<p dir="ltr">Since its inception, the field of heterogeneous catalysis has evolved to address the needs of the ever-growing human population. Necessity, after all, fosters innovation. Today, the world faces numerous challenges related to anthropogenic climate change, and that has necessitated, among other things, a search for new catalysts that can enable renewable energy conversion and storage, sustainable food and chemicals production, and a reduction in carbon emissions. This search has led to the emergence of many promising classes of materials, each having a unique set of catalytic properties. Among such candidate materials, high-entropy alloys (HEAs) have very recently shown the potential to be a new catalyst design paradigm. HEAs are multimetallic, disordered alloys containing more than four elements and, as a result, possess a higher configurational entropy, which gives them considerable stability. They have many conceivable benefits over conventional bimetallic alloy catalysts—greater site heterogeneity, larger design space, and higher stability, among others­. Consequently, there is a need to explore their application in a wide range of thermal and electrocatalytic reaction systems so that their potential can be realized.</p><p dir="ltr">In the past few decades, first principles-based approaches involving Density Functional Theory (DFT) calculations have proven to be effective in probing catalytic mechanisms at the atomic scale. Fundamental insights from first principles studies have also led to a detailed understanding of reactivity and stability trends for bimetallic alloy catalysts. However, the express application of first principles approaches to study HEA catalysts remains a challenge, due to the large computational cost incurred in performing DFT calculations for disordered alloys, which can be represented by millions of different configurations. A combination of first principles approaches and computationally efficient machine learning (ML) approaches can, however, potentially overcome this limitation.</p><p dir="ltr">In this thesis, combined workflows involving first principles and machine learning-based approaches are developed. To map catalyst structure to properties graph convolutional network (GCN) models are developed and trained on DFT-predicted target properties such as formation energies, surface energies, and adsorption energies. Further, the Monte Carlo dropout method is integrated into GCN models to provide uncertainty quantification, and these models are in turn used in active learning workflows that involve iterative model retraining to both improve model predictions and optimize the target property value. Dimensionality reduction methods, such as principal components analysis (PCA) and Diffusion Maps (DMaps), are used to glean physicochemical insights from the parameterization of the GCN.</p><p dir="ltr">These workflows are applied to the analysis of binary, ternary, and quaternary alloy catalysts, and a series of fundamental insights regarding their stability are elucidated. In particular, the origin and stability of “Pt skins” that form on Pt-based bimetallic alloys such as Pt₃Ni in the context of the oxygen reduction reaction (ORR) are investigated using a rigorous surface thermodynamic framework. The active learning workflow enables the study of Pt skin formation on stepped facets of Pt₃Ni (with a complex, low-symmetry geometry), and this analysis reveals a hitherto undiscovered relationship between surface coordination and surface segregation. In another study, an active learning workflow is used to identify the most stable bulk composition in the Pd-Pt-Sn ternary alloy system using a combination of exhaustively sampled binary alloy data and prudently sampled ternary alloy data. Lastly, a new GCN model architecture, called SlabGCN, is introduced to predict the sulfur poisoning characteristics of quaternary alloy catalysts, and to find an optimal sulfur tolerant composition.</p><p dir="ltr">On another front, the electrocatalytic activity of quinary HEAs towards the ORR is investigated by performing DFT calculations on HEA structures generated using the High-Entropy Alloy Toolbox (HEAT), an in-house code developed for the high-throughput generation and analysis of disordered alloy structures with stability constraints (such as Pt skin formation). DFT-predicted adsorption energies of key ORR intermediates are further deconvoluted into ligand, strain, and surface relaxation effects, and the influence of the number of Pt skins on these effects is expounded. A Sabatier volcano analysis is performed to calculate the ORR activities of selected HEA compositions, and correspondence between theoretical predictions and experimental results is established, to pave the way for rational design of HEA catalysts for oxygen reduction.</p><p dir="ltr">In summary, this thesis examines stability and reactivity trends of a multitude of alloy catalysts, from conventional bimetallic alloys to high-entropy alloys, using a combination of first principles approaches (involving Density Functional Theory calculations) and machine learning approaches comprising graph convolutional network models.</p>

The investigation of high-entropy alloys (HEAs) has revealed many promising properties. HEAs with a high share of Al and Ti are suitable for the formation of lightweight materials. Investigations of the alloy system AlCoCrFeNiTi showed high strength, hardness, ductility, and wear resistance, which makes this special alloy interesting for surface engineering and particularly for thermal spray technology. In this study, the suitability of inert gas-atomised HEA powder for high-velocity-oxygen-fuel (HVOF) thermal spray is investigated. This process allows for high particle velocities and comparatively low process temperatures, resulting in dense coatings with a low oxidation. The microstructure and phase composition of the atomised powder and the HVOF coating were investigated, as well as the wear behaviour under various conditions. A multiphase microstructure was revealed for the powder and coating, whereas a chemically ordered bcc phase occurred as the main phase. The thermal spray process resulted in a slightly changed lattice parameter of the main phase and an additional phase. In comparison with a hard chrome-plated sample, an increase in wear resistance was achieved. Furthermore, no brittle behaviour occurred under abrasive load in the scratch test. The investigation of wear tracks showed only minor cracking and spallation under maximum load.

This thesis deals with the influence of process parameters on the contamination level of powder materials produced by mechanical alloying (MA) technology. For this purpose austenitic stainless steel 316 L and equiatomic CoCrFeNi high-entropy alloy (HEA) were prepared by high-energy ball milling. Both materials were milled in argon and nitrogen atmospheres from 5 to 30 hours. Spark plasma sintering method (SPS) was then used for consolidation of chosen powder samples. Chemical analysis of contamination within MA was carried out using combustion analysers for determination of carbon, oxygen, and nitrogen contents after different lengths of milling. Also differences in chemical composition of powder and corresponding bulk samples were measured. The microstructure analysis using scanning electron microscopy (SEM) of both powder and bulk materials was executed with focus on oxide and carbide presence and dispersion. Increasing content of carbon with increasing milling time was observed across all measured samples. This contamination is attributed to using milling vial made of tool steel AISI D2 (containing 1,55 wt. % of carbon). Increase of carbon content within consolidation using SPS was also observed. Milling of specimens using N2 as milling atmosphere caused higher contamination level in both AISI 316 L and HEA compared to milling in argon.

High Entropy Alloy (HEA) is a class of construction steels based on the mixing of five or more elements in approximately equimolar ratios. Despite the ambiguity of their future use, HEAs represent a significantly new group of construction materials that are currently receiving a great deal of attention. Single-phase HEAs fail when used at elevated tempera-tures. The improvement of their high-temperature resistance was achieved by introducing a dispersion of oxides Al2O3 and Y2O3. To generalize the positive effect of dispersions on the mechanical properties at elevated temperatures, particles of a similar nature were cho-sen. These were dispersed particles of nitrides: hardness-incompatible AlN and hardness-compatible BN. The particles were evenly distributed inside the alloys by mechanical al-loying and compacted by SPS (Spark Plasma Sintering). The new structural alloy reached a density higher than 96.5 % and brought an increase in yield strength at room tempera-ture of up to 67 % and 40 % at elevated temperatures, while maintaining a homogeneous distribution of input powders.

Les alliages à haute entropie forment une nouvelle classe de matériaux découverts récemment et démontrant des propriétés physiques et mécaniques très prometteuses. Ces solutions solides à phase unique présentent une grande dureté, une haute résistance à la corrosion, une bonne résistance aux dommages causés par l’irradiation ionique et une phase stable même à température élevée. Pour ces raisons, ils ont attiré l’attention pour plusieurs utilisations potentielles, notamment dans la prochaine génération de réacteurs nucléaires. Dans ce mémoire, nous étudierons la diffusion de défauts ponctuels dans l’alliage de 55Fe-28Ni-17Cr. Ces défauts sont très fréquemment créés par l’irradiation par ion ayant lieu dans les cuves des réacteurs nucléaires. Nous profiterons de l’occasion d’étudier un alliage ayant une microstructure complexe afin d’introduire et de tester une méthode du calcul du taux de transition global et local se basant sur le calcul du facteur pré-exponentiel de la théorie de l’état de transition harmonique (hTST). Ces méthodes sont implantées dans la technique d’activation-relaxation cinétique, une méthode de Monte Carlo cinétique, que nous utiliserons pour réaliser la diffusion de défauts ponctuels dans l’alliage. Nous démontrons une différence importante entre le taux de transition calculé avec et sans hTST qui peut mener à une erreur dans les propriétés calculées de diffusion des défauts. Nous démontrons également que le facteur pré-exponentiel obéit à une anti-loi de compensation de Meyer-Neldel. Le calcul local du facteur pré-exponentiel est étudié et nous démontrons qu’il est capable de reproduire le taux global pour plusieurs événements. / High-entropy alloys are a novel class of materials discovered recently and demonstrating promising physical and mechanical properties. These single-phase solid solutions present a high hardness, a great resistance to corrosion, a good resistance to ion radiation damages and a stable phase even at high temperature. For these reasons they have attracted the attention for numerous potential uses, notably in the next generation of nuclear reactors. In this thesis, we study the diffusion of point defects in the 55Fe-28Ni-17Cr alloy. This kind of defect being very frequently created by irradiation in nuclear reactors. We will also use the occasion of having an alloy with a complex microstructure to add and test a method of computing the transition rate globally and locally based on the computation of the prefactor of the harmonic Transition State Theory (hTST). These additions will be made in the kinetic Activation-Relaxation Technique, a kinetic Monte Carlo method that will be used to study the diffusion of point defects in the alloy. We demonstrate that there is an important discrepancy between the rate computed with and without the hTST that can lead to an error in the computed diffusion properties of defects. We also show that the prefactor obeys an anti Meyer-Neldel compensation law. The local method to compute the prefactor is then studied and proven to be able to reproduce the global rate for a large number of events.

Alloying aluminum offers the possibility of creating low-density high-entropy alloys (HEAs). Several studies that focus on the system AlCoCrFeNiTi differ in their phase determination. The effect of aluminum on the phase composition and microstructure of the compositionally complex alloy (CCA) system AlxCoCrFeNiTi was studied with variation in aluminum content (molar ratios x = 0.2, 0.8, and 1.5). The chemical composition and elemental segregation was measured for the different domains in the microstructure. The crystal structure was determined using X-ray diffraction (XRD) analysis. To identify the spatial distribution of the phases found with XRD, phase mapping with associated orientation distribution was performed using electron backscatter diffraction. This made it possible to correlate the chemical and structural conditions of the phases. The phase formation strongly depends on the aluminum content. Two different body-centered cubic (bcc) phases were found. Texture analysis proved the presence of a face-centered cubic (fcc) phase for all aluminum amounts. The hard η-(Ni, Co)3Ti phase in the x = 0.2 alloy was detected via metallographic investigation and confirmed via electron backscatter diffraction. Additionally, a centered cluster (cc) with the A12 structure type was detected in the x = 0.2 and 0.8 alloys. The correlation of structural and chemical properties as well as microstructure formation contribute to a better understanding of the alloying effects concerning the aluminum content in CCAs. Especially in the context of current developments in lightweight high-entropy alloys (HEAs), the presented results provide an approach to the development of new alloy systems.

The investigation of high-entropy alloys (HEAs) has revealed many promising properties. HEAs with a high share of Al and Ti are suitable for the formation of lightweight materials. Investigations of the alloy system AlCoCrFeNiTi showed high strength, hardness, ductility, and wear resistance, which makes this special alloy interesting for surface engineering and particularly for thermal spray technology. In this study, the suitability of inert gas-atomised HEA powder for high-velocity-oxygen-fuel (HVOF) thermal spray is investigated. This process allows for high particle velocities and comparatively low process temperatures, resulting in dense coatings with a low oxidation. The microstructure and phase composition of the atomised powder and the HVOF coating were investigated, as well as the wear behaviour under various conditions. A multiphase microstructure was revealed for the powder and coating, whereas a chemically ordered bcc phase occurred as the main phase. The thermal spray process resulted in a slightly changed lattice parameter of the main phase and an additional phase. In comparison with a hard chrome-plated sample, an increase in wear resistance was achieved. Furthermore, no brittle behaviour occurred under abrasive load in the scratch test. The investigation of wear tracks showed only minor cracking and spallation under maximum load.

In this study, the wear behaviour of a powder metallurgically produced AlCoCrFeNiTi0.5 high-entropy alloy (HEAs) is investigated at elevated temperatures. Spark plasma sintering (SPS) of inert gas atomised feedstock enables the production of dense bulk material. The microstructure evolution and phase formation are analysed. The high cooling rate in the atomisation process results in spherical powder with a microstructure comprising two finely distributed body-centred cubic phases. An additional phase with a complex crystal structure precipitates during SPS processing, while no coarsening of microstructural features occurs. The wear resistance under reciprocating wear conditions increases at elevated temperatures due to the formation of a protective oxide layer under atmospherical conditions. Additionally, the coefficient of friction (COF) slightly decreases with increasing temperature. SPS processing is suitable for the production of HEA bulk material. An increase in the wear resistance at elevated temperature enables high temperature applications of the HEA system AlCoCrFeNiTi0.5.

Hochentropielegierungen stellen einen neuen Entwicklungsansatz metallischer Werkstoffe ohne ein eigenschaftsbestimmendes Hauptelement dar. Die zielgerichtete Übertragung der bisher überwiegend an Massivwerkstoffen ermittelten Eigenschaften in die Beschichtungstechnik erfordert die Kenntnis der bestimmenden Einflussfaktoren. Für die Schichtherstellung werden die Verfahren des thermischen Spritzens betrachtet. Hierfür wird eine geeignete Prozessroute ermittelt. Die detaillierten Untersuchungen zu den Prozess-Struktur-Eigenschaftsbeziehungen erfolgen an Legierungen mit variabler Struktur. Diese werden anhand von thermodynamischen Parametern sowie Untersuchungen an schmelzmetallurgisch hergestellten Massivwerkstoffen ausgewählt. Zur Bewertung des Einflusses der Größe der Strukturmerkmale, der Heterogenität und möglicher Ungleichgewichtszustände werden schmelz- und pulvermetallurgisch hergestellte Massivwerkstoffe als Referenz betrachtet. Die geplanten Forschungsarbeiten tragen zu einem Verständnis der Prozess-Struktur-Eigenschaftsbeziehung von Hochentropielegierungen bei. Weiterhin wird eine geeignete Prozessroute für die pulvermetallurgische Verarbeitung sowie für Anwendungen in der Oberflächentechnik ermittelt.

Les alliages à haute entropie (HEAs) sont des alliages métalliques composés de 5 éléments ou plus, présents en proportions equimolaire ou presque. Depuis leur apparition dans le domaine de la métallurgie, leurs propriétés intéressantes ont causé un intérêt croissant de la part de la communauté scientifique pour essayer de les comprendre et les prédire. Plusieurs de ces propriétés peuvent aussi être observées dans d'autres systèmes cristallins ayant moins d'éléments, comme les solutions solides concentrées (CSAs) composées de FeNiCr. Ce mémoire présente les effets du calcul des préfacteurs par l'approximation harmonique de la théorie de l'état de transition (hTST) sur la diffusion d'une lacune dans une CSA en FeNiCr modélisée par un algorithme Monte-Carlo cinétique (KMC) hors réseau. Ce travail est motivé par les nombreux débats qui entourent la diffusion lente dans les HEAs et autres CSAs hautement désordonnés. Bien que cette caractéristique ait été proposée et utilisée pour expliquer certaines des propriétés les plus intéressantes des HEAs, les mécanismes de diffusion dans ceux-ci sont encore mal compris. Dans des travaux précédents, il a été démontré que les préfacteurs hTST dans une CSA FeNiCr peuvent avoir des valeurs qui s'étalent sur plusieurs ordres de grandeur. En partant de ces résultats, l'influence de cette variation de préfacteurs sur la diffusion d'une lacune est étudiée. Grâce à une analyse comparative entre des simulations utilisant des préfacteurs hTST et constants, le rôle de l'entropie dans la diffusion est étudié. Plus de un millions d'évènements au total sont trouvés dans les 96 simulations effectuées dans chaque type de simulation, fournissant une base statistique solide. Ces simulations KMC ont été performées par l'algorithme d'activation-relaxation cinétique (kART) couplé au potentiel Bonny-2013 pour les calculs de surface d'énergie potentielle (PEL). Nous démontrons que, en plus de l'entropie configurationnelle, le désordre affecte aussi l'entropie vibrationnelle, et que ce phénomène peut être à la base de diverses propriétés de ces systèmes, y compris leur diffusion lente. Les résultats présentés ne peuvent être obtenus que grâce à une analyse cinétique du système. En effet, la dynamique obtenue ne peut pas être extraite directement de l'évaluation statique du PEL, car la corrélation de sélection des événements est construite à partir des contributions combinées du préfacteur et des barrières énergétiques. Cette combinaison affecte la loi de compensation qui est mesurée, selon si le calcul de cette loi est effectué avec les évènements qui sont disponibles ou avec les évènements sélectionnés. Une introduction, ainsi que deux chapitres sur les HEAs et sur la théorie de l'état de transition débutent ce travail, suivis de la méthodologie, présentée au chapitre 4, et de l'article au chapitre 5. / High entropy alloys (HEAs) are metallic alloys composed of 5 or more elements, present in equimolar or near equimolar proportions. Since their appearance in the field of metallurgy at the beginning of the XXIst century, their properties have caused a growing interest from the scientific community in order to understand and predict certain of these properties. Many of them can also be observed in other crystalline systems with fewer elements, such as concentrated solid solution (CSAs) composed of FeNiCr. This masters' thesis presents the effect that the computation of prefactors by the harmonic approximation of the transition state theory (hTST) has on the diffusion of a single vacancy in a FeNiCr CSA, simulated by a kinetic Monte Carlo algorithm (KMC). The debate around a sluggish defect diffusion, proposed as a core effect of HEAs and CSAs with high amounts of disorder motivates this research. Indeed, even though this characteristic is often used to explain some of the most interesting properties of HEAs, the diffusion mechanisms are still not fully comprehended. In a previous study, it was demonstrated that hTST prefactors span over several orders of magnitude. Based on these results, we study the impact of hTST on diffusion. Through a comparative analysis between simulations using hTST and constant prefactors, the role of entropy on diffusion is studied. More than one million events in total are found in the 96 simulations performed for each type of simulation, providing a solid statistical basis for this analysis. These KMC simulations were performed by the kinetic activation-relaxation technique (kART) coupled with the Bonny-2013 potential for potential energy landscape (PEL) calculations. We demonstrate that both disorder and configurational entropy strongly affect the vibrational entropy, and that this can be responsible for various properties of these systems, including their sluggish diffusion. Presented results can only be obtained by a kinetic study of the system. The kinetic patterns that are observed can not be obtained by only the static analysis of the PEL for the combination of both prefactors and energy barriers affects event selection. This selection of events can change the compensation law that is measured whether it is computed using available events or selected events. Two chapters on HEAs and transition state theory, as well as a chapter on the methodology are presented before these results.