructive, standard-free methods for quantitative materials characterisation on the atomic level [10]. Classical IBA mainly employs ions with MeV energies. The existence of accelerators providing ions in this energy regime in combination with relatively simple detection methods might be the main reason for this predominance. However, another mayor advance is that the energy loss of MeV ions in matter can be treated by perturbative theoretical approaches and that thus obtained results compare satisfactorily well with experimental data. IBA techniques all use ions as probes, but they differ in the type of reaction products they detect and the research questions they thus can address. The detection of scattered primary ions, recoiled target atoms, element-specific X-rays or nuclear reaction products can provide information on chemical composition. In combination with the energy loss of ions, the thickness and concentration profile of a layer can be revealed with high accuracy. The depen- dency of the scattering process on the atomic structure also allows for studying crystallinity of a solid sample [11]. The IBA methods not only complement each other in the information they can reveal about a sample of interest [12, 13] but also allow for a complete picture of the underlying ion-solid interactions - at MeV energies. In the 1980s medium energy ion scattering (MEIS) was developed as an IBA method operating at lower energies [14]. Typically, light ion beams with several ten to a few hundred keV in energy are directed towards a sample and detected after backscattering for element identification and depth profiling. Considering the seemingly always ongoing miniaturisation of electronics and the growing importance of thin film coatings, the improved depth resolution must be regarded as the real advantage of MEIS over conventional MeV methods. The increased energy loss per energy interval of keV ions compared to MeV energies leads to achievable energy resolutions of better than 4 × 10−3 [14, 15]. This value is equivalent to a depth resolution of a few Å near the surface [14, 16, 17]1, which means a significant improvement compared to equivalent methods employing MeV ions. The first MEIS system was used with a toroidal electrostatic analyser and a position-sensitive detector [14]. This approach has the disadvantage of being sensitive to the charge state, which complicates quantification, and energy of the backscattered ion resulting in time-consuming and invasive scanning procedures. These problems could be solved, however, with the development

1At larger depths the depth resolution worsens due to straggling of the ion beam [17, 18].

2 of a time-of-flight (ToF) spectrometer [19, 20]. The ToF-MEIS technique allows for the detection of scattered particles independent of their charge state and to analyse all energies simultaneously. Regardless the energy measurement method, the use of large, position-sensitive detectors has made MEIS an excellent tool for crystallographic studies right from the beginning [21–24]. Also on a more fundamental level, a closer look at the energy loss of medium-energy ions is worthwhile. In this regime, ion velocities are of the same order of magnitude as those of sample valence electrons, thus, the ion- electron interaction becomes non-adiabatic. In addition, the charge state of the projectile and the electronic structures of both projectile and sample influence the interaction [25, 26]. Established perturbative approaches therefore can no longer reliably predict the energy loss, and the development of a comprehensive theoretical model of ion-solid interactions at these velocities is much more complex. Hence, both experimental and theoretical studies are an active field of research. With the advent of time-dependent density functional theory we now have a tool available to model dynamic interaction [27], however, adequate experimental studies to serve as benchmark systems are still needed. The aim of this thesis work has been twofold. First, the potential for experimental approaches beyond the detection of backscattered ions in the medium- energy regime has been explored. While I have described the development of MEIS, methods based on the detection of other ion-solid interaction products at energies of several ten keV are in fact scarce. The development of complementary methods and possibilities to detect not only backscattered ions but also secondary species using keV ions would allow to further enhance the analytical capabilities of MEIS, thus, improving its competitiveness among ion beam-based methods, especially for near-surface analysis. Second, fundamental interactions of keV ions with solids have been studied employing experimental techniques different from backscattering. All experimental work has been done at the ToF-MEIS set-up at the Ång- ström laboratory at Uppsala University. This set-up operates with pulsed ion beams, and features a ToF approach for energy determination and a large, position-sensitive detector sensitive to a range of particles apart from energetic ions. More details are described in Chapter 3. The system’s versatil- ity proved to be an ideal starting point for the work presented in this thesis. The obtained results are divided into four main topics: (i) trajectory-selective energy loss measured by using a transmission approach combined with crystalline samples (Sect. 4.1), (ii) the assessment of ion-induced electron emission with a ToF set-up (Sect. 4.2), (iii) the analysis of photon emission in the medium-energy regime (Sect. 4.3), and (iv) the integration of secondary ion mass spectrometry into the ToF-MEIS set-up (Sect. 4.4). In Chapter 4, I put each of these topics into a broader context of previous work and literature before summarising my contributions. Most of the results are in an unabridged form described in the published papers or manuscripts that are attached to this comprehensive summary.

2. Ion-solid interactions

In this chapter, I will brieﬂy introduce established concepts forming the basis of our understanding of the interactions of ions with solid matter. This is not a textbook, and I do not aim for completeness, but I will focus on the mechanisms enabling us to interpret the experimental results presented later. This thesis focusses on the interactions of ions with keV energies. Adequate theoretical approaches can differ signiﬁcantly between velocity regimes, and I will point out these differences where relevant.

2.1 Binary collisions As a ﬁrst step it is helpful to set aside the nature of the solid and to instead consider a scattering event between two particles with masses m1 and m2 only. A sketch of such a binary collision in the laboratory frame (used throughout this thesis unless otherwise noted) is shown in Fig. 2.1. The incident particle with initial energy E0 and mass m1 approaches a stationary particle at impact parameter b. A head-on collision would correspond to b = 0. We assume these collisions to be elastic. From conservation of kinetic energy and momentum, the energy E1 of the projectile after it has been scattered by an angle θ can be calculated (for a derivation see e.g. [28]). Commonly, the ratio of ﬁnal to initial energy is written as the kinematic factor k:

E k ≡ 1 E0 q 2  2 2 2  (2.1) ± m2 − m1 sin (θ) + m1 cos(θ) =   . m1 + m2

Note that for m2 ≥ m1 only the + sign in front of the square root gives meaningful results. An analogous relation can be derived for the corresponding recoiling particle with energy E2 and recoil angle φ:

E2 krecoil ≡ E0 (2.2) 4m1m2 2 = 2 cos (φ). (m1 + m2)

5 2. Ion-solid interactions

These equations, assuming only kinetic energy and momentum conservation, already present the basic idea for several ion beam based methods for materials analysis. An ion of known mass and energy is sent onto an unknown sample. After the collision the energy of either scattered primary or recoil particle is measured in a well deﬁned geometry. The only remaining unknown m2, i.e. the mass of the target constituent acting as the scatterer, can thereby easily be determined. When the ion is detected in a backscattering geometry (θ > 90°), the corresponding method is usually called Rutherford backscattering spectrometry (RBS) for primary ion energies in the MeV regime, MEIS for energies between several ten to a few hundred keV or low energy ion scattering (LEIS) for E0 ≤ 10keV. Equation 2.2 becomes relevant for elastic recoil detection analysis (ERDA), a method which typically employs heavy ions to detect light target recoils.

m1, E1

m1, E0 � b �

m2, E2

Figure 2.1: Schematic drawing of a binary collision in the laboratory frame. A particle with mass m1 and energy E0 approaches a stationary particle with mass m2 under impact parameter b. The ﬁrst particle is scattered by the scattering angle θ and con- tinues to travel with reduced energy E1. The recoiling particle moves with energy E2 in the direction given by the recoil angle φ.

The above considerations are true for any elastic collision independent of the nature of the force leading to the deflection of the incoming particle. For atomic collisions, the simplest case is the scattering of two point charges mediated by the Coulomb force. Having, thereby, defined the interaction potential V(r), the scattering cross section can be derived (see e.g. [9]). This well- known Rutherford cross section, named after and first derived by E. Ruther- ford [5], is given in its differential form, i.e. per solid angle Ω, by

1/2 2 2 2 1 − [(m /m )sin(θ)] + cos(θ) dσ Z Z e2 1 1 2 = 1 2 · . 4 1/2 dΩ 8πε0E0 sin (θ) 2 1 − [(m1/m2)sin(θ)] (2.3)

Now assuming atomic collisions, Z1 and Z2 denote the atomic numbers of the two nuclei participating in the collision, e is the elementary charge, and ε0

6 2.2 Scattering in the solid: channelling and blocking the vacuum permittivity. While the scattering of two point charges proved to be a rather successful approximation for the description of the Geiger-Marsden experiments and the development of a theory of the atomic structure, it is of course a rather simpliﬁed assumption. To fully describe ion-solid interactions, the spatial structure of the solid and the electronic systems of both target and projectile have to be taken into account.

2.2 Scattering in the solid: channelling and blocking For ion energies relevant in this thesis, interaction lengths of atomic collisions are significantly smaller than typical interatomic distances inside a solid. As long as the nuclei in the solid of interest are distributed randomly and isotrop- ically, interactions of an ion with these can therefore be well described by a series of independent binary collisions. If the material features a long-range order, i.e. if it is crystalline, however, scattering is no longer necessarily a process involving two particles only. When an ion moves with its direction of motion closely aligned with a crystal axis, it can be deflected by a string of atoms, i.e. in a continuum potential obtained by integrating individual atomic interaction potentials [29]. This effect is called channelling, and it is schemat- ically shown in Fig. 2.2. The ion moves then on a stable trajectory that oscillates with a constant wavelength and amplitude [29]. Most importantly, the repulsive string potential confines the ion to large impact parameters, thereby, effectively preventing close collisions [30]. In backscattering experiments, the channelling effect, therefore, leads to a drastic reduction of the backscattering yield.

Z2, m2 d

E0, Z1, m1

Figure 2.2: Schema of the channelling effect. An ion with energy E0, atomic number Z1 and mass m1 is scattered by a string of atoms (each with atomic number Z2 and mass m2) that are located at distance d from each other. The ion then moves along an oscillating trajectory at large impact parameters through the channel.

Channelling demands the ion motion to be almost aligned with the crystal axis. A critical angle can be deﬁned that describes the maximum allowed deviation from perfect alignment. Lindhard derived this angle to be [29]

7 2. Ion-solid interactions

Figure 2.3: Spatial distribution of 75 keV protons transmitted through a Si(100) crystal. The blocking pattern, i.e. the nodes and lines of reduced intensity, forms a real-space image of the crystal structure. The high-intensity region in the centre is caused by ions transmitted through the crystal on rather straight trajectories, which are, thereby, not subject to the blocking effect in this geometry.

2 1/2 2Z1Z2e ψ1 = . (2.4) 4πε0E0d

The “real” critical angle will be on the order of this Lindhard angle. How- ever, its exact value depends on the chosen interaction potential as well as the contribution of thermal vibrations [31]. The structure of the crystal also has an effect on particles leaving the solid. A particle that is scattered or emitted at a lattice site is blocked by the strings and planes and cannot exit in these directions. This blocking effect is visualised in Fig. 2.3. Here, protons with a primary energy of 75 keV are transmitted through a Si(100) crystal in a geometry that features no alignment with a low-index crystal axis. Ions on straight trajectories are, therefore, not subject to blocking and form a region of high intensity in the detector centre. At larger deﬂection angles, lines and nodes of reduced intensity show where ions are blocked from exiting the crystal by planes and strings, respectively. The blocking pattern forms a real-space image of the crystalline structure. Both channelling and blocking effects can be used for crystallographic studies [22, 32].

8 2.3 The role of electrons 2.3 The role of electrons The electric field exerted by an incident ion of course also influences the electrons in the solid. The ion can excite electron-hole pairs and plasmons and thereby transfer energy. At the same time, the ion can carry bound electrons, strip off these or capture target electrons. The extent to which different ion- electron interactions need to be considered strongly depends on interaction times and distances, and thereby on the ion velocity. While a swift, bare nucleus might only perturb the sample electronic system shortly and in a nearly adiabatic manner, a slow ion might be more susceptible to the specific electronic structure of the solid and tunnelling of electrons between target and projectile states (charge exchange) becomes possible. One relevant parameter for distinguishing different velocity regimes is the relation between ion and target-electron velocities. In this picture, the use of atomic units (a.u.) is favourable, and the projectile velocity vp is often expressed as a multiple of the Bohr velocity

e2 c v0 = = , (2.5) } 137 which gives the orbital speed of the electron in a hydrogen atom in the ground state. Here, } and c are the reduced Planck constant and the speed of light, respectively. “Fast” then refers to velocities signiﬁcantly higher than v0 whereas I usually use “slow” to describe velocities around and below the Bohr velocity.

2.3.1 Screening If the distance of closest approach in a scattering event is larger than the K- shell electron radius, as it is the case for low ion velocities, the scattering potential is not determined purely by the participating nuclei, but screened by electrons. A screened potential can be expressed in the form r V = V (r)Φ , (2.6) scr C a

where VC(r) is the unscreened Coulomb potential multiplied with the screen- r ing function Φ a with the screening length a. Several theoretical descriptions for the form of the screening function as well as for the exact dependence of a on Z1 and Z2 exist. Two commonly employed potentials are the Ziegler-Biersack-Littmark (ZBL, also called universal) [33] and the Thomas- Fermi-Molière potential [34], which both exhibit the form

3 r ci · r Φ = ∑ bi exp − , (2.7) a i=1 a

9 2. Ion-solid interactions

but differ in the choice of the parameter sets bi and ci as well as a. For simulations of backscattering spectra in this thesis the ZBL potential has been employed.

2.3.2 Stopping models1 When an ion travels through matter, it continuously loses kinetic energy in interactions with target nuclei as well as electrons. The mean loss of kinetic energy per path length is called stopping power S, and it can be written as the sum of the nuclear and electronic stopping powers Sn and Se, respectively: dE S = S + S := − . (2.8) n e dx Often it is convenient to express the energy loss independently of the atomic density of the material n in the form of the stopping cross section ε. The above equation can then be written as 1 1 1 ε = S = S + S . (2.9) n n n n e Whereas nuclear stopping can be described as a sequence of elastic binary collisions, the term electronic stopping includes various mechanisms in which kinetic energy is transferred to free or bound electrons. In this thesis, experimental conditions were chosen such that the energy transfer from a medium- energy ion to electrons could be studied. First, light ions, for which electronic stopping dominates over nuclear stopping at all but the lowest ion velocities, were employed in the majority of experiments. Second, energy loss was evaluated for straight trajectories in transmission geometry, thus, avoiding close collisions with target nuclei. Third, when applicable multiple scattering in backscattering was accounted for with the help of Monte Carlo simulations. I will, therefore, focus on electronic stopping in the following. Electronic stopping depends in a non-trivial way on the ion velocity as sketched in Fig. 2.4 for the example He in Si. Even though ﬁrst theoretical descriptions of this relation are now over a hundred years old [36, 37], no complete model valid for all energies and ion-target combinations exists. As can be clearly seen in Fig. 2.4, the stopping power exhibits a distinct maximum, which is called the Bragg peak [38]. At high energies, i.e. on the right-hand side of this maximum, the ion is stripped off all its electrons (since vp v0), and the electronic stopping is approximately proportional to the in- verse energy. Experimental data is predicted well by the Bethe equation [39] and subsequent corrections. These take into account a correction to the mean

1Parts of this section are based on the corresponding part of my Licentiate thesis: S. Lohmann. Electronic excitation, luminescence and particle emission. Studying ion-induced phenomena in ToF-MEIS. 2018.

10 2.3 The role of electrons

He ® Si

Lindhard

10 & Scharff

1/2

µ E

Bethe

-1 , eV/Å , µ E x /d E d

(dE/dx)

0.1

-1 0 1 2 3 4 5 6 7

10 10 10 10 10 10 10 10 10

Ion energy, keV Figure 2.4: Stopping power as a function of incident ion energy. As an example the stopping of helium ions in silicon was extracted from SRIM [35]. Nuclear stopping (red curve) dominates only at low energies. The electronic stopping curve (black) exhibits a clear maximum, which is called the Bragg peak. Below this peak electronic stopping increases approximately linear with ion velocity as described by Lindhard and Scharff. The well-known Bethe formula (+ corrections) is valid beyond the maximum. At even higher energies (not shown) relativistic effects start to play a role. ionisation potential [40], higher order perturbation theory terms [40–43] and, eventually, relativistic effects:

! 2 2 2 2 m v2 dE 4πZ1e ne e 2 e p − = 2 · ln + corrections, (2.10) dx mevp 4πε0 I

with the electron mass me, the target electron density ne, and the mean ionisation potential I. When the ion velocity reaches the order of the electron velocities in the solid, the Bethe equation is no longer an adequate description for experimentally observed stopping. Assuming that mainly weaker bound valence electrons can be excited, the solid can be modelled by a free electron gas of constant density [44]. Using this model, Lindhard and Scharff found that the electronic stopping is approximately proportional to the ion velocity [45, 46]

Se ∝ vp. (2.11) Going beyond the ﬁrst Born approximation, Ferrell and Ritchie determined the energy loss of slow ions from scattering theory [47]. The basic interaction is, hereby, the scattering of an electron in the screened Coulomb potential of the ion. Higher-order terms are added in a Feynman diagram approach, ﬁnally, resulting in

11 2. Ion-solid interactions

Se = mevpvF neσtr (2.12) = Q(Z1,ne)vp,

with the Fermi velocity vF and the transport cross section σtr (essentially the scattering cross section dependence). Q is the so-called friction coefﬁcient. In this approach, the material properties are entirely determined by the electron density, which is in turn characterised by the density parameter (or Wigner- Seitz radius) rs

3πn 1/3 r = e . (2.13) s 4

Q and as a consequence Se can be determined from density functional theory (DFT) calculations [48, 49]. Even though this approach disregards the structure of the solid, DFT has successfully predicted the stopping of protons in several metals and semiconductors [50]. For velocities significantly lower than v0, the precise band structure of the material of interest can be expected to influence the electronic stopping. As an example, for noble metals, a deviation from velocity proportionality for slow protons was observed in several experiments [50–54]. Two velocity regimes with different slopes can be distinguished. This observation was explained by the contribution of nearly free d electrons, which can only be excited above a certain threshold velocity. In terms of Eq. 2.12 this statement means that the friction coefficient is written as a sum over two different electron densities. Corresponding DFT calculations could then reproduce the experimental findings [52, 54]. For all ions heavier than protons, DFT often underestimates the electronic energy loss at low velocities ([55, 56], Paper VI). The reason behind this dis- crepancy is that processes beyond electron-hole pair excitations such as formation of molecular orbitals [57] and charge exchange [58] also contribute to the stopping. Different charge-exchange mechanisms are further discussed in Sect. 2.3.3. Such local and dynamic energy-loss channels cannot be ade- quately modelled by a theory that assumes equilibrium conditions (DFT). A more accurate picture can be obtained by modelling the time evolution of electronic states when a charged particle moves through matter. Time-dependent density functional theory (TD-DFT) takes this approach to predict electronic energy loss [27]. The work just cited e.g. provided new insights in the threshold behaviour of energy loss in insulators. Several other ion-target combinations have been studied by TD-DFT in the past years [59–63], and compared to experimental data. However, TD-DFT simulations are typically performed in channelling geometry whereas experimental data is often only available for polycrystalline samples. More adequate benchmark systems are, therefore, required.

12 2.3 The role of electrons

The charge-state dependence of electronic stopping has been conﬁrmed by several experiments [64, 65]. Therefore, independent of the development of TD-DFT, semi-empirical models predicting the equilibrium charge state have been developed and incorporated into other theories such as the Bethe- Bloch formalism [66–69]. An important concept in this context is the effective ∗ charge Z1 of the ion, which is often expressed in the form [70]

dE dE 1/2 Z∗ = (Z )/ (Z = 1) . (2.14) 1 dx 1 dx Thus, the experimental determination of the stopping power can provide important insights into ion-solid interactions and provide benchmarks for theories. Moreover, accurate knowledge of ion stopping is needed to employ ions for cancer treatment [71] or to predict radiation damage in extreme environ- ments [72, 73] as well as ion-induced astrophysical phenomena [74]. Fur- thermore, this information can be used for targeted materials modification by sputtering, implantation or defect creation [75–77]. For ion beam analysis, understanding the deceleration of ions also has a very practical value: tools like RBS and MEIS use the energy loss of ions for depth profiling of thin films. A particle that is backscattered from a target atom at a certain depth will have a lower initial and final energy than a particle backscattered from an identical atom at the surface. Likewise a transmitted ion will reach a detector with reduced energy. If the stopping power is well known, measured energy differences can be transformed into depth information.

2.3.3 Charge-exchange processes Charge exchange is an umbrella term for a number of processes in which electrons are transferred between projectile and electronic states of the target either by tunnelling or by shifting of electronic levels. They thus alter the charge state of the projectile. Furthermore, if electron promotion occurs, it comes at a cost of projectile kinetic energy. Charge exchange therefore con- tributes to electronic stopping. As an example, a He+ ion that is neutralised when entering a solid and subsequently reionised reduces its kinetic energy by about 20 eV [78]. Charge-exchange effects discussed here can be grouped into two categories: (i) Auger processes and (ii) resonant processes, which include collision-induced processes. Auger processes are possible for many materials whenever an empty projectile state lies below the Fermi level of the solid, as it is typically the case for noble gas ions. An example for direct Auger neutralisation is shown on the right-hand side of Fig. 2.5. Hereby, an electron from the conduction band of the solid tunnels through the barrier into an empty ground-state level of the projectile. The released energy can be transferred to another conduction band electron or lead to plasmon excitations. Note that the Auger electron can

13 2. Ion-solid interactions

Vacuum level Energy W�

Collision-induced Collision-induced Auger ionisation neutralisation neutralisation r r Distance i n Figure 2.5: Examples of charge exchange processes. To the very left the target material conduction band with electronic states ﬁlled up to the Fermi energy EF is visualised by the red shaded area. To the right-hand side direct Auger neutralisation is depicted, which can happen independent of impact-parameter. Hereby, a target electron is transferred to a lower lying projectile state. The excess energy is transferred to an Auger electron if the projectile state binding energy is at least twice the material work function Wφ . When the interatomic distance decreases, i.e. in a close collision, the levels of the projectile experience a signiﬁcant shift in energy (indicated by the dotted lines) due to the electrostatic repulsion experienced in the overlap of target and projectile orbitals. At rn, the here depicted level is in resonance with the target conduction band allowing for a target electron to tunnel to an empty projectile state (collision-induced neutralisation). If the level is lifted even higher, above EF , the opposite process can happen, and an electron tunnels from the projectile to an empty conduction band state (collision-induced ionisation).

14 2.3 The role of electrons only leave the solid if the binding energy of the involved projectile state is at least twice the material work function Wφ . Other Auger processes (not shown) involve the capture of an electron into an excited state of the projectile and subsequent de-excitation (see e.g. [58] or [79] for details). Auger neutralisation is a non-local process, i.e. possible independent of the impact parameter of the ion-solid interaction. Note that the tunnelling probability decreases with distance r though. The Auger transition rate 1/τA(r) can then be described by a (simpliﬁed) exponential ansatz [80, 81]

1 = AA exp(−aAr), (2.15) τA(r)

with the characteristic Auger rate AA and the reciprocal interaction length aA. Going beyond this simple equation, Auger rates can be calculated employing a jellium model of the target surface [82, 83] or by using a more sophisticated linear combination of atomic orbitals approach, which can also account for crystallinity [84]. Collision-induced electron capture and loss can only happen at a minimum distance reached in close collisions between the projectile and target atoms. When the ion moves close enough to a target atom, the electronic orbitals of projectile and solid start to overlap. The electrostatic interaction between the levels can lead to signiﬁcant shifts in energy. In general, these level shifts depend on the ion-material combination [58]. I will, therefore, explain the promotion of electronic levels using the example of the well studied He-Al system [85]. For distances closer than ∼ 2.5Å the interaction of the Al conduction band with the He 1s-level leads to a down-shift of the latter. When the ion moves even closer, the overlap with the Al core levels leads to a strong repulsion and a signiﬁcant lift of the He 1s-level to higher energies. At distances smaller than rn (about 0.5 Å for the He-Al system [58]) the level is in resonance with the solid conduction/valence band. This level shift is illustrated in Fig. 2.5. If the bands are in resonance, electrons can tunnel from the solid to the projectile core level. This process is often referred to as collision-induced neutralisation, and shown in the centre part of Fig. 2.5. At even closer interatomic distances ri, if an occupied projectile level is located above the Fermi level of the solid, the opposite mechanism - collision-induced ionisation - can happen (shown on the left of Fig. 2.5). The ionisation threshold can experimentally be determined from LEIS experiments using initially neutral projectiles [58]. Note that for some ion-solid combinations, projectile energy levels are already in resonance with the target conduction band without a collision-induced level shift. Resonant neutralisation and ionisation events following the same principles as described can then occur. The illustration in Fig. 2.5 and the corresponding explanation in the text have been made for one-electron processes as they typically appear for He

15 2. Ion-solid interactions ions. For heavier ions with a more complex electronic structure, charge- exchange processes involving more states and electrons can be expected.

2.4 Ion-induced emission phenomena 2.4.1 General concepts The energy transfer of energetic ions to matter is typically accompanied by the emission of secondary particles. Alongside with measuring the projectile energy loss, the study of secondary particle emission can yield information on the details of ion-solid interactions. Secondary particles can also exhibit material specific characteristics. Various experimental methods have therefore been developed that use specific features of secondary particle emission for materials analysis. For an overview of relevant methods see the respective “Introductions” in Chapter 4. An experimentally often easily accessible and much studied quantity - also in this thesis - is the yield of particles Y. The yield is simply defined as

Number of emitted particles within a time t Y = . (2.16) Number of incident ions in t It is important to note that the yield refers to the number of emitted particles, which might differ signiﬁcantly from the number of particles created or released by the primary beam. Relevant concepts in this context are e.g. attenuation or overcoming the surface barrier of the solid. The study of secondary particle emission is therefore also always a study of the interactions of the very same with the solid. The yield can be assessed in its absolute form, as given by above equation, or in (double) differential form per energy and/or solid angle.

2.4.2 Electron emission Much has already been written about electronic stopping, therefore, after studying ion energy loss it might seem as the next obvious step to look at electron emission. Electron emission can be understood in a three-step model: First, ion energy transfer leads to a primary excitation of electrons. The second step consists of electron transport through the solid. Third, an electron needs to be able to overcome the solid-vacuum boundary to be emitted so that it can be detected. Primary excitation mechanisms can be further divided into two different regimes of particular interest: Kinetic emission and potential emission. Detailed reviews of both topics can be found in e.g. [86] and [79], respectively. Note that electron emission from metals and insulators differs fundamentally. I will describe key concepts of ion-induced electron emission in the following, however, limiting myself to conductors.

16 2.4 Ion-induced emission phenomena

Kinetic emission refers to processes in which kinetic energy from an ion is directly transferred to an electron in a binary collision. Statements made in Sect. 2.1 are, thus, applicable. The initial electron energy can then be calculated by setting m2 in Eq. 2.2 equal to the electron mass me. The maximum energy transfer Tmax can be achieved in head-on collisions and yields

4me Tmax ≈ Eion, (2.17) mion with the ion mass mion and the ion energy at the time of the collision Eion. Neglecting binding energies, transport and passage over the surface barrier, electron energies can, therefore, be expected to scale linearly with projectile energy. However, in a more realistic picture, taking into account the material work function, kinetic emission exhibits a threshold2. For conducting materials, this behaviour can be understood by evoking the picture of a shifted Fermi sphere [88] in momentum space as shown in Fig. 2.6. In a binary head-on collision with an ion, a momentum of 2mevp is transferred to the electron as indicated by the shift of the Fermi sphere (grey to red in the figure). Only if the projectile velocity is large enough that at least some of the resulting momenta extend over the dashed circle defined by the Fermi energy EF and the material work function, electron emission can happen. Since the momentum transfer in ion beam direction is highest, these electron also have the highest probability to be able to leave the solid. Kinetic electron emission, therefore, peaks in forward direction. The term potential emission compiles all processes in which potential energy of an impinging ion is transferred to electronic excitations leading to electron emission. Potential emission is strongly connected to charge-exchange processes (see Sect. 2.3.3). The above described Auger processes are e.g. a source of potential electron emission if the available energy is sufficient in comparison to the material work function. Also, resonant processes have been identified as an important precursor for electron emission since they can lead to singly or multiply excited ions [80]. In this context, autoionisation, i.e. the intra-atomic Auger de-excitation of a multiply excited projectile [89], is another widespread mechanism for potential emission [90]. Independent of the primary excitation mechanism, a secondary electron created inside the solid needs to first travel towards the surface before it can be emitted and subsequently detected. On its way, the electron will lose energy in inelastic collisions with other electrons, and it will change direction by elastically scattering from target nuclei. If the initial secondary electron is sufficiently energetic, the former process can result in a cascade of tertiary electrons that in turn can travel towards the surface and be emitted - if they

2Note that sub-threshold kinetic emission has been observed for heavier noble gas atoms under grazing-incidence conditions [87]. To explain this behaviour a more complex description of the local electron momentum distribution at the surface is needed, which goes beyond the scope of this thesis.

17 2. Ion-solid interactions

1/2 |k| = (2me(EF+W�))

k||

|k| = kF 2mevp

Figure 2.6: Visualisation of the threshold behaviour of kinetic electron emission by the shifted Fermi sphere model. Initially, electron momenta (with a component parallel to the ion velocity k||, and transverse component kt) are distributed in the grey Fermi sphere with radius equal to the Fermi momentum kF . In a binary head-on collision with an ion with velocity vp, the Fermi sphere is shifted by 2mevp (red sphere). Electrons with momenta large enough to also overcome the material work function Wφ can leave the solid (indicated by the dashed circle). are energetic enough3. Both inelastic and elastic scattering lead to a loss of information both directional and about the initial energy of the electron distribution. The detected electron spectrum might, therefore, yield only indirect information on primary excitation events. The important length scales for electron transport are the inelastic mean free path (IMFP), i.e. the average distance between successive inelastic scattering events, and correspondingly the elastic mean free path. Both these variables strongly depend on electron energy [91]. The theoretical description of electron transport in solids is a ﬁeld of extensive study in its own [92–95]. In a simpliﬁed picture, however, the probability P that an electron reaches a certain depth x is attenuated exponentially

x P(x) ∝ exp − , (2.18) λ with the attenuation length λ. Historically, it was believed that λ ≈ IMFP [94] neglecting, however, the inﬂuence of elastic scattering events. This attenuation relation, together with low IMFPs for electron energies relevant in this thesis, results in any case in the surface sensitivity of electron detection methods. In general, the information depth from electron emission is signiﬁcantly smaller than the depth probed by medium-energy ion beams.

3Note that in literature the electrons I call here “tertiary” are often also called secondary electrons.

18 2.4 Ion-induced emission phenomena

2.4.3 Photon emission4 In previous sections I have already explained how energetic ions can excite or ionise atoms both by electron-hole pair creation and by charge-exchange processes. In the last section de-excitation via the emission of Auger electrons was described. A competing de-excitation channel is photon emission. Figure 2.7 illustrates on the left-hand side the creation of an inner-shell vacancy. This vacancy is ﬁlled by an electron from an outer shell during de-excitation. The excess energy ∆E is usually either radiated in the form of a photon with energy hν = ∆E (shown here) or transferred to an Auger electron as explained above.

�E h��E

passing ion

Figure 2.7: Principle of ion-induced photon emission. An incident ion transfers energy to an electron, which is either promoted to the vacuum level (ionisation) or a higher energetic shell (excitation). The electron vacancy is subsequently ﬁlled by an electron from an outer shell, and the energy difference ∆E is emitted in the form of a photon with energy hν = ∆E.

The transitions and, thus, the photon energies are unique for each element. However, when the atom is not isolated, the formation of a chemical bond shifts the energy levels of the participating outer valence electrons. The inner core shells, however, hardly shift, and by probing these levels characteristic X- rays are emitted that can be used for element identiﬁcation. Photons emitted in valence transitions, which lie in the ultraviolet (UV) region, on the other hand, can yield information on chemical bonds. The intensity I of emitted photons in a solid is attenuated according to the Lambert-Beer law [96]

I(x) = I0 exp(−µx), (2.19)

with the initial intensity I0 and the linear attenuation coefﬁcient µ, which is composed of different, energy-dependent light-matter interaction cross sections.

4This section is largely based on the corresponding part of my Licentiate thesis: S. Lohmann. Electronic excitation, luminescence and particle emission. Studying ion-induced phenomena in ToF-MEIS. 2018.

19 2. Ion-solid interactions

2.4.4 Sputtering and desorption5 Sputtering denotes the process in which particles are removed from the surface of a material by ion bombardment. Two distinct sputtering regimes governed by different underlying sputtering mechanism can be identiﬁed. Nuclear sputtering means particle emission as a result of elastic collisions between nuclei [97]. Electronic sputtering or desorption describes processes in which energy deposited into the electronic system of a target leads to the emission of surface species [98]. I will here follow R. Johnson and B. Sundqvist [98] and use these terms interchangeably by the deﬁnition given above but noting that their usage in literature is not unambiguous. The term “sputtered particles” will refer to all particles emitted from the target, no matter the exact emission process.

Nuclear sputtering Nuclear sputtering can be further classified into three regimes [97]: single knock-on sputtering, sputtering by collision cascades and the spike regime. In the first one of these the incident ion transfers sufficient energy to a target atom in an elastic collision for the latter to leave its lattice position. If it is energetic enough to overcome the surface binding energy, it might eventually be emitted from the target. If more energy is transferred to the recoil, it can through further elastic collisions trigger a cascade of recoils, of which some might be ejected through the surface. This collision cascade is called linear if the density of the recoils is low enough that collisions between recoils and target atoms at rest dominate over recoil-recoil collisions. In the spike regime the recoil density is very high and the majority of atoms within a certain volume (called the spike volume) will be displaced from their initial lattice positions. In order to quantify the sputtering process, often the so-called sputter yield is used. Note that sputter yield values reported in literature are sometimes given for the number of emitted ions of a species [99], which might differ significantly from the total number of emitted particles. Analogous to Eq. 2.16, we can write the sputter yield for a species A as

No. of sputtered particles (or ions) A within a time t Y(A) = . (2.20) No. of primary ions impinging on the sample surface in t The sputter yield depends on a number of variables such as target material, incident ion species, ion ﬂuence, beam energy, and incidence angle [6, 100]. Most importantly, the sputter yield is essentially proportional to the nuclear stopping power [101]. Since channelling reduces the probability for close nuclear collisions, alignment of the sputtering beam with a crystal axis leads to signiﬁcantly lower sputtering yields [102].

5This section is partly based on the corresponding part of my Licentiate thesis: S. Lohmann. Electronic excitation, luminescence and particle emission. Studying ion-induced phenomena in ToF-MEIS. 2018.

20 2.4 Ion-induced emission phenomena

Another central characteristic of sputtered particles is their energy distribution. The spectrum of atoms emitted as the result of a collision cascade exhibits a maximum in the range of the surface binding energy and a tail de- clining with E−2 towards the high-energy side [103].

Electronic sputtering Like nuclear sputtering, electronic sputtering can occur both in a low- and in a high-excitation density regime. Low-excitation density means that the excitations produced by the incoming ion along its trajectory are spatially separated [98]. Electronic sputtering in this regime is understood as the consequence of an electron being excited into a non-bonding or an antibonding orbital [104–106]. Relaxation can then lead to dissociation. If this process occurs close enough to the surface of the solid, surface species can desorb. Both atomic and molecular species can leave the surface as either neutrals or ions. As explained in previous sections, relaxation causes electron and photon emission, which therefore commonly accompanies electronic sputtering [98]. Note that also Auger processes have been found to contribute to the initial electron excitation [107, 108]. High density excitations are, typically, caused by heavy ions in an energy regime in which electronic stopping dominates. Projectiles have thus energies of at least 1 MeVu−1. The electronic sputtering process is then described by the inelastic thermal spike model [109–111]. The ion energy is initially transferred by the creation of electron-hole pairs, and it subsequently diffuses by electron transport. Via electron-phonon coupling energy is ﬁnally transferred to the atomic lattice, which can lead to melting, track formation and sublima- tion of material [112]. The latter process is called electronic sputtering. Note that although Sn is small compared to Se, the effectivity of the nuclear sputtering process might lead to contributions of nuclear sputtering to total sputtering yields even in this regime [113]. The yield for electronically sputtered particles can be deﬁned in the same way as written in Eq. 2.20. However, even though a dependence on the electronic stopping exists, it cannot be formulated in such a general way as in the nuclear case. Experiments measuring the yield of small electronically sputtered molecules have found linear, quadratic and cubic dependencies on the electronic stopping power at low excitation densities [114]. In the high-density regime the response of the material is largely dependent on the strength of the electron-phonon coupling [112].

3. Experimental set-up and methods1

The experimental results presented in this work were primarily obtained using the ToF-MEIS set-up at the Ångström laboratory at Uppsala University. Therefore, the focus of this chapter lies on a presentation of the same. I will outline the main features of the set-up including the ion source, beamline and scattering chamber. A detailed description of the MEIS beamline can also be found in [24]. A large part of the work forming the basis of this thesis comprised of developing and performing experiments beyond a standard backscattering approach. I will, thus, especially point out the aspects relevant for transmission experiments, and the detection of secondary particles. Resulting changes to the set-up were also published as part of Paper VIII. Additional experimental methods were used for sample preparation and characterisation, and are brieﬂy presented in the second part of this chapter. Subsequently, I will explain relevant data evaluation procedures.

3.1 Medium energy ion scattering 3.1.1 General set-up At the Ångström laboratory at Uppsala university, beams of keV ions are provided by a 350 kV accelerator platform. The platform is based on the Danfysik ion implanter 1090 model. Positive ions are produced by a Model 921A high- current ion source, which is based on the CHORDIS (Cold or HOt Reﬂex Dis- charge Ion Source) originally developed at GSI Darmstadt, Germany [115]. Three different ion source modes (gas, oven and sputter) allow for beams of almost all elements, including molecular beams, to be produced, and beam currents can reach 40 mA [116]. The extraction voltage of the source is set to 20 kV, which at the same time deﬁnes the minimum kinetic energy of singly charged ions. Following the ion source, a 90° magnet is located, which mass analyses the extracted beam with a mass resolution of m/∆m = 150 to 250 [116]. Subse- quently, the ions are post-accelerated to the desired energy (maximum 350 keV for singly charged ions), and focussed by a quadrupole triplet. With a switch

1This chapter is loosely based on the corresponding chapter of my Licentiate thesis: S. Lohmann. Electronic excitation, luminescence and particle emission. Studying ion- induced phenomena in ToF-MEIS. 2018. An exception are all parts concerning transmission experiments and electron detection, which have only been implemented later.

23 3. Experimental set-up and methods magnet the beam is steered into one of three beamlines leading to an ion implantation platform, the ToF-MEIS set-up and a chamber for low-energy IBA experiments. Only the central MEIS beamline has been used in this thesis, and is described in the following. To use the ToF technique, the incident beam has to be pulsed. The main objective to be achieved in the beamline is, thus, to chop the continuous beam coming from the implanter into short pulses and to focus the beam. The electrostatic chopper consists of two sets of parallel plates. The horizontal plates form the capacitance in a resonant circuit driven by a 4 MHz sinus. The vertical plates receive a gating pulse from a pulse generator, and the repetition rate of these gating pulses can be adjusted between 1/32 MHz and 1 MHz. Two sets of horizontal and vertical slits frame the chopper. With help of the entrance slits before the chopper the beam size can be reduced, typically to below (1 × 1) mm2. The separation of the exit slits deﬁnes the distance over which the beam is scanned. These two quantities together with the scanning frequency and the amplitude of the sinus deﬁne the pulse width of the chopped beam. Typically, pulse widths between 1 ns and 2 ns are achieved. To decrease the pulse width even further (down to 0.3 ns), a drift tube buncher, which is installed further down the beamline, can be employed. For experiments presented here, however, it has not been used. Focussing of the beam is achieved with the help of an Einzel lens located in front of the entrance slits and an electrostatic quadrupole triplet following the buncher. The described pulsing and focussing procedure leads to typical ion doses on the sample of 1011 cm−2, thereby, making ToF-MEIS a non-destructive technique. To prevent neutral particles from entering the experimental chamber, the beamline features a 7° bend around 0.9 m before the chamber entrance. The charged particle beam is steered electrostatically through this part. The beamline is pumped by turbo molecular pumps to a vacuum on the order of 10−7 mbar, and it is separated from the following chamber by a tube with low cross section to reduce conductance. Thereby, an ultra-high vacuum (UHV) environment in the scattering chamber can be maintained. The chamber is pumped by two turbo molecular pumps (one turbo and one ion pump until recently), and the base pressure is typically found to be below 1 × 10−8 mbar. Figure 3.1 illustrates the experimental set-up including the possible scattering geometries within the chamber. In the centre of the chamber, the sample holder is mounted on a 6-axis goniometer from Panmure allowing for three translational and three rotational movements (only the rotation around the y- axis is drawn into Fig. 3.1)[117]. As a consequence, the incident angle measured between the sample surface normal and the incoming beam can also be changed. The goniometer is furthermore equipped with an electron bombardment heater system for in-situ thermal annealing. Samples can be annealed from room temperature up to 600 °C. Note that self-supporting samples employed in transmission studies cannot be heated at the moment because they

24 3.1 Medium energy ion scattering have to be located below the goniometer. Further details and applications can be found in Paper VIII. The set-up features two detectors. The ﬁrst one can be rotated freely around the chamber centre on a circular path with radius rdet = 286mm allowing for experiments both in transmission and backscattering geometry (maximum backscattering angle is 160°). The second one is stationary (scattering angle 135°), and located at larger distance from the sample for enhanced energy resolution. Only the ﬁrst one has been used in this work though, and is described more in detail below.

rotatable MCP detector

transmitted ions scattering angle θ grid rdet rdet

backscattered ions �

Vsample Vgrid V incident pulsed ion beam sample MCP

Figure 3.1: Sketch of the set-up inside the MEIS scattering chamber. The position- sensitive detector from RoentDek consists of two MCPs and two delay lines. It can be rotated around the scattering point on a circular path with radius rdet = 286mm, thus, allowing for measurements under various scattering angles θ in back- and forward- scattering (in grey) and transmission geometry (in colour). The values of the ad- justable potentials shown in the ﬁgure depend on the type of particles that should be assessed. For measurements with an electric ﬁeld applied between the sample holder and the grid, which is mounted in front of the detector, it is favourable to turn the sample surface parallel to the detector (rotation around y-axis of the goniometer as shown). Note that the goniometer itself and its other movements are not depicted.

The employed detector is a DLD120 from RoentDek [118, 119], which consists of two microchannel plates (MCPs) stacked in Chevron conﬁguration and two delay-line anodes for position determination in x- and y-direction. With an MCP diameter of 120 mm the detector covers a solid angle of 0.13 sr. The employed MCP has an open area ratio (OAR) of ∼ 60%, which diminishes the area that actually detects particles. To provide a ﬁeld free region between goniometer and detector, a nickel grid with 90% transmittance is mounted in front of the detector. The energy of charged and neutral particles is determined via a ToF detection system. The time difference between the chopper gating pulse and the signal from a particle hitting the MCP serves as the input for the

25 3. Experimental set-up and methods time-to-digital converter. The actual ﬂight time between the sample and the detector has to be determined via the prompt photon peak (see Sect. 3.1.2). Experiments in transmission geometry can, generally spoken, be performed in the same way as those in more conventional backscattering geometry. How- ever, due to the low probability of large-angle scattering when traversing a nanometre thin sample, almost all incident particles will also reach the detector. Therefore, the primary beam current has to be reduced signiﬁcantly to a few fA only.

3.1.2 Detection of secondary particles MCPs are, in contrast to for example electrostatic detectors, sensitive to energetic ions, neutral particles, electrons, UV rays as well as hard and soft X-rays [120]. This characteristic has not only the advantage that the ion fraction of backscattered or transmitted primary particles does not need to be known [121, 122] but also allows for the detection of secondary particles. Photons can be seen in every backscattering experiment conducted with the Uppsala set-up. Since photon emission is prompt within the time resolution of the system, and the travelling time of photons between sample and detector can easily be calculated (a flight path of ∼0.3 m over the velocity of light results in a flight time of 1 ns), the photon peak position is also used to determine when the primary beam reaches the sample [24]. The sensitivity of MCPs to photons depends on the photon energy, which is outlined further in Paper IV. Note that the ToF- technique does not allow for a direct measurement of the photon energy. With the MCP detector photon counts can be analysed, but spectroscopy cannot be performed. The MCP detector can be operated in two different ways. Ions and neutrals with energies above a few keV, like backscattered and transmitted primary particles, can be recorded equally well in both modes. For secondary particles with low kinetic energy, however, a suitable biasing of the front MCP has to be chosen to enable detection. To measure positively charged ions VMCP < −2kV. Note that VMCP here refers to the front MCP bias. The back MCP is always set to VMCP +Va, where Va is the internal electron amplification potential difference set to > 2kV. In order to assess negative particles (electrons and negative sputtered ions), the detector is instead operated in electron- mode by setting VMCP = 200V. It is important to note that neutral atoms and molecules with low kinetic energy cannot be detected in either of the described situations. Sputtered ions have such low initial kinetic energies that they need to be accelerated in order to reach the detector within the detection time window. To that purpose a bias Vsample between −500 V and 500 V can be applied to the sample holder. In order to ensure a defined geometry of the electric field, the sample and detector surfaces must be parallel to each other. For further im-

26 3.1 Medium energy ion scattering

Mass to charge ratio

1 2 3 12 20 30 40 50 60 80 100

100 keV He VN, V = 500 V 10

sample

Desorbed

+ + +

H , H Sputtered V

3 Counts

10 Photons Backscattered He Backscattered

0 2000 4000 6000 8000

Time-of-flight, ns

Figure 3.2: Example for a ToF spectrum recorded with VMCP = −2.4kV and an electric field applied between sample and detector (Vsample = 500V, Vgrid = 0V). 100 keV He ions served as projectiles and the target was a VN film. At ToF = 1ns the narrow photon peak is visible followed by the broad spectrum of primary particles backscattered from the target. On top of the low-energy tail of the backscattering spectrum + + peaks of desorbed H and H2 are visible. At longer flight times other sputtered species can be observed; V+ sputtered from the matrix is identified as an example. The calculated mass to charge ratio of sputtered ions is additionally shown on the top axis (for details see Sect. 4.4).

provements of the field homogeneity, an additional voltage Vgrid can be applied to the grid. By applying a positive voltage to the sample holder, backscattered particles, positive sputtered ions and photons can be measured at the same time (note that all studies on sputtered ions in MEIS have been performed in backscattering geometry). An example for a ToF spectrum recorded in this mode is shown in Fig. 3.2. The prompt photon peak is visible at ToF = 1ns followed by a broader spectrum of primary He backscattered from the VN film target. All other peaks originate from sputtered positive ions. Their mass to charge ratio is shown on the top axis (for details see Sect. 4.4). H+ and + + H2 are identified as examples for desorbed surface contaminants, and V as a sputtered matrix species. Secondary electron emission can and has been studied both in backscattering and transmission geometry [123]. Only the latter allows a direct corre- lation between a specific impinging ion and consequently ejected electrons, however. Kinetic emission also exhibits an angular dependence. In our set-up, transmission geometry features a more favourable azimuthal symmetry. For these reasons all results presented in Manuscript III were obtained in transmission experiments.

27 3. Experimental set-up and methods

Electrons emitted upon the impact of keV ions have low kinetic energies, and are, therefore, easily deflected by electromagnetic fields. Initial tests showed that positioning transmission samples directly underneath the goniometer leads to a majority of secondary electron trajectories ending in the grounded goniometer when applying a sample bias. The sample holder was, therefore, modified in a way that samples are positioned around 60 mm behind the goniometer front side. In addition, an aluminium cone with an opening angle of ∼ 45° was added to the holder to achieve a uniform potential surface at the electron exit point especially for a biased sample holder (see Fig. 1 in Manuscript III for a sketch of the geometry). The effects of these sample holder modifications were also verified with help of the SIMION software [124]. Even with the cone in place, the employed experimental chamber provides no shielding against external magnetic fields. The earth magnetic field is, however, likely to deflect electrons of such low energy, which has to be taken into account during data analysis. This influence is in detail discussed in Manuscript III. Despite their low kinetic energy, secondary electrons have a high velocity even compared with primary ions due to the low electron mass. Applying an accelerating electric field between sample and detector is, therefore, no prerequisite for detection. A negative sample bias can, on the other hand, lead to straighter trajectories towards the detector and, thereby, higher detected electron yields (cf. Manuscript III). Figure 3.3a shows a ToF spectrum measured in transmission geometry, and + with VMCP = 200V. 150 keV Ne ions served as projectiles, and the sample was a 25 nm thin self-supporting C foil. The black and red line represents a measurements with no applied field between sample and detector and Vsample = −330V, respectively. Visible are emitted electrons without (1A) and with acceleration (1B), primary ions transmitted through pinholes in the foil (2), and the sample itself (3). Figure 3.3b visualises the spatial distributions of electrons on the detector and how it changes with an applied field. Black points show the initial intensity distribution of electrons, i.e. the black shaded area in Fig. 3.3a. Applying a sample bias has a focussing effect, which is demonstrated by the yellow/red intensity distribution.

3.2 Sample preparation Experimental results presented in this thesis have been obtained from different samples. Self-supporting foils have been used to study trajectory-dependent energy loss as well as electron emission in a transmission approach. Photon emission and sputtered particles have been assessed in backscattering geometry employing thin ﬁlms on substrate as well as bulk samples. Single-crystalline Si(100) foils used for the experiments presented in Pa- per I were purchased from Norcada [125]. Electron emission from C (pur-

28 3.3 Sample characterisation

1.4 a 1B b No applied field

V = -330 V

sample 50

1.2

1.0 40

0.8

30 , mm y ,

0.6

20 Norm. counts Norm.

0.4

0.2 1A

0.0 0

0 50 100 150 200 250 0 10 20 30 40 50 60

x, mm Time-of-flight, ns Figure 3.3: a: Time-of-flight spectra recorded for 150 keV Ne+ ions and a C target in electron mode. The black (red) line shows data without accelerating field (for Vsample = −330V). Visible are secondary electrons (1A and 1B), and ions transmitted both through pinholes (2) and through the C sample (3). b: Spatial distributions of electrons on the detector. Black points correspond to the measurement without applied field (black shaded area in a). Yellow/red points show the focussing effect of an applied sample bias on the electron intensity distribution (red shaded area in a). chased from Micromatter [126]) and Au foils was studied in Manuscript III. Note that these samples have to be floated on water and then transferred to a sample holder, where they stick upon drying. They consequently form a self-supporting target over an opening in the holder. Employed TiN thin films were deposited on Si(100) wafers by cathodic arc evaporation using an Oerlikon Balzers INGENIA P3e industrial batch coating system. Details can be found in Paper VI. The Au thin films used to study photon emission were manufactured by magnetron sputter deposition using a MED 010 mini thin film deposition set-up from Balzers. Argon was used as the sputter gas. The base pressure in the vacuum chamber was found below 5 × 10−5 mbar, and the argon pressure during sputtering was 5 × 10−3 mbar. Si(100) and glassy C were used as substrate materials.

3.3 Sample characterisation The areal density and purity of all samples (except for those employed in studies on secondary electrons) were determined with the help of RBS and time-of-ﬂight elastic recoil detection analysis (ToF-ERDA). Experiments were performed at the Tandem laboratory at Uppsala University, where a 5 MV 15SDH-2 tandem accelerator from National Electrostatic Corporation is employed for ion beam analysis. For all RBS measurements, a beam of 2 MeV He+ ions was used. Inside the RBS scattering chamber samples are mounted on a rotatable sample holder

29 3. Experimental set-up and methods

1600 12000

+ +

a 2 MeV He 173 Å Au/Si b 120 keV He 173 Å Au/Si

1400

10000

1200

8000

1000

Experiment

SIMNRA simulation

800 6000 TRBS simulation

Counts 600 Counts

4000

400

2000

200

0 0

750 1000 1250 1500 1750 2000 60 70 80 90 100 110 120

Detected energy, keV Detected energy, keV Figure 3.4: a: RBS spectrum of 2 MeV He+ scattered from a thin gold film on a Si substrate under a scattering angle of 170°. The experimental data (black open circles) is simulated with SIMNRA (blue full line) to determine the film thickness. b: Time-to-energy converted MEIS spectrum of the same sample. The experimental data (black open circles) was obtained using 120 keV He ions as projectiles and detecting backscattered particles under an angle of 135°. Also shown is a Monte Carlo simulation of the experiment using TRBS (red full line). wheel. Backscattered ions are detected at a scattering angle of 170° with a pas- sivated implanted planar silicon detector. Channelling effects can be avoided by setting the azimuth angle of the sample wheel 6= 0 and additionally performing small rotations around the set value during the course of the measurement with the help of the acquisition software. An example of an RBS spectrum of a thin gold film on silicon substrate is shown in Fig. 3.4a. In ERDA heavy ions are employed as probes, and recoiled target atoms are detected in a forward direction. Like in RBS and MEIS, the mass of the recoil can be determined via energy and momentum conservation in a known geometry (cf. Eq. 2.2). In ToF-ERDA energy and flight time are measured in coincidence to obtain the mass of the recoiled particles. Due to this coincidence technique, light elements can be separated from a heavy-element matrix. In contrast to RBS, even hydrogen can be quantified. Here, ToF-ERDA was employed to test the samples for impurities and to verify, if applicable, the stoichiometry. 36 MeV I8+ ions were used as probes. The beam impinges on the sample under an incident angle (measured to the sample surface normal) of 67.5°. The detection system is likewise positioned at an exit angle of 67.5°, thus, leading to a recoil angle of 45°. Two different ToF-ERDA set-ups were used for the measurements in this thesis. In both of them, the flight time is measured with the help of a pair of carbon foil detectors [127, 128]. The energy of particles is either determined with a silicon p-i-n detector [128] or a segmented gas ionisation chamber [129]. Hereby, the latter is less sensitive to radiation damage and, thus, preferred for the analysis of high-Z materials. Figure 3.5 shows a ToF-ERDA spectrum recorded for a self-supporting Si(100) sample. In the coincidence spectrum curves of equal mass are visible that can be identified with the help

30 3.4 Data evaluation

H C N O Si

Figure 3.5: ToF-ERDA spectrum of a self-supporting, 200 nm thick Si(100) foil. A 36 MeV I8+ probing beam was used, and energy and ToF of recoils were measured in coincidence. Besides the Si from the foil, H, C, N and O signals are visible. The gaps in these curves indicate though that these contaminations are primarily present on both surfaces of the sample. of reference samples. Here, besides the Si from the foil, signals from H, C, N and O can be separated from each other. The gaps in the curves of the latter elements imply that these are contaminations only present on both surfaces of the foil. Secondary electrons are only detected from near-surface regions of the sample (see Manuscript III for details). By exciting and detecting Auger electrons, information on the chemical composition of the near-surface region of a sample can be gained. Samples used in the study on electron emission were, therefore, characterised with Auger electron spectroscopy (AES). For these experiments, the AES set-up in the target preparation chamber attached to the Uppsala ToF-LEIS system was used [130]. Electrons with an energy of 3 keV were employed as the primary, exiting beam, and the Auger electron spectrum was recorded by scanning the pass energy of a cylindrical mirror analyser.

3.4 Data evaluation 3.4.1 Energy determination

The basic principle of ToF-MEIS implies that the kinetic energy Ekin of primary as well as secondary particles (except for photons) is determined via measuring the ﬂight time over a known distance dToF.

1 E = mv2 kin 2 (3.1) 1 d 2 = m ToF , 2 ToF

31 3. Experimental set-up and methods

where m and v are the mass and the velocity of the particle of interest. By obeying particle conservation N (Ekin)dEkin = N(ToF)dt, the energy spectrum N (Ekin) can then be calculated from the ToF spectrum N(ToF) to

ToF N (Ekin) = N(ToF) . (3.2) 2Ekin

This conversion is usually performed with the help of the RoentDek COBOLD software [119]. The large area of the employed detector causes two difficulties that need to be considered during evaluation. First, the flight paths of particles hitting the detector at different positions differ from each other. To correct for this difference, a geometry correction is applied [24]. Second, different positions (within the horizontal plane) at the detector cover different scattering angles, which means that the kinematic factors that are assigned to detected particles are not equal (cf. Eq. 2.1). This issue is ad- dressed in different ways depending on the specific particle of interest. When evaluating ion backscattering spectra an angular range limited by ±θcut around the scattering angle corresponding to the detector centre is chosen to avoid significant differences in k. Typically, θcut is set to 2° or 3°. All particles arriving within the projection of this acceptance angle on the detector are used for the evaluation. Since the focus of ion transmission studies presented here lies mainly on trajectory-dependent processes, only small regions on the detector (typically spanning scattering angles < 1°) are evaluated anyway. Differences in k within these selected regions of interest are negligible. The energy loss of ions ∆E is simply defined as the difference between the initial and the final ion energy:

∆E = E0 − E1, (3.3)

where the initial beam energy E0 is chosen at the high-voltage platform and E1 is determined via Eq. 3.1. In transmission experiments, and when evaluating straight trajectories, where nuclear energy losses are negligible, the electronic stopping power can be evaluated as

∆E S = (3.4) e ∆x

given that ∆E is small compared to E0. ∆x is in this case given by the thickness of the self-supporting sample. The analysis of electronic stopping in backscattering geometry lies not in the scope of this thesis. Ion backscattering spectra were only used to quantify particle yields, which is explained in the following.

32 3.4 Data evaluation

3.4.2 Secondary particle yields In order to quantify yields of secondary particles and to compare different measurements, the number of incident primary ions needs to be known. In backscattering experiments, the current of the pulsed ion beam reaching the sample is typically only of the order of a few pA. In addition, the emission of secondary electrons is non-negligible at these ion energies. Application of a simple suppression voltage to the sample holder may generate leakage currents on the order of the primary beam current, which makes it difficult to perform an accurate measurement of the particle fluence. Therefore, experiments are normalised by using the spectrum of backscattered particles. To determine the number of incident ions from the backscattering spectrum, a simulation software is used. At MEIS energies, where multiple scattering and electronic screening start to become non-negligible, a Monte Carlo approach is typically chosen. In this work, the TRBS (TRim for BackScattering) code [131] was used. TRBS performs efficient simulations by calculating only large-angle scattering events individually and accounting for small-angle collisions globally. The program allows to choose between different scattering potentials and screening lengths and to adjust the electronic stopping power. Here, an uncorrected ZBL potential [33] was selected. Figure 3.4b shows the time-to-energy converted spectrum of a MEIS measurement (black open circles). In this case He ions with an energy of 120 keV were directed onto a gold target and detected under a scattering angle of 135°. The red full line depicts a TRBS simulation for identical conditions, and it was scaled in such a way that the integral over the gold peak is the same as for the experimental data. TRBS has the disadvantage to only consider normal incidence events (θinc = 0). However, for measurements with an electric field applied between sample and detector θinc 6= 0 (typically θinc = 30°). In these cases, SIMNRA [132] was employed as the simulation software. SIMNRA is not a Monte Carlo code, however, and only approximates multiple scattering effects. For light ions (H, He) the incident charge can be approximated sufficiently well though. SIMNRA was also used to simulate the RBS measurements performed for this work and, thereby, to determine the areal thicknesses of the samples. In Fig. 3.4b a typical RBS spectrum using a thin gold film as a target is presented. The blue full line shows the corresponding SIMNRA simulation. The sample thickness that was found by fitting SIMNRA to the data later served as the input for the TRBS simulation of the MEIS measurement, which is shown on the right-hand side. If not stated otherwise, simulations are done with electronic stopping values based on SRIM-13 [35]. The detection efficiency for the energetic backscattered particles is expected to be higher than for the detected photons and possibly also than for the sputtered particles [120]. The measured photon and sputter yields can, therefore, be considered as minimum yields. Note that the already mentioned OAR of

33 3. Experimental set-up and methods about 60 % will affect all particles in the same way and, therefore, does not have to be taken into account. For electrons accelerated to energies > 200eV, the detection efficiency of MCPs is approximately the same as for energetic ions [133, 134]. However, electrons of very low kinetic energy (below 7 eV approximately) are most likely not detected due to deflection by the earth magnetic field, and multiple hits in a short time frame cannot be registered by the data acquisition hardware (cf. Manuscript III for details). Absolute electrons yields are, therefore, not studied systematically in this work.

34 4. Results

This thesis focuses (i) on exploring the potential of experimental techniques for materials analysis beyond a backscattering approach at keV energies, and (ii) on studying ion-solid interactions, specifically electronic excitations, using these techniques. After I have described the more technical details of the employed experimental methods in the previous chapter, I now present an overview of obtained results accompanied by short section-wise introductions putting my work into a broader context of previous scientific knowledge. Section 4.1 presents results on trajectory-dependent electronic excitations studied by transmitting ions through single-crystalline silicon in various geometries. The first part of this work has been published in Paper I, and follow- up experiments are presented in Manuscript II. Related work on data visualisation in 3D ion transmission experiments is the subject of Manuscript IX. Section 4.2 focuses on ion-induced electron emission. Measurements of electron energies with a ToF approach were performed. Results are compiled in Manuscript III. Ion-induced photon emission is the topic presented in Sect. 4.3. The photon yield has been studied as a function of several experimental parameters, and results are published in Paper IV. Finally, results obtained by implementing secondary ion mass spectrometry into the ToF-MEIS set-up are summarised in 4.4. These results are partly published in Paper V, and partly only presented in this comprehensive summary. Note that Papers IV and V also form the basis of my Licentiate thesis.

4.1 Trajectory-dependent electronic excitations by ions in Si(100) 4.1.1 Introduction The energy loss of ions to matter is most often quantiﬁed using the concept of the stopping power. As introduced in Sect. 2.3.2, stopping power denotes the mean energy loss per unit path length, and thereby constitutes an averaging over different energy loss processes and all impact parameters. Considering the sheer amount of individual particles, and thereby potential scattering part- ners, in a solid, the success of this model in describing ranges or the energy loss experienced by the ion along trajectories large against distances between atoms becomes quickly apparent. This approximation is especially justiﬁed

35 4. Results when target atoms are distributed randomly along the ion trajectory as it can be assumed to be the case for amorphous or polycrystalline materials. For the same reason, theories that do not model the target internal structure but assume the movement in a gas of electrons, such as DFT, are successful in predicting S in some cases. These successes should not hide the fact that the energy transfer of the moving ion to target constituents is impact parameter dependent though [135]. To understand individual processes and to obtain an accurate picture of energy deposition at the nanoscale, different experimental and theoretical approaches are therefore needed. One way to probe various impact parameters experimentally is to employ crystalline samples since the channelling effect restricts the ion movement to large impact parameters (cf. Sect. 2.2)[136]. At high energies, the interactions with localised core electrons can be assessed this way, and the observed reduced energy loss and related longer ranges in the channel compared to amorphous targets are attributed to suppressed excitations of the same [137]. At lower energies, however, core-electron excitations become inefficient and ion-electron interactions become dynamic, which can be expected to influence also the impact-parameter dependence. At any energy, the crystal quality and the exact experimental geometry are decisive for the accurate selection of trajectories. Hereby, the transmission method is preferable over a backscattering approach since the latter by definition includes at least one close collision [138]. The availability of high-quality, self-supporting, single-crystalline samples needed for such experiments is, however, not trivial especially for low- energy studies where the required thickness is much reduced. Experimental data of high quality in the medium-energy regime is, therefore, scarce. Re- cently, Wang et al. demonstrated transmission channelling through silicon in a helium ion microscope (HIM) [139], which could potentially be employed for imaging of atomic structure [140]. No electronic stopping has been measured, however. Research on channelling has in the past often been driven by computational and theoretical efforts - it has in fact been discovered in computer simulations [141]. Now the development of TD-DFT could help to model the non- adiabatic energy-loss mechanisms at low ion velocities. Since these calculations are typically performed in channelling geometry, experiments performed under comparable conditions are needed.

4.1.2 Summary of results Ions are directed onto single-crystalline, self-supporting Si(100) nanomem- branes, and detected after transmission. Energies are measured together with angular distributions, and different alignments between the incident beam and the crystalline samples are studied. If the beam is positioned parallel to the principal [100] crystal axis, ions are subjected to channelling. The spatial dis-

36 4.1 Trajectory-dependent electronic excitations by ions in Si(100)

Figure 4.1: Spatial distribution of 100 keV 29Si+ ions transmitted through a 53 nm thick Si(100) crystal in channelling geometry. The projected incident beam position is indicated by the black circle, and the detector is positioned at 0° with respect to the initial beam direction. The inset shows the angular distribution of detected ions along a line parallel to the x-axis at the height of the beam position (y = −3.5mm). tribution of ions on the detector in such a geometry is depicted in Fig. 4.1, using the example of 100 keV 29Si+ ions transmitted through a 53 nm thick sample. The large majority of ions is detected closely around the projected initial beam position, indicated by the black circle. The inset shows the angular distribution of ions on the detector for a cut through the intensity maximum parallel to the x-axis. This peak has a full width at half maximum (FWHM) of 1.6°, which is much smaller than for example the Lindhard angle of 5.8° for the same conditions (c.f. Eq. 2.4). The narrow distribution thus illustrates that the large majority of ions does indeed not undergo scattering at larger angles, but is transmitted on a rather straight, channelled trajectory. The chosen experimental approach allows in principal for studying trajectory-dependent processes in two different ways. First, trajectories ending in different regions of interest (ROIs) on the detector can be compared. The detector could also be rotated to cover larger deﬂection angles, even though this possibility has not been used for presented work. Second, the sample can be rotated to study different alignments between incident beam and crystal axes and planes. For the study published in Paper I, the second approach has been chosen. Protons and He+ ions are employed as probes, and the sample is successively rotated from channelling into random geometry. “Random” in this case means that the sample is rotated such that the beam is not aligned

37 4. Results with any plane or low-index axis of the crystal, which can be controlled by the readily visible blocking pattern. Details are explained in Fig. 2 of Paper I and accompanying text. An example of the spatial distribution of transmitted ions in random alignment is also shown in Fig. 2.3 of this thesis. Only comparably straight trajectories are studied by selecting ions arriving in small, circular ROIs (max. 4 mm radius corresponding to deﬂection angles ±0.8°) around the initial beam position. Energy loss depends on the beam- crystal alignment in all studied cases with the energy loss being lowest in channelling geometry. An example for 50 keV He ions is shown in Fig. 3, Pa- per I. The observed broadening close to the channel is attributed to the overlap of trajectories channelled to strongly varying degrees. To quantify this effect, we express the channelled energy loss as a fraction of the random energy loss, i.e. we calculate ∆Ech/∆Er for each measurement. Results are shown in Fig. 4 in Paper I. For protons, this ratio decreases, from values very close to unity, with increasing energy, and an extension of our results agrees well with data measured at higher energies [142]. For He ions, a reverse trend is observed: an increase of ∆Ech/∆Er with initial energy. Comparison of our data to literature [143–145] suggests the presence of a maximum at around 400 keV to 500 keV. Our results for protons as well as high-energy data can be explained by increasing contributions of core-electron excitations. These electrons are highly localised, and therefore more likely to be excited at small impact parameters [146], which are only accessible in random geometry. For He ions at these low energies, excitations of core electrons are strongly suppressed, however. We, therefore, explain the observed behaviour by collision-induced charge- exchange event, which can only happen along random trajectories. As explained in Sect. 2.3.3, the promotion of electronic levels leads to a direct reduction of kinetic energy, which is however much smaller than the observed energy-loss difference even for repeated charge-exchange cycles. Another out- come of charge exchange is the increase of the mean charge state. The consequently higher stopping power can explain our results. The difference between the results for protons and He ions already shows that impact-parameter dependence does not only depend on ion velocity but also strongly on the projectile electronic structure. We, therefore, performed a follow-up study measuring the energy loss of N+, Ne+, Si+ and Ar+ again for different trajectories in Si(100), which is presented in Manuscript II. The energy loss of 29Si+ ions in 53 nm Si(100) for three different crystal orientations is shown in Fig. 4.2. Again, only trajectories ending in small ROIs on the detector (visualised by the black circle drawn into Fig. 4.1) are evaluated. A large difference between the energy loss in channelling geometry (purple curve) and in a random alignment (red curve) is observed, which is in fact much more pronounced than for He (cf. Fig. 3, Paper I). The dark blue curve for a sample rotation of 1° and 2° around the x- and the y-axis, respectively, exhibits a new feature not observed for He; a double-peak structure. We

38 4.1 Trajectory-dependent electronic excitations by ions in Si(100)

1.0 Channelled

(q , q ) = (1 °, 2°)

x y

0.8 (q , q ) = (5 °, 10 °)

x y

0.6

0.4 Normalised counts Normalised

0.2

0.0

0 10 20 30 40 50 60

Energy loss (keV) Figure 4.2: Energy loss of 29Si+ ions in Si(100) for different crystal orientations. The initial beam energy is 100 keV and the employed self-supporting sample has a thickness of 53 nm. In channelling geometry (purple curve) the incident beam is aligned parallel with the primary [100] axis of the crystal. θx and θy give the rotation of the sample around the x- and the y-axis, respectively. The red curve, hereby, represents a random alignment. study the origin of this observation more in detail by determining the energy loss for different exit deﬂection angles. Evaluated ROIs on the detector are drawn into Fig. 1a of Manuscript II. Obtained results for channelling and random incidence are presented in Manuscript II, Fig. 2a and b, respectively. Comparison of the two cases for larger deﬂection angles shows that the high energy-loss peak in 2a corresponds to a completely random trajectory. We conclude that these ions, thus, dechan- nel very close to the entry point into the sample, i.e. in the surface oxide. The second distinct peak exhibiting lower energy loss is attributed to ions that follow a channelling trajectory before they are dechannelled close to the exit point, i.e. in the oxide on the other side of the foil. From these results, together with the high contrast of blocking patterns and ToF-ERDA measurements, we also conclude that our samples, apart from to be expected surface oxides, are of high quality and purity. Again, we determine the value ∆Ech/∆Er to compare the trajectory dependence of the energy loss for different ion species and velocities. Results (including the data for light ions) are compiled in Fig. 3, Manuscript II. Also for heavier ions other than Si, the difference between channelled and random trajectories is pronounced. ∆Ech/∆Er does not gradually increase with Z1, however, but exhibits an apparent oscillatory behaviour. First, we attribute the increased energy loss along random trajectories to the same charge-exchange induced effects as in the case of He. The much larger difference can be attributed to multiple-electron transitions and higher possible charge states for

39 4. Results heavier ions. Second, the oscillation agrees with the observation that the stopping power strongly oscillates with Z1 for channelling conditions [147–150] whereas for amorphous or polycrystalline samples only weak or no oscillations have been reported ([151], PaperVII). Finally, we compare our experimental data for Si in Si to SRIM predictions and TD-DFT calculations by Lim et al. [60] as shown in Fig. 4, Manuscript II. Data points measured in random geometry are well predicted by SRIM. The electronic stopping in the channel is in very good agreement with the TD- DFT calculation, thus, showing that our transmission approach can indeed be employed for benchmarking these types of calculations.

4.2 Measuring electron energies with a ToF set-up 4.2.1 Introduction Ion-induced electron yields are an relatively easily accessible observable of ion-solid interactions. Electron emission also has high relevance for a vast number of technologies. Examples range from plasma-wall interactions in fusion devices [152, 153] to modelling DNA damage in ion beam based cancer therapy [154, 155]. Until recently, electron emission from insulating thin films, especially MgO, has attracted much attention due to its relevance for the operation of plasma display panels [156, 157]. In addition, the understanding of electron emission is, in turn, a prerequisite for a number of experimental methods. Examples are the accurate measurement of currents, effective signal amplification e.g. in MCPs [134, 158, 159] or more specifically imaging with the helium ion microscope [160, 161]. Recently, ion-induced electron emission has also proven to be a suitable probe for studying the electronic response of 2D materials [162, 163]. To gain understanding of ion-electron interactions, experimental studies have often been designed in a way to disentangle potential from kinetic emission. The pioneering work by Hagstrum identified four different types of electron transitions to be relevant for potential emission [80, 164–166]. Whereas he still used mainly singly charged ions, later research has focussed on slow, multiply charged ions that store a lot of potential energy (see e.g. [79], [167] and references therein). To study kinetic emission, electron yields and emission statistics are typically measured as a function of ion velocity. Specifically, the threshold behaviour of kinetic emission has been subject to extensive studies [88, 168, 169]. The need to measure very small electron yields and the growing contributions of potential emission at low ion velocities [169, 170], make this a challenging endeavour though. Electron yields attributed to kinetic emission have also been connected to the electronic stopping power via modelling [168, 171, 172] or even measured in coincidence with ion energy loss [86, 173].

40 4.2 Measuring electron energies with a ToF set-up

The yield of electrons can and has been simply measured by determining the ratio of electron current to incident beam current, often in combination with a suitably biased collector [174]. This method has several shortcomings though, most importantly the potential contributions of scattered and sputtered ions as well as tertiary electrons to the measured current and the need for primary currents on the order of nA [174]. Instead, the electron emission statistics can be measured by accelerating and focussing all electrons onto a solid state detector using electric potentials of several kV [175, 176]. This way also low yields can be assessed accurately. In addition, the possibility to use primary beams of low current allows to study even insulating targets [177]. Electron energy distributions are typically measured using electrostatic spec- trometers [79, 178]. A retarding field approach can also be used in combination with a high-potential set-up as described above [163]. However, gaining information on both emission geometry and electron energy is not straightfor- ward with such a technique. Measuring electron energies via the flight time has been, to our knowledge, seldom attempted. Existing experiments combine the ToF approach with guiding by magnetic fields making the determination of emission energy and direction, again, much less direct [179, 180]. We have integrated the detection of electron emission induced by keV ions into our ToF-MEIS set-up. This study aims to show that electrons with low initial kinetic energy can be assessed by a time-of-flight approach. Results are compiled in Manuscript III, which is attached to this thesis, and summarised in the following.

4.2.2 Summary of results Since electrons are ubiquitous, the project’s first goal was to verify that we indeed detect electrons emitted from the sample due to ion impact. To that aim first and most importantly, the electron flight time was studied as a function of Vsample (cf. Fig. 1, Manuscript III for a sketch of the relevant parts of the set-up). Resulting ToF spectra for a 200 keV He beam and a Au sample are shown in Fig. 3 in Manuscript III and, for one example Vsample only, also in Fig. 3.3a. Both figures visualise how the electron distribution is accelerated and focussed in the time domain by a negative sample bias. Second, SIMION simulations [124] were performed using the experimental geometry and measured electron energies as input parameters (emitting the influence of the earth magnetic field though). Figure 4.3 compares flight times obtained from these simulations (black squares) with the most-probable flight times of the experimental spectra shown in Fig. 3, Manuscript III (red open circles). For the simulation, one electron with an initial energy of Ee = 32.7eV (deduced from the time-to-energy converted spectrum for Vsample = 0V, see Sect. 3.4.1) was placed at the sample position. An initial emission direction aligned with the experimental beam direction was chosen, and the time when

41 4. Results

200 keV He ® 141 nm Au

40 Time-of-flight, ns Time-of-flight,

Experiment

SIMION simulation E = 32.7 eV

SIMION simulation E = 16.1 eV

-500 -400 -300 -200 -100 0

V , V

sample Figure 4.3: Comparison of experimental electron flight times with SIMION simulations for different sample biases. Experimental data was recorded by transmitting a 200 keV He beam through a self-supporting Au target. The red open circles give the most-probable flight time with error bars indicating the time resolution of the respective measurement. For the simulations, the flight time of a single electron with initial energy Ee = 32.7eV (black squares) or accordingly Ee = 16.1eV (black open squares) and emission direction aligned with the initial beam direction was recorded with SIMION.

the electron hit the MCP front was recorded with SIMION. For high sample biases the agreement between simulation and experimental results is extremely good. This observation indicates consistency between experiment and simulation concerning the geometry and electric field configuration since a high sample bias constitutes a situation in which the electric field strength and direction dominate the flight time. For lower electric fields (Vsample & −250V) the simulation reproduces the Vsample dependence rather well, but underestimates the experimental flight times. In this case, the flight time depends a lot more on the precise knowledge of the initial electron energy and actual trajectory, which is in turn determined by the emission angle and eventually subject to the influence of the earth magnetic field. In addition, the most-probable flight time is not identical with the time corresponding to the most-probable energy due to the non-linearity of Eq. 3.2. A second simulation was performed, this time by tuning Ee until the simulated flight time at Vsample = −20V matched the experiment. The resulting energy is 16.1 eV, and simulated ToF for different voltages are given by black open squares in Fig. 4.3. Considering the rather large error bar of Ee as obtained from the energy spectrum (cf. Fig. 4, Manuscript III), and the before described unknowns, the reproduction of the trend but not the precise flight times with this simulation can be considered sufficient to say that experimental trajectories resemble the simulated ones.

42 4.2 Measuring electron energies with a ToF set-up

1x10

150 keV Ne ® 25 nm C

1x10

8x10

6x10 Counts

4x10 Most-probable energy

Mean energy

2x10

max

20 40 60 80 100 120 140

Electron energy, eV Figure 4.4: Time-to-energy converted electron spectrum recorded by employing 150 keV Ne ions as projectiles and a 25 nm thin, self-supporting C foil as the target. The blue full and the dashed line indicates the position of the most-probable energy and the mean energy of the measured distribution, respectively. The calculated maximum energy transfer in a classical binary head-on collision is given by the dotted line.

Finally, since the recorded data is stored event-wise, a coincidence crite- rion between detected electrons and ions can be implemented in the analysis software. This way, we can confirm that electrons are indeed detected within the same 750 ns long detection window (set in the acquisition software) as a transmitted ion. Given this evidence we presume that we can reliably detect secondary electrons ejected as a result of the ion-sample interaction. As discussed in detail in Manuscript III, however, electrons with very low initial energies (approximately < 7eV) have a gyromagnetic radius comparable to the sample-detector distance. Hence they can most likely not be measured with the present set-up due to insufficient shielding against the earth magnetic field. The energy of emitted electrons was studied for a wide variety of ion species and velocities. All results are compiled in Fig. 4 in Manuscript III. Self- supporting Au and C foils were employed as samples. However, no sample cleaning was performed so that the Au foil surface was found to be covered by around 83 % C according to our analysis by AES. Therefore, and due to the surface sensitivity of electron emission, no material dependence of the electron energy is observed. Figure 4.4 depicts an example of a time-to-energy converted electron distribution. Here, Ne+ ions with an energy of 150 keV were transmitted through a 25 nm thin C foil (the corresponding ToF spectrum is in fact shown in Fig. 3.3a). Three blue, vertical lines indicate the positions of the most-probable energy (full), the mean energy (dashed) and the calculated maximum energy

43 4. Results transfer in a classical binary collision Tmax (cf. Eq. 2.17) (dotted). The observed electron energy distributions are broad and feature a tail on the high- energy side. Detected electron energies range between 10 eV and 400 eV. No peak at the position of the C Auger line (272 eV [181]) has been seen in any measurement. In Manuscript III we have chosen the most-probable energy as our observable, and it is plotted as a function of ion exit velocity in Fig. 4. We are aware that this energy cannot be assigned to a speciﬁc physical variable, but is the result of a combination of the electron emission processes described in Sec- tion 2.4.2. The velocity dependence of the mean energy moreover scales in a similar way. For ion velocities above 1 a.u., a clear velocity dependence can be observed with most-probable energies lying well below Tmax, however. We interpret this scaling as the signature of a primarily kinetic energy transfer in binary collisions between ions and electrons. Due to the short inelastic mean free path of electrons in this energy range [182], a majority of electrons can be expected to originate from electronically driven cascades leading to the reduced most-probable energy in comparison with Tmax. At lower ion velocities, the observed electron energy is constant within the measurement uncertainty. As can also be seen in Fig. 4.4, the most-probable energy is higher than the maximum energy transfer possible in a binary collision. Additional contributions from potential emission or emission via plasmon decay [183], therefore, need to be considered.

4.3 Ion-induced photon emission1 4.3.1 Introduction An established IBA technique, which exploits ion-induced photon emission for materials analysis, is particle2 induced X-ray emission (PIXE). In PIXE light ions (most commonly protons) with energies of a few MeV are used to excite target atoms, and characteristic X-rays from the subsequent decay of inner-shell holes are detected [184]. The highly sensitive technique is commonly used to detect trace elements, and has been employed in a variety of ﬁelds such as materials science [185], medicine [186], cultural heritage and archaeology [187] as well as environmental sciences [188]. PIXE has even been used to analyse Martian rocks - on Mars [189]. Of particular relevance is the combination of PIXE with the nuclear microprobe technique [190], which allows for scanning of a focussed ion beam over the sample. X-rays are detected from depths up to a few mm, depth information, however, cannot be

1This section is largely based on the corresponding part of my Licentiate thesis: S. Lohmann. Electronic excitation, luminescence and particle emission. Studying ion-induced phenomena in ToF-MEIS. 2018. 2Sometimes “proton” is used instead.

44 4.3 Ion-induced photon emission obtained directly [9]. Due to the high X-ray production cross sections for inner-shell transitions, MeV ions are commonly used as probes [191, 192], however, PIXE using ions with energies between 200 keV and 1 MeV (called low-energy PIXE) has also been employed as a tool in mainly materials science [193]. These experiments principally aimed at improving light element detection [194], and thin-film and near-surface analysis [195, 196]. Atomic transitions can be probed by either ions, electrons or photons with sufficient energy. In energy dispersive X-ray spectroscopy (EDX) a focussed electron beam is used to excite the sample, and characteristic X-rays are detected with a solid state detector [197]. Employing electrons has the disadvantage though that the large background due to Bremsstrahlung diminishes sensitivity. The analysis of insulators is additionally hindered by charging of the sample. Another widespread technique to study core electron levels experimentally is X-ray photoelectron spectroscopy (XPS) also called electron spectroscopy for chemical analysis (ESCA) [198]. This method reverses the approach of EDX, and uses X-rays as probes and directly detects the emitted electrons. Ultraviolet photoelectron spectroscopy (UPS) is a related technique, which employs low-energy UV photons typically produced in gas discharges to probe valence transitions [199, 200]. Research using ion beams with energies lower than 200 keV to induce UV photon emission is, however, scarce. Photon emission has been observed in a number of time-of-flight set-ups using ion beams as probes [24, 201, 202]. Even though the photon peak has been used to determine the time when the incident beam strikes the sample, to my knowledge no further investigations of e.g. the dependence of the observed yields on ion species, energy or material have been carried out. Therefore, this project comprises of a systematic analysis of the ion-induced photon emission measured in a ToF-MEIS set-up. A summary of the results, which are also published in Paper IV is presented in the following.

4.3.2 Summary of results Experiments were conducted with hydrogen, helium and neon ions as projectiles. Gold and TiN ﬁlms of different thicknesses as well as several bulk samples (Au, Si, SiO2, C) served as target materials. In all experiments photon emission is found prompt within the time resolution of the system, which is illustrated in the inset of Fig. 2 in Paper IV and can also be observed in Fig. 4.5. Thus, the life time of observed states is well below 1 ns. For a series of experiments a calcium ﬂuoride (CaF2) viewport was mounted in front of the detector so that it partly screened its active area (see Fig. 1 in Pa- per IV). Figure 4.5 shows a comparison between the detected photon yield after transmission through the window with the photon yield from an uncovered detector area of the same size for a gold sample. The yield after transmission through CaF2 was found to reach about 15 % of the unscreened one both for

45 4. Results

Au and a TiN target. In Fig. 1 in Paper IV a typical MCP detection efficiency curve is contrasted with the transmission curve of the viewport. The curves overlap between 120 nm and 180 nm (corresponds to a converted photon energy range between 7 eV and 10 eV), which means that a significant fraction of photons must have energies in this range. The photon yield shows dependencies on a number of experimental parameters. The main experimental observations are summarised in the following. • Film thickness. The photon yield was determined for gold films of 166 Å and 281 Å thickness as well as a gold bulk sample for a number of ion velocities. The results are presented in Fig. 4.6, and it is clearly visible that the photon yield rises with increasing gold thickness. • Scattering angle. The dependence of the photon yield on the scattering angle is depicted in Fig. 4 in Paper IV for three different projectile-target combinations. The photon yield significantly increases for larger scattering angles in all cases. • Projectile. Figure 5 in Paper IV compares the photon yields induced by H2, He and Ne ions. For the same ion velocity the photon yield from Au clearly increases for heavier projectiles. The figure additionally shows the electronic stopping cross sections for all three ion species in Au. The difference of the photon yield is found to exceed the difference in stopping. • Incident ion velocity. Figure 5 in Paper IV illustrates that the photon emission increases with incident ion velocity for all employed projectiles. In addition, Fig. 4.6 shows that at least for an incident helium ion the photon yield depends linearly on primary energy in the studied energy range. • Target material. Table 1 in Paper IV lists photon yields for various materials. A material dependence becomes most obvious when compar- ing the photon emission from common substrate materials (Si, SiO2, C) with each other: While Si yields a signal of about 551 arbitrary units, the yield for SiO2 and C reach only about 12 and 5, respectively. The large yield from Si, however, complicates the evaluation of photon emission from thin films deposited on this substrate. The dependence on the film thickness and the increase with scattering angle (larger scattering angle corresponds to a shorter path length through the material for photons moving towards the detector) are strong indications that photons are produced along and detected from the whole path of the incident ion. Since a longer path length is connected to increased attenuation, the angular dependence also shows that the attenuation length is on the same order of magnitude as the film thickness. An attenuation length in gold of 135 Å is connected to deep UV photons with an energy of 10 eV [203]. This observation, therefore, is in line with the findings of the experiments conducted with the CaF2 viewport.

46 4.3 Ion-induced photon emission

140

100 keV He 289 Å Au/Si

120

Photon yield

100

unfiltered

Photon yield

behind CaF

60 Counts

-10 -5 0 5 10

Time-of-flight, ns Figure 4.5: Comparison between the detected photon yield after transmission through a CaF2 viewport (blue area) with the unﬁltered yield (black line). The chosen region- of-interest has the same size for both curves. The experiment was conducted with 100 keV He ions as projectiles and a thin Au (289 Å) ﬁlm on Si substrate as the target. The scattering angle was 155°.

The large difference between the photon emission from Si and SiO2 furthermore indicates that Si core-level transitions, which would be present in both materials, play a minor role in the observed photon emission. In addition, lattice defects can be expected to be more prevalent in the SiO2 ﬁlm than in Si wafer. This assumption, together with the high photon yield from Si and the narrowness of the photon peak, implies that photons are not primarily produced as decay products of long-living states. We, therefore, suggest that a large fraction of detected photons originates from excitations of valence and conduction band states. Due to the enhanced increase for heavier projectiles in comparison to the electronic stopping, a production mechanism additional to direct electron-hole pair creation seems likely. The observed dependence of the photon emission on the incident ion energy is not yet understood and should be studied further. Whereas a general increase of the photon yield with increasing energy deposited into the target could be expected, a linear behaviour with a positive offset at vanishing primary energy as it is shown in Fig. 4.6 is non-physical. After the publication of Paper IV, additional tests with an X-ray detector were performed. An XR-100SDD from AMPTEK [204] was mounted at the MEIS beamline just behind the chopper, and positioned close to an aluminium-based viewer plate at a 90° angle from the beam direction. Tests were performed with a continuous as well as a pulsed 200 keV He+ beam. For the former, a distinct X-ray signal from the beam impact on the Al side of the viewer plate could be recorded. With a pulsed beam, however, no X-

47 4. Results

350

He 166 Å Au/C

300

He 281 Å Au/C

He bulk Au

250

200

150

100

Negligible signal from

C substrate

0 Photon yield per incident ion, arb. units arb. ion, incident per yield Photon

0 50 100 150 200 250

He energy, keV Figure 4.6: The photon yield induced by He ions as a function of primary energy for different Au thicknesses. Two thin film samples, specifically, 166 Å (blue open squares) and 281 Å (red triangles) on carbon substrate, and a bulk sample (black dots) served as targets. The scattering angle was 155° in all cases. The error bars give the statistical uncertainty. One data point measured for a pure carbon substrate is added to illustrate that photon emission from carbon is negligible and does not add to the thin film photon yields. ray signal could be distinguished from noise even within measurement times significantly exceeding typical MEIS experiment durations. The employed detector is covered by a 12.5 µm thick beryllium window, and is sensitive to photons with a minimum energy of 600 eV (i.e. Z > 9) [204]. While characteristic X-rays are produced by medium-energy ions, and yields are high enough to perform low-energy PIXE with a continuous beam [205], these are most likely not the ones observed in our ToF-MEIS experiments. These results further strengthen our hypothesis that the photons detected using a pulsed beam and an MCP detector have energies in the deep UV regime.

48 4.4 Secondary ion mass spectrometry with medium-energy ions 4.4 Secondary ion mass spectrometry with medium-energy ions3 4.4.1 Introduction The analysis of sputtered particles can be used both to assess fundamental ion-solid interactions and to study the composition of surfaces and thin films. For around 60 years the method of secondary ion mass spectrometry (SIMS) has been employed for this purpose [206, 207]. SIMS is typically not an accelerator-based method, and ions with energies of at most a few keVu−1 are provided by an ion gun [208, 209]. The ejected ions are analysed according to their mass by sector mass spectrometry, quadrupole mass spectrometry [210, 211] or time-of-flight [212], and mass resolution m/∆m of 104 can be achieved [213]. The ToF technique together with pulsed beams is most often used in the static SIMS regime [99, 214]. “Static” in this context means that less than 1 % of surface atoms are hit by the primary beam [213], i.e. ion doses need to be kept well below 1013 ions/cm2, which allows for the characterisation of even sensitive biomaterials [215]. In SIMS only sputtered ions are detected. However, the amount of sputtered neutrals is typically much higher than that of sputtered ions [216]. In addition, the ionisation or neutralisation of sputtered particles is subject to significant matrix effects [217], and quantitative results without references are, thus, difficult to achieve. Secondary neutral mass spectrometry (SNMS) assesses sputtered neutrals by postionising them [218], e.g. with a strong laser field [219, 220]. Through this separation of the emission from the ionisation process, matrix effects can be avoided and quantification simplified. Sensitivity can also be greatly enhanced. Mass spectrometry in the electronic sputtering regime has first been probed by fast fission fragments from 252Cf sources [221] and subsequently also by heavy MeV ions provided by accelerators [222]. This method known as plasma desorption mass spectrometry (PDMS) or MeV-SIMS is able to sputter large intact organic molecules [98, 221], and has therefore been successfully employed as an interdisciplinary research tool [223]. The usage of PDMS has, however, declined with the introduction of matrix-assisted laser desorption/ ionisation (MALDI) [224]. More recently, attempts have been undertaken to perform MeV-SIMS at ambient conditions, which would allow to analyse even volatile samples [225, 226], or with a highly focussed beam to enable scanning [227]. Electronic sputtering by swift heavy ions (i.e. ions with energies around and above 1 MeVu−1) can lead to significant material modifications [113]. This process, closely related to the formation of ion tracks, has been studied for

3Parts of this section are based on the corresponding part of my Licentiate thesis: S. Lohmann. Electronic excitation, luminescence and particle emission. Studying ion-induced phenomena in ToF-MEIS. 2018.

49 4. Results a number of materials [228, 229], and results have been shown to strongly depend on the material class [113]. Sputtering phenomena at energies above the range of ion guns but below the MeV regime provided by large accelerators have been studied far less. One recent development is the combination of SIMS with the high resolution imaging capabilities of a HIM [201, 230, 231]. The HIM uses helium or neon primary beams with ion energies between 5 keV and 35 keV, and imaging is typically achieved via secondary electron emission contrast. Here, SIMS could yield additional information on chemical composition [230]. Kobayashi et al. performed an early study on desorption induced by light ions at medium energies in the Uppsala ToF-MEIS set-up [232]. However, in their work only one, rather complex target material (LiO2 on a MgLi alloy), was investigated. The present work strives to perform a systematic analysis of the sputtering process induced by medium-energy ions and its dependencies on several experimental parameters by employing simple test systems. The results are partially published in Paper V and summarised below.

4.4.2 Summary of results Experiments published in Paper V were performed by probing TiN thin film + + and Al samples with He and H2 beams. Additional experiments using different target systems (bulk VN, V, Cu and Au(110)) have been conducted. When an electric field is applied between sample and detector (typically, Vsample = 500V), a vast number of additional peaks can be observed in the ToF spectrum. An example obtained from He on a VN sample is shown in Fig. 3.2. The peaks are identified as positive sputtered ions, and their mass to charge ratio can be calculated from their flight time (cf. Eq. (1) in Paper V), which is shown on the top axis of Fig. 3.2. A majority of the peaks are identified as surface contaminations by com- paring spectra taken from sputter-cleaned and as-transferred samples (Fig. 4 in Paper V). Contaminations are significantly reduced after cleaning (60 keV He+, ∼3 × 1018 ions/cm2, 45° beam incidence), whereas the Ti+ yield, which is also clearly visible in all experiments using TiN films, hardly changes. Con- sidering the matrix effects well-studied in SIMS, it is concluded that even the non-cleaned samples were only slightly contaminated, but that the MEIS- based method is rather sensitive to these contaminations. I will in the following first describe results regarding target bulk constituents before coming back to studies on surface contaminants. All detected signals from sputtered target bulk species exhibit an asymmetric peak shape both in time (see e.g. Fig. 4.7) and in energy domain. The high-energy side tail is well known from sputtering by collision cascades, which is hence assumed to be the mechanism behind the sputtering of bulk constituents in the MEIS regime as well.

50 4.4 Secondary ion mass spectrometry with medium-energy ions

200

100 keV He ® Cu

Sputtered

Sputtered & annealed 150

100 Counts

6400 6600 6800 7000 7200 7400 7600 7800 8000

Time-of-flight, ns Figure 4.7: Peak of sputtered Cu+ in a ToF spectrum recorded with a 100 keV He+ beam and employing a polycrystalline bulk Cu sample. The black curve shows the signal from a only sputter-cleaned sample, whereas the orange peak originates from a sample, which has additionally been annealed. For details on the in-situ cleaning procedures see text.

To further study possible matrix effects, additional experiments were conducted with Au(110) and Cu samples (not published). To this aim, surfaces were not only sputter-cleaned (50 keV He+, ∼5 × 1016 ions/cm2, 45° beam incidence) but also subsequently annealed at 300 °C. This procedure proves to be very effective in removing surface contaminations - only small peaks identi- + + + + ﬁed as H ,H3O , Na and K are left visible in the ToF spectrum. The yield of sputtered Cu+ and Au+, respectively, is also greatly reduced in comparison to the only sputter-cleaned sample. For Cu, this reduction is shown in Fig. 4.7. Table 4.1 shows sputter yields and ion fractions for Cu, both for a very clean and a slightly contaminated (either only partially cleaned by sputter-cleaning without annealing or oxidised) surface. Data obtained by us using a 100 keV He+ beam (labelled “MEIS” in the table) is compared to SIMS data from [99] recorded with a 3 keV Ar+ beam. Note that all MEIS sputter yields presented here and later in the text are normalised to the total integrated charge obtained from the spectrum of backscattered ions as described in Sect. 3.4.2. Total sputter yields (neutrals and ions) are extracted from empirical ﬁts from [233]. Note that due to limited availability of data otherwise, incidence angles between beam and surface normal are different for all three sources. Our experiments are performed under 30° incidence, the SIMS incidence angle is 20° and data in [233] is reported for normal incidence. For Cu, both ion and total sputter yields are much lower for MEIS conditions than for SIMS which can be expected due to the much higher nuclear stopping cross section of the Ar beam. This observation is true for both states

51 4. Results

MEIS SIMS MEIS SIMS clean clean sc only oxidised Cu+/inc. ion (Exp.) 8 × 10−7 1.3 × 10−4 5 × 10−6 4.5 × 10−3 Cu/inc. ion [233] 5 × 10−2 4.5 5 × 10−2 4.5 Ion fraction Cu+/Cu 1.6 × 10−5 2.9 × 10−5 1.0 × 10−4 1.0 × 10−3 Table 4.1: Sputter yields and ion fractions for Cu. MEIS data is recorded with a 100 keV He+ beam under 30° incidence angle. SIMS data is taken from [99], and was obtained with a 3 keV Ar+ primary beam (20° incidence angle). Total sputter yields (Cu/inc. ion) are from empirical ﬁts to tabulated data from [233]. The column labelled with “sc only” refers to a sputter-cleaned but not annealed surface which leaves some surface contaminants (e.g. O, H20, hydrocarbons).

of the surface. Ion fractions determined for a clean surface are very similar regardless the technique though. The surface conditions for the “contaminated” surfaces are probably not identical. However, ion fractions exhibit the same trend and increase in both cases compared to the clean surface. This behaviour can be explained by the presence of a highly electronegative element such as oxygen, which significantly increases the formation of positive ions and thus the measurable yield. This effect is well studied in SIMS [234]. Hence we conclude that matrix effects experienced by sputtered bulk species at typical MEIS conditions are comparable to those of a standard SIMS measurement. We are also positive that our employed combination of a large-area detector and an applied electric fields is effective in capturing the large majority of positive sputtered ions. To assess further influences of the matrix on the sputtering process, a comparison between TiN, VN and V samples was planned. The mass spectra obtained from TiN and VN look qualitatively very similar, and yields of sputtered Ti+ and V+ obtained from sputter-cleaned samples differ by maximum 15 %. Attempted cleaning of the V sample revealed, however, that a significant number of impurities must also be present in the bulk for this sample. Further comparison was therefore not attempted, and measurements should be repeated with better defined surfaces. + I will now show results on surface species with a focus on H and H2 . The + + primary kinetic energies E0 of desorbed H and H2 have been determined + by varying the sample voltage. The flight time of H as a function of Vsample is shown in Fig. 4.8. The most-probable initial kinetic energy is extracted from fitting Eq. (1) (Paper V) to the data, and it is found to be (11.3 ± 1.0) eV + and (6.4 ± 1.2) eV for H and H2, respectively. Note that H ions can even reach the detector without acceleration. The energy can thus be identified without fitting, and is found to be 11 eV matching the result reported above and corroborating the choice of the fitting function.

52 4.4 Secondary ion mass spectrometry with medium-energy ions

+ 6000

100 keV He 189 Å TiN/Si

5000

4000 , ns , +

3000 ToF of H of ToF

2000

E = (11.3 1.0) eV

1000

0 100 200 300 400 500

Sample voltage, V Figure 4.8: Flight time of desorbed H+ as a function of applied sample voltage. The black dots represent the experimental data while the red line is a ﬁt using Eq. (1) in + Paper V. The initial kinetic energy of the H ions E0 can be extracted from the ﬁt since it is the only free parameter. Note that the time resolution for each measurement is < 1.2ns, and that error bars are therefore the size of the symbols and not visible.

A quantification of sputter yields for additionally selected, easily identified species is attempted. A comparison of the results from He and H2 projectiles as well as TiN and Al targets is presented in Table 1 in Paper V. The orders of magnitudes of surface contamination yields that can be measured with the ToF-MEIS set-up are found comparable with yields measured with conventional SIMS machines. The yield difference between He and H induced sputtering is found to be higher for target constituents than for surface contaminants. The behaviour of the desorbed H+ yield is shown in more detail in Fig. 4.9. + Depicted are the yields for primary He (red circles) and H2 (black squares) + beams in combination with a TiN thin film and for H2 ions incident on three different Al samples (blue asterisks, diamonds and triangles) for different ion velocities. The increased yield for heavier projectiles can clearly be observed from comparison of the two curves for TiN. Also, the H+ yield apparently exhibits a dependence on the velocity of the primary ion. The yields of desorbed + + H2 and H3 show a similar behaviour. For surface contaminants, we suggest a predominantly electronic energy transfer mechanism as the cause of desorption. Summarised, this proposal is based on the following observations:

• the high amount of molecular species present in the spectra, • the invariability of the initial kinetic energy of desorbed ions with beam energy, • the narrow and symmetric energy distribution,

53 4. Results

-4

3.0x10

He 189 Å TiN

-4

H 189 Å TiN 2.5x10

H Al foil I

-4

2.0x10 +

H Al foil II

H Al bulk

-4 2

yield / inc. ion inc. / yield 1.5x10 +

-4

1.0x10

-5

5.0x10 Desorbed H Desorbed

0.0

0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4

Incident ion velocity, a.u . Figure 4.9: Dependence of the desorbed H+ yield on the incident ion velocity. Data + is shown for a TiN thin ﬁlm sample both for a primary He (red circles) and a H2 beam + (black squares) and for three different Al samples (only H2 , blue asterisks, diamonds and triangles). The beam incidence angle was 30° in all cases, and secondary ions were accelerated with Vsample = 500V. All samples were transferred from ambient conditions.

• the yield difference between He and H induced desorption (YHe/YH ), which is of the same order of magnitude as the difference in electronic stopping power.

Due to this conclusion a dependence of the yield on the electronic stopping power could be expected, which is, however, not observed (cf. Fig. 4.9). A different scaling with the incident ion velocity of other effects such as average excitation energies of electrons, secondary electron interactions and electron- phonon coupling could explain this effect. To explore potential possibilities of sputtered ion detection in ToF-MEIS as a surface analysis technique, the behaviour of sputtering yields after in-situ sample cleaning was studied. A TiN film was employed as the sample, and + + sputter-cleaned until no more H2 and H3 were detected in the ToF spectrum of sputtered ions. Time-resolved measurements of sputter yields were then per- + + formed with a pulsed 50 keV H2 beam, which is shown in Fig. 4.10.H (black + + squares), H2 (black open squares) and CH3 (red open circles) are selected as examples for desorbed surface species and Ti+ (blue asterisks) is shown as the sputtered bulk constituent. All values are normalised to the yield obtained at the first measurement point. Additionally, yields for an as-transferred sample are shown on the right-hand side for the three contaminants. For Ti+, overlap with hydrocarbon signals in the spectrum from the as-transferred sample allowed for no clear quantification of the yield, and it was therefore omitted. As already observed before, the Ti+ yield exhibits no strong dependence on

54 4.4 Secondary ion mass spectrometry with medium-energy ions the surface condition whereas the yields of surface contaminants continue to + + increase for hours after cleaning. H and H2 yields rise linearly with the same slope within the measurement uncertainty ((0.0037 ± 0.0003) ions/min indicated by the full line and (0.0041 ± 0.0003) ions/min (dashed line), respec- + tively). This similarity indicates that hydrogen is adsorbed as H2 at the TiN surface. Experiments of the same kind were also performed with a polycrystalline Cu sample and a 100 keV He beam. Here, the matrix effects already shown in Table 4.1 lead to a strong increase of the yield of sputtered Cu+ + + with time. H and H2 yields exhibit again a linear behaviour with time, in + this case a slightly lower slope for H2 suggests a possibly different adsorption mechanism than for the TiN surface.

Desorbed H

Desorbed CH

Sputtered Ti

Linear fit, H data

2 Norm. desorption yield desorption Norm.

0 20 40 60 80 100 120 140 160

Uncleaned t-t , min

ref

sample Figure 4.10: Development of ion yields after in-situ sputter-cleaning. Measurements + were performed with a pulsed 50 keV H2 beam employing a polycrystalline TiN sample. Ti+ (blue asterisks) as a sputtered bulk constituent is shown together with se- + + + lected surface contaminants (H (black squares), H2 (black open squares) and CH3 ions (red open circles)). All yields are normalised to the respective yield obtained at the first measurement point. The points at the right-hand-side refer to as-transferred conditions. Note that the Ti+ yield could not be fully quantified under these conditions due to overlap with the signatures of hydrocarbons. Additionally a linear fit to the H+ + and H2 yields is shown by the full line and the dashed line, respectively.

5. Conclusions

This thesis set out to study ion-matter interactions in a medium energy ion scattering set-up. Based on pulsed ion beams and a time-of-flight approach, experimental methods beyond conventional backscattering were explored. Ex- periments in transmission geometry were performed, and capabilities to detect secondary electrons, photons and sputtered ions were integrated into the existing set-up at Uppsala University. So, what can be learned from pulsed keV ion beams? For transmission experiments, the low ion currents achievable with the pulsed-beam method are imperative for neither damaging the employed self- supporting samples nor saturating the detector. In combination with single- crystals, impact-parameter selective experiments can be performed. Results from energy-loss measurements in Si(100) show strong indications that contributions from charge exchange and its influence on the ion mean charge state are significant for electronic stopping at medium energies. These interactions are, however, strongly impact-parameter dependent, and suppressed for channelled trajectories. Furthermore, the simplicity of our experimental geometry allows for employing our results as benchmark systems for dynamic calculations using time-dependent density functional theory. The presented experiments, as well as results published in related Papers VI and VII, thus provide further evidence that the energy transfer of medium-energy ions to electrons in solids goes beyond the excitation of electron-hole pairs, and need to be modelled accordingly. For studying charge-state dependent effects, the time-of-flight method yields the advantage over electrostatic approaches that also neutrals can be detected. By additionally installing a deflection unit behind the sample, exit charge states of transmitted particles could be separated. Experiments of this kind are in preparation to directly test our hypothesis of a trajectory dependence of the mean charge state of the ion. We showed that the energies of electrons emitted upon ion impact can be assessed by measuring their flight time, again in transmission geometry. For even more quantitative results, also at the lowest electron energies, shielding against external magnetic fields should be added to the set-up, however. In the future, a target-preparation chamber will be attached to the experimental chamber allowing for in-situ cleaning. Then, the surface-sensitivity of electron emission could potentially supplement materials characterisation performed in conventional ToF-MEIS experiments. This technique also has potential to be employed for research on the electronic response of 2D materials, especially

57 5. Conclusions in combination with ion-electron coincidence measurements. We have already performed first experiments using samples of self-supporting graphene that show promising results regarding the feasibility of such studies. The photons detected in the ToF-MEIS set-up seem to originate from different transitions than X-rays measured in PIXE experiments. Energies are on the order of typical valence transitions in solids, and the photon yield is sensitive to chemical matrix effects. Therefore, a method based on the analysis of photon emission could be an interesting complement to the elemental information obtained in backscattering experiments. Direct spectroscopy of deep UV photons is technically challenging and costly, however, especially for the observed low yields, and was thus not further pursued in this thesis. The mass of sputtered target bulk constituents and surface species can be determined from the measured flight time in combination with an applied electric field. Yields of positive sputtered ions are sufficiently high to allow for near-surface materials analysis, which could supplement the depth profiles obtained from scattering experiments. Matrix effects on the same order as for conventional SIMS have been found, thus, complicating quantification. As for electrons, advanced in-situ target preparation methods and improved vacuum conditions would benefit this technique. The possibility for time-resolved, non-destructive measurements has the potential for studying adsorption processes of gases. If Geiger and Marsden had directed keV ions onto crystalline sample, their results would have looked rather different. In strong contrast to ion-matter interactions at MeV energies, which resemble binary collisions of point charges, interactions of slow ions with both target nuclei and electrons are complex multi-body problems. (Collision-induced) Electron-capture and -loss processes resulting in a dynamic charge state of the ion need to be accounted for. These interactions need to be modelled by non-perturbative, time- dependent approaches providing more information about specific energy-loss mechanisms, and going beyond the concept of an average energy loss along the whole ion trajectory. A hundred years after the ground-breaking experiments in Rutherford’s lab, such complex modelling demands powerful computers, and requires to be benchmarked against energy-loss experiments as performed in this work. Complementary measurement techniques that assess products of the primary ion-electron interaction such as secondary electrons and photons could, hereby, help paint a more complete picture of the electronic excitations in matter.

58 6. Sammanfattning på svenska (Summary in Swedish)

Växelverkan mellan joner och materia spelar en central roll för flera olika fe- nomen och teknologiska tillämpningar såsom inflytandet av solvinden på him- lakroppar, protonterapi för behandling av cancer eller interaktion mellan plas- mat och väggen i en fusionsreaktor. Joner kan också användas för att förändra egenskaper hos material eller för att analysera materialets kemiska samman- sättning och struktur. Medium energy ion scattering (MEIS) är en experimentell metod som använder joner med medelhöga energier, det vill säga mellan ett fåtal och några hundratals keV, för materialanalys på nanometerskala. Jo- nernas spridning från atomkärnor och elektroner leder till energiöverföring från jon till material. Det innebär att jonen bromsas men medför också emis- sionen av olika partiklar från materialet, såsom elektroner, fotoner, sputtrade joner och atomer samt produkter från kärnreaktioner. I MEIS används vanligt- vis (bakåt)spridda joner för analys. Forskning gällande huruvida sekundärpar- tiklarna kan användas för att få en djupare förståelse av fysikaliska processer bakom energiöverföring eller för materialanalys är sällsynt. Joner med medel- höga energier interagerar först och främst med materialets valenselektroner. De här växelverkningarna är dynamiska då joner och elektroner har liknande hastigheter och experimentell och teoretisk forskning är pågående. Den här avhandlingen bidrar till att få en mer komplett bild av hur joner och elektroner påverkar varandra vid medelhöga energier genom att utveckla och använda andra metoder än bakåtspridning. Mätmetoder för sekundärelektroner, fotoner och sputtrade joner har därför integreras i MEIS-systemet på Uppsala univer- sitet. I första delen av arbetet presenteras ett experiment där joner skickas genom tunna, fristående kiselkristaller i transmissionsgeometri. På detta sätt kan man påverka interaktionens stötparameter. Stora skillnader i energiförlust mellan kanaliserande och slumpmässig geometri har upptäckts för alla joner förutom protoner. Anledningen är troligtvis att elektroner kan överföras mellan provatomer och joner men bara för tillräckligt små avstånd som inte kan nås i kanaliserande geometri. De här processerna höjer jonens laddningstal vilket leder till högre energiförlust. Sekundärelektroner har också mätts i transmissionsgeometri och deras energier, som ligger mellan 10 eV and 400 eV, har bestämts från deras flygtid. För att uppnå kvantitativa mätningar även vid de lägsta elektronenergierna behövs dock skärmning mot magnetiska fält. Elektroner som mätts kommer från mycket nära ytan. Tillverkning och rengöring av ytor i vakuumkammaren skulle

59 6. Sammanfattning på svenska (Summary in Swedish) därför kunna utgöra en förbättring av metodiken. Med en sådan förbättring kunde information från elektronmätningar vara komplementärt till djuppro- filering genomförd med standard-MEIS. Detta skulle också möjliggöra mät- ningar av hur 2D-material som grafen reagerar på bestrålning med joner och vi har gjort första tester med lovande resultat. Fotoner som detekteras i MEIS-systemet har energier av bara några eV, vilket betyder att de skapas i elektroniska övergångar i valensbandet av provet. Fotonutbyte har mätts för olika experimentella inställningar och ett beroende av den kemiska omgivningen har fastställts. Den här informationen kan använ- das som ett komplement till identifiering av grundämnen som görs med MEIS. Spektroskopi av fotoner med energier i djup UV är dock tekniskt komplicerad och dyr och har inte gjorts i den här avhandlingen. I det sista avsnittet undersöks sputtringsprocesser vid medelhöga energier. Det är möjligt att identifiera massan av sputtrade positiva joner genom att mä- ta deras flygtid i ett applicerat elektriskt fält. Både sputtrade joner från provet självt och från föroreningar på ytan har detekterats. Sputtring av provatomer verkar ske på samma sätt som vid lägre energier, det vill säga via kaskader in- ducerade av kollisioner mellan atomkärnor. Sputtring av föroreningar å andra sidan verkar utlösas av energiöverföring till provets elektroner. Metoden verkar vara mycket känslig för att detektera föroreningar och tillsammans med rengöringsmetoder i vakuum skulle detta kunna bidra till karakterisering av ytor i MEIS-systemet.

60 Acknowledgements

Finally, I would like to acknowledge everyone who contributed to this work in one way or another and to thank everyone who accompanied and supported me during this time. Dankeschön and tack så mycket to all of you! I especially want to mention the following people: First and foremost, I want to thank my supervisor Daniel Primetzhofer for giv- ing me the opportunity to work on this PhD project. You have contributed to this work in too many ways to mention them all. Thank you for your help and guidance and your always open door! Andreas Wucher, who kindly agreed to be my opponent, as well as the mem- bers of the examination committee, Henrik Bergsåker, Andrea Sand, Kristina Stenström and Henrik Sjöstrand. I appreciate your time and effort. I also like to mention Göran Ericsson who agreed to chair the examination and who has been most helpful with regard to organisational issues. To everyone who has been working in the Ion Physics group and at the Tandem laboratory within the past 4+ years: It’s mostly been an immense pleasure to work with you! Thank you for creating such a nice atmosphere both at work and outside the lab (Social group’s the best group!). Barbara, for being such a fantastic ofﬁce mate, colleague, conference compan- ion, and most of all, friend. Thank you for everything! Mauricio, I think it’s been a lucky coincidence that we both started working in Uppsala at almost the same time. Thanks for help with and collaboration on the MEIS set-up, but even more for being such a great friend. Sotiris, Melanie and Carl-Johan for providing me with those keV ion beams (and nice conversations in the control room). At this point, I would also like to acknowledge the astonishing ability of Dan to solve every technical problem. Anna and Vincent for staying long evenings in the lab with me for chasing electrons. Radek, thanks for the great collaboration in the past months, I hope we continue this way! Barbara and Marcos proofread this thesis. Their suggestions only made it better. All errors are fully my responsibility. Everyone who has been active in PhD student representation at UU. It’s been an honour to work together with you. Keep up the good work!

61 Acknowledgements

Thanks to everyone in the Lindy Hop community in Uppsala for sharing the joy of dancing. Special shout out to Ben for introducing me to this fantastic dance (and also for ﬁka company, emergency chocolate, etc.)! My old and new friends in Germany, Sweden and all over the world. Just thank you for being you, and making life so much more worth living. If you read the thesis and didn’t just jump straight to the acknowledgements, you hopefully learned that the cover shows an ion transmitted through a silicon crystal. It can also be read as an homage to Ólafur Arnalds, whose music keeps inspiring me in so many ways. I wouldn’t be where I am today without the everlasting love and support of my family. Danke!

Uppsala, May 10, 2020

Svenja Lohmann

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