This dissertation investigates the complex defect diffusion behaviors in concentrated solid solution alloys (CSAs) including high-entropy alloys (HEAs), which are critical for understanding their exceptional mechanical and radiation-resistant properties. Through a combination of multiple atomistic-level simulation techniques and novel machine learning methods, this work reveals how the intricacies of local atomic arrangements and chemical heterogeneities influence diffusion processes, thereby offering new insights into alloy design and optimization. The research initially focuses on the vacancy-mediated diffusion employing binary Ni-Fe concentrated alloys as model systems. To evaluate the impact of local chemical short-range orders (SROs) on vacancy diffusion, both random solid solution configurations and alloys with SROs are prepared using hybrid molecular dynamics (MD) and metropolis Monte Carlo (MMC) methods. The results demonstrates that the development of SROs can significantly impede vacancy-mediated diffusion and enhance the chemically biased diffusion between Fe and Ni sites. Such findings suggest that the diffusion behavior in CSAs can be intricately controlled by adjusting the chemical ordering, a principle that could revolutionize alloy design strategies. Moreover, the study establishes a linear correlation between changes in the enthalpy of mixing and the formation of SROs, indicating that the reduction of enthalpy of mixing towards the more negative direction within an alloy system acts as a driving force for the observed diffusional slowdown. Advancing the methodological frontier, this dissertation introduces a state-of-the-art approach that integrates machine learning (ML) with kinetic Monte Carlo (KMC) simulations to efficiently investigate the controversial phenomenon of "sluggish diffusion" in concentrated alloys. As the first step, the Ni-Fe concentrated alloys are used as model systems. The complexity of defect diffusion in varying local atomic environment in CSAs makes it impractical to apply the standard nudged elastic band (NEB) method for on-the-fly determination of defect migration barriers at each step. By developing an artificial neural network (ANN) model trained on a dataset of NEB-computed migration barriers, it enables precise, efficient, and on-the-fly predictions of vacancy migration barriers for arbitrary local atomic environments during KMC simulations, including both random solution configuration and alloys with SROs. The diffusivities derived from this ANN-KMC modeling closely align with those from independent MD and temperature-accelerated dynamics (TAD) simulations at their accessible temperatures. The research delves into the sluggish diffusion mechanisms over the entire composition range of the Ni-Fe alloy system, elucidating them through the lens of ANN-KMC-derived insights at both high and low temperatures. The exploration then extends to quinary FeNiCrCoCu HEAs, utilizing a similar but improved ANN model to predict vacancy migration barriers across a wide compositional range. Due to the challenges of exploring the vast HEA compositional space, to date most experimental and computational studies have been limited to equiatomic compositions. This model, remarkably effective despite being trained solely on equiatomic HEA data, accurately predicts vacancy migration barriers in non-equiatomic compositions and their binary to quinary subsystems. Implementing this ANN model as an on-the-fly barrier calculator for KMC simulations, such ANN-KMC framework derives diffusivities nearly identical to the those from independent MD simulations but with far higher efficiency. This capability facilitates an extensive study of over 1,500 HEA compositions, uncovering the presence of sluggish diffusion in many non-equiatomic compositions. The analysis provides critical insights into the interplay between compositions, complex potential energy landscape, and percolation effect of the faster diffuser (i.e., Cu) on sluggish diffusion behaviors, offering invaluable perspectives for experimental alloy design and development. Lastly, the dissertation delves into interstitial-mediated diffusion in FeNiCrCoCu HEAs, confirming the presence of sluggish interstitial diffusion by comparing the equiatomic HEA with a range of reference systems. To study the non-monotonic concentration dependences in interstitial diffusion, a machine learning KMC (ML-KMC) method has been developed to simulate 〈100〉 dumbbell interstitial diffusion across various HEA compositions. Diverging from conventional KMC (C-KMC) and random sample KMC (RS-KMC) approaches, which approximate transition energies through a mean-field and random sampling methods, respectively, the ML-KMC predicts dumbbell formation energy on-the-fly based on local atomic configurations. This enables it to effectively replicate diffusion patterns from independent MD simulations. This novel ML-KMC approach offers a promising high-throughput method for studying HEAs, avoiding the expensive computational overhead associated with calculating dumbbell migration barriers. The impact of the percolation effect of faster diffusing elements (Cr, Cu) is also analyzed. Insights from this study can advance the understanding of compositional-dependent diffusion and provide valuable insights for the HEA design. Beyond the achievement of these completed works, two promising future projects have been evaluated that could significantly advance the field of diffusion research. The first initiative seeks to broaden the scope of the ANN-KMC framework, aiming to significantly enhance simulation efficiency across a broad range of HEA compositions. An accurate ANN model for predicting interstitial migration barriers has already been developed, and its full integration into the KMC framework could enable more accurate diffusion simulations. The second project aims to develop a comprehensive ML interatomic potential tailored specifically for HEAs, intended to improve the predictive accuracy of MD simulations. Although progress has been made in modeling an equiatomic CoCrFeMnNi HEA, constructing a robust ML potential for HEAs faces substantial challenges, primarily due to the extensive data requirements and computational demands. / Doctor of Philosophy / This dissertation investigates the complex defect diffusion behaviors in concentrated solid solution alloys (CSAs) including high-entropy alloys (HEAs), which are critical to understanding their exceptional mechanical and radiation-resistant properties. Through a combination of multiple simulation techniques and novel machine learning methods, this work reveals how the intricacies of local atomic arrangements and chemical heterogeneities influence diffusion processes, thereby offering new insights into alloy design and optimization. The research initially focuses on the complex vacancy diffusion mechanism in concentrated Ni-Fe alloys, demonstrating that local chemical short-range orders (SROs) significantly impede vacancy-mediated diffusion. Such findings suggest that the diffusion behavior in CSAs can be intricately controlled by adjusting the chemical ordering, a principle that could revolutionize alloy design strategies. Moreover, the study revealed a linear correlation between changes in the enthalpy of mixing and the formation of SROs, indicating that the enthalpy of mixing may be important for the diffusional behavior in CSAs. Advancing the methodological frontier, this dissertation introduces a cutting-edge approach that integrates machine learning (ML) with kinetic Monte Carlo (KMC) simulations to efficiently investigate the controversial "sluggish diffusion" phenomenon using Ni-Fe concentrated alloys as the initial model systems. By developing an artificial neural network (ANN) model trained on pre-calculated migration barriers using the standard nudged elastic band (NEB) method, this approach enables precise, efficient, and on-the-fly predictions of vacancy migration barriers for arbitrary local atomic environments, including both random solution configuration and alloys with SROs. The diffusivities obtained from this ANN-KMC modeling closely align with independent molecular dynamics (MD) and temperature-accelerated dynamics (TAD) simulations at their accessible temperatures, but with a far better efficiency. The ANN-KMC approach is then extended to non-equiatomic FeNiCrCoCu HEAs. An improved ANN model is developed to predict vacancy migration barriers across a wide compositional range. This model, remarkably effective despite being trained solely on equiatomic HEA data, accurately predicts vacancy migration barriers in non-equiatomic compositions and their binary to quinary subsystems. This capability facilitates an extensive study of over 1,500 HEA compositions, uncovering the presence of sluggish diffusion in many non-equiatomic compositions. The analysis provides critical understanding of the diffusion behavior in a vast compositional space, offering invaluable insights for experimental alloy design and development. Lastly, the dissertation delves into interstitial-mediated diffusion in FeNiCrCoCu HEAs, confirming the presence of sluggish interstitial diffusion. A machine learning KMC (ML-KMC) method has been developed to simulate 〈100〉 dumbbell interstitial diffusion across various HEA compositions, closely replicating diffusion patterns as independent MD simulations. This novel ML-KMC approach offers a promising high-throughput method for studying HEAs, avoiding the expensive computational overhead associated with calculating migration barriers. The impact of the percolation effect of faster diffusing elements (Cr, Cu) is also analyzed. Regarding future research directions, two promising projects are evaluated. The first expands the ANN-KMC framework to render more accurate interstitial diffusion simulations, and the second focuses on developing a ML potential for an equiatomic CoCrFeMnNi HEA. The progresses and challenges are discussed.

In this study, we have investigated the relationship between the process-microstructure to predict and modify the material's properties. Understanding these relationships allows the identification and correction of processing deficiencies when the desired properties are not achieved, depending on the microstructure. Hence, the co-relation between process-microstructure-properties helped reduce the number of experiments, materials & tool costs and saved much time. In the case of high entropy alloys, friction stir welding (FSW) causes improved strength due to the formation of fine grain structure and phase transformation from f.c.c to h.c.p. The phase transformation is temperature sensitive and is studied with the help of differential scanning calorimetry (DSC) to calculate the enthalpy experimentally to obtain ΔGγ→ε. The second process discussed is heat treatment causing precipitation evolution. Fundamental investigations aided in understanding the influence of strengthening precipitates on mechanical properties due to the aging kinetics – solid solution and variable artificial aging temperature and time. Finally, in the third case, the effect of FSW parameters causes the thermal profile to be generated, which significantly influences the final microstructure and weld properties. Therefore, a computational model using COMSOL Multiphysics and TC-Prisma is developed to generate the thermal profile for different weld parameters to understand its effect on the microstructure, which would eventually affect and predict the final properties of the weld. The model's validation is done via DSC, TEM, and mechanical testing.

High entropy alloys (HEAs) or complex concentrated alloys (CCAs) represent a new paradigm in structural alloy design. Molten salt corrosion behavior was studied for single-phase HEAs such as TaTiVWZr and HfTaTiVZr, and multi-phase HEAs such as AlCoCrFeNi2.1. De-alloying with porosity formation along the exposed surface and fluxing of unstable oxides were found to be primary corrosion mechanisms. Potentiodynamic polarization study was combined with systematic mass–loss study for TaTiVWZr, HfTaTiVZr, and AlCoCrFeNi2.1 as a function of temperature. Electrochemical impedance spectroscopy (EIS) was used for monitoring the corrosion of TaTiVWZr and HfTaTiVZr in molten fluoride salt at 650 oC. TaTiVWZr and AlCoCrFeNi2.1 showed low corrosion rate in the range of 5.5-7.5 mm/year and low mass-loss in the range of 35-40 mg/cm2 in molten chloride salt at 650 oC. Both TaTiVWZr and HfTaTiVZr showed similar mass loss in the range of 31-33 mg/cm2, which was slightly higher than IN 718 (~ 28 mg/cm2) in molten fluoride salt at 650 oC. Ta-W rich dendrite region in TaTiVWZr showed higher corrosion resistance against dissolution of alloying elements in the molten salt environment. AlCoCrFeNi2.1 showed higher resistance to galvanic corrosion compared to Duplex steel 2205 in molten chloride salt environment. These results suggest the potential use of HEAs/CCAs as structural materials in the molten salt environment for concentrating solar power and nuclear reactor systems.

In this dissertation, tribo-corrosion behavior of several single-phase and multi-phase high entropy alloys were investigated. Tribo-corrosion of body centered cubic MoNbTaTiZr high entropy alloy in simulated physiological environment showed very low friction coefficient (~ 0.04), low wear rate (~ 10-8 mm3/Nm), body-temperature assisted passivation, and excellent biocompatibility with respect to stem cells and bone forming osteoblast cells. Tribo-corrosion resistance was evaluated for additively manufactured face centered cubic CoCrFeMnNi high entropy alloy in simulated marine environment. The additively manufactured alloy was found to be significantly better than its as-cast counterpart which was attributed to the refined microstructure and homogeneous elemental distribution. Additively manufactured CoCrFeMnNi showed lower wear rate, regenerative passivation, less wear volume loss, and nobler corrosion potential during tribo-corrosion test compared to its as-cast equivalent. Furthermore, in the elevated temperature (100 °C) tribo-corrosion environment, AlCoCrFeNi2.1 eutectic high entropy alloy showed excellent microstructural stability and pitting resistance with an order of magnitude lower wear volume loss compared to duplex stainless steel. The knowledge gained from tribo-corrosion response and stress-corrosion susceptibility of high entropy alloys was used in the development of bio-electrochemical sensors to sense implant degradation. The results obtained herewith support the promise of high entropy alloys in outperforming currently used structural alloys in the harsh tribo-corrosion environment.

<p>Ni-based superalloys continue to exert themselves as the industry standards in high stress and highly corrosive/oxidizing environments, such as are present in a gas turbine engine, due to their excellent high temperature strengths, thermal and microstructural stabilities, and oxidation and creep resistances. Gas turbine engines are essential components for energy generation and propulsion in the modern age. However, Ni-based superalloys are reaching their limits in the operating conditions of these engines due to their melting onset temperatures, which is approximately 1300 °C. Therefore, a new class of materials must be formulated to surpass the capabilities Ni-based superalloys, as increasing the operating temperature leads to increased efficiency and reductions in fuel consumption and greenhouse gas emissions. One of the proposed classes of materials is termed refractory complex concentrated alloys, or RCCAs, which consist of 4 or more refractory elements (in this study, selected from: Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, and W) in equimolar or near-equimolar proportions. So far, there have been highly promising results with these alloys, including far higher melting points than Ni-based superalloys and outstanding high-temperature strengths in non-oxidizing environments. However, improvements in room temperature ductility and high-temperature oxidation resistance are still needed for RCCAs. Also, given the millions of possible alloy compositions spanning various combinations and concentrations of refractory elements, more efficient methods than just serial experimental trials are needed for identifying RCCAs with desired properties. A coupled computational and experimental approach for exploring a wide range of alloy systems and compositions is crucial for accelerating the discovery of RCCAs that may be capable of replacing Ni-based superalloys. </p> <p>In this thesis, the CALPHAD method was utilized to generate basic thermodynamic properties of approximately 67,000 Al-bearing RCCAs. The alloys were then down-selected on the basis of certain criteria, including solidus temperature, volume percent BCC phase, and aluminum activity. Machine learning models with physics-based descriptors were used to select several BCC-based alloys for fabrication and characterization, and an active learning loop was employed to aid in rapid alloy discovery for high hardness and strength. This method resulted in rapid identification of 15 BCC-based, four component, Al-bearing RCCAs exhibiting room-temperature Vickers hardness from 1% to 35% above previously reported alloys. This work exemplifies the advantages of utilizing Integrated Computational Materials Engineering- and Materials Genome Initiative-driven approaches for the discovery and design of new materials with attractive properties.</p> <p> </p> <p><br></p>

The main aim of this thesis was to design and develop new Aluminium based compositionally complex alloys (CCAs) using the high entropy alloy (HEA) concept, and to understand their evolution of microstructures during casting and also after the secondary process which is heat-treatment, and finally to evaluate their subsequent mechanical properties. Prior to the development of alloys, a computational technique ThermoCalc was used which helped in understanding the phase formation in various results. Use of thermodynamic physical parameters for predicting the stability of single-phase fields was done to assess their validity in predicting the compositional regions of the alloys developed. The first alloy developed is Al73.6Mg18Ni1.5Ti1.9Zr1Zn4 in at% (NiTiZrZn) CCA. The microstructure consists of the FCC as a primary phase with ~49% volume fraction along with β-AlMg and intermetallic (IM) phases including Al3Ni, Al3Ti, and Al3Zr. After casting, the microstructure showed some presence of eutectic structures. The Al3Ti, and Al3Zr IM phases seemed to precipitate early which led to less homogenization of Ti and Zr, causing deviation in the amount of these elements in the matrix. Further, the CCA was heat-treated at 375 oC for 24hrs and 48hrs and the evolution of microstructure along with its hardness and phase transformation characterisation was investigated. The second developed alloy was quaternary Al65.65Mg21.39Ag10.02Ni2.94 in at% (AgNi) CCA. In the as-cast state, the main phase (matrix) was FCC with ~64 % volume fraction along with BCC, β-AlMg and Al3Ni IM phases. There was a good level homogenization of all elements in the alloy. They were further heat- treated at 400 oC for 24 hrs and 48 hrs and were studied for any change in microstructure along with its hardness and thermal stability. This CCA had the highest hardness value from all developed CCAs. Lastly, in order to check how Ni affects the microstructure and properties of (AgNi) CCA, a ternary Al67.2Mg22.09Ag10.7 in at% (Ag) CCA was developed. The composition was kept such that it is exactly 97% by excluding the Ni. During the development of this alloy, the cast was cooled in two ways first being the normal cooled just like other CCAs and second being a fast cooling method. Both of these alloys consists of the FCC phase as a primary phase with 72% volume fraction along with BCC and β-AlMg. Both of them were also heat treated at 400 oC for 24 hrs and 48 hrs to evaluate any changes in microstructure and also to assess its hardness and thermal stability.

O desenvolvimento de novos materiais com baixa densidade e propriedades mecânicas estáveis em altas temperaturas é necessário para reduzir o consumo de combustível e consequentemente a emissão de gases no setor aeroespacial. Uma nova classe de materiais chamada HEAs (Ligas de Alta Entropia), que combinam elementos refratários e alumínio podem ser candidatas para superar esse desafio. Ligas de Alta Entropia contendo Al-Zr-Nb-Ti-V estão sendo estudadas em nosso grupo de pesquisa. Os diagramas de fases são uma ferramenta necessária para o desenvolvimento e otimização dessas ligas. O objetivo do presente trabalho é a investigação experimental do sistema ternário Al-V-Zr a 1200°C. Ligas do sistema foram fundidas em um forno a arco com cadinho de cobre refrigerado a água e eletrodo não consumível de tungstênio sob atmosfera de argônio. Pedaços das amostras foram embrulhados em folhas de Zr e tratadas a 1200°C por 10 dias usando tubos de sílica em vácuo primário para alcançar o equilíbrio termodinâmico. Para a observação das microestruturas, as amostras foram preparadas pelo método metalográfico padrão. A composição e microestrutura das amostras foram analisadas por microscopia eletrônica de varredura (MEV) e espectroscopia por energia dispersiva (EDS). A caracterização microestrutural das amostras foi complementada por difratometria de raios X (DRX) utilizando pó e radiação de Cu-K?. No trabalho publicado por Guzei (1993) foi proposto a existência de duas fases ternárias com estequiometria Zr0,9V0,4Al2,7 e Zr13V2Al5. Entretanto neste trabalho, apenas a fase ternária Zr0,9V0,4Al2,7 foi observada. Em contrapartida, observou-se a estabilidade uma outra fase ternária com estequiometria aproximada (Zr,Al)2V e protótipo Ti2Ni. Uma nova seção isotérmica a 1200°C foi proposta baseada no equilíbrio termodinâmico determinado pelas medições das composições das fases. / The development of new materials with low density and stable mechanical properties at high temperature is necessary to reduce fuel consumption and consequently the emission of gases. A new class of material called HEA combining refractory elements and aluminum can be good candidate to overcome this challenge. High entropy alloys in the Al-Zr-Nb-Ti-V system are being investigated in our research group. The phase diagram data are a necessary tool for the design and optimization of the alloys. The objective of these study is an experimental research of the Al-V-Zr ternary system at 1200°C. Several alloys were melted in an arc furnace using non-consumable tungsten electrode in a water cooled copper crucible, under an inert atmosphere of argonium. Parts of the samples were treated at 1200 °C for 10 days using silica tubes sealed under primary vacuum in order to achieve the thermodynamic equilibrium. For the observation of microstructures, the specimens were prepared following conventional metallographic methods. The compositions and microstructures of the alloys were investigated by scanning electron microscopy (SEM) and electronic microanalysis (EDS). The microstructural characterization was complemented by X-ray diffractrometry (XRD) on powder using Cu-k? radiation. In the work published by Guzei (1993) the existence of two ternary phases with the stoichiometry Zr0,9V0,4Al2,7 and Zr13V2Al5 is indicated. However, in this work only the ternary phase Zr0,9V0,4Al2,7 was observed. In addition, another ternary phase with approximate stoichiometry (Zr,Al)2V and prototype Ti2Ni was observed. A new isothermal section at 1200°C is proposed based on the thermodynamic equilibria determined to measured compositions of the phases.

O desenvolvimento de novos materiais com baixa densidade e propriedades mecânicas estáveis em altas temperaturas é necessário para reduzir o consumo de combustível e consequentemente a emissão de gases no setor aeroespacial. Uma nova classe de materiais chamada HEAs (Ligas de Alta Entropia), que combinam elementos refratários e alumínio podem ser candidatas para superar esse desafio. Ligas de Alta Entropia contendo Al-Zr-Nb-Ti-V estão sendo estudadas em nosso grupo de pesquisa. Os diagramas de fases são uma ferramenta necessária para o desenvolvimento e otimização dessas ligas. O objetivo do presente trabalho é a investigação experimental do sistema ternário Al-V-Zr a 1200°C. Ligas do sistema foram fundidas em um forno a arco com cadinho de cobre refrigerado a água e eletrodo não consumível de tungstênio sob atmosfera de argônio. Pedaços das amostras foram embrulhados em folhas de Zr e tratadas a 1200°C por 10 dias usando tubos de sílica em vácuo primário para alcançar o equilíbrio termodinâmico. Para a observação das microestruturas, as amostras foram preparadas pelo método metalográfico padrão. A composição e microestrutura das amostras foram analisadas por microscopia eletrônica de varredura (MEV) e espectroscopia por energia dispersiva (EDS). A caracterização microestrutural das amostras foi complementada por difratometria de raios X (DRX) utilizando pó e radiação de Cu-K?. No trabalho publicado por Guzei (1993) foi proposto a existência de duas fases ternárias com estequiometria Zr0,9V0,4Al2,7 e Zr13V2Al5. Entretanto neste trabalho, apenas a fase ternária Zr0,9V0,4Al2,7 foi observada. Em contrapartida, observou-se a estabilidade uma outra fase ternária com estequiometria aproximada (Zr,Al)2V e protótipo Ti2Ni. Uma nova seção isotérmica a 1200°C foi proposta baseada no equilíbrio termodinâmico determinado pelas medições das composições das fases. / The development of new materials with low density and stable mechanical properties at high temperature is necessary to reduce fuel consumption and consequently the emission of gases. A new class of material called HEA combining refractory elements and aluminum can be good candidate to overcome this challenge. High entropy alloys in the Al-Zr-Nb-Ti-V system are being investigated in our research group. The phase diagram data are a necessary tool for the design and optimization of the alloys. The objective of these study is an experimental research of the Al-V-Zr ternary system at 1200°C. Several alloys were melted in an arc furnace using non-consumable tungsten electrode in a water cooled copper crucible, under an inert atmosphere of argonium. Parts of the samples were treated at 1200 °C for 10 days using silica tubes sealed under primary vacuum in order to achieve the thermodynamic equilibrium. For the observation of microstructures, the specimens were prepared following conventional metallographic methods. The compositions and microstructures of the alloys were investigated by scanning electron microscopy (SEM) and electronic microanalysis (EDS). The microstructural characterization was complemented by X-ray diffractrometry (XRD) on powder using Cu-k? radiation. In the work published by Guzei (1993) the existence of two ternary phases with the stoichiometry Zr0,9V0,4Al2,7 and Zr13V2Al5 is indicated. However, in this work only the ternary phase Zr0,9V0,4Al2,7 was observed. In addition, another ternary phase with approximate stoichiometry (Zr,Al)2V and prototype Ti2Ni was observed. A new isothermal section at 1200°C is proposed based on the thermodynamic equilibria determined to measured compositions of the phases.

No description available.

Master‘s thesis deals with the preparation and evaluation single-phase high-entropy alloy based on cobalt, chromium, iron, nickel and manganese and its variants strengthened by dispersion of oxidic particles. High-entropy alloy was prepared in powder form by mechanical alloying from the equiatomic proportions of atomic powders. Obtained powder was subsequently compacted by spark plasma sintering. By the method of mechanical alloying were successfully prepared single-phase high-entropy alloy and its variant strengthened by dispersion of nanometric yttria oxides. It has been found that the oxide particles present in the microstructure of high-entropy alloy significantly block mobility of grain boundary and dislocation at elevated temperatures. As a result of this behavior were observed doubling of alloy strength and decreasing of creep rate at 800 °C.