Complex concentrated alloys (CCAs) offer the unique ability to tune composition and microstructure to achieve a wide range of mechanical performance. Recently, the development of metastable CCAs has led to the creation of transformation-induced plasticity (TRIP) CCAs. Similar to TRIP steels, TRIP CCAs are more effective at absorbing high strain rate loads when TRIP is activated during the loading process. The objective of our study is to investigate the effect of copper on the critical pressure for activating TRIP and the high pressure stability of a Fe(40-X)Mn20Cr15Co20Si5CuX TRIP CCA, where x varies from 0 to 3 at.% Cu. To achieve this goal, diamond anvil cell testing during in-situ synchrotron radiation X-ray diffraction was performed using both a monochromatic wide angle X-ray scattering (WAXS) beam and, for the first time ever, a polychromatic Laue diffraction beam on a CCA. Laue diffraction allows for real-time phase evolution tracking of the γ-fcc → ε-hcp transformation in a high pressure environment. Based on the results, a new method for processing and preparation of high pressure samples without changing the microstructure of sample was developed. This new method can be used to prepare any CCA samples for high pressure testing.

High entropy alloys (HEAs), also referred to as complex concentrated alloys (CCAs), are a relatively new class of alloys that have gained significant attention since 2010 due to their unique balance of properties that include high strength, ductility and excellent corrosion resistance. HEAs are usually based on five or more elements alloyed in near equimolar concentrations, and exhibit simple microstructures by the formation of solid solution phases instead of complex compounds. HEAs have great potential in the design of new materials; for instance, for lightweight structural applications and elevated temperature applications. The relation between grain size and yield strength has been a topic of significant interest not only to researchers but also for industrial applications. Though some research papers have been published in this area, consensus among them is lacking, as the studies yielded different results. Al atom being a large atom causes significant lattice distortion. This work attempts to study the Hall-Petch relationship for Al0.3CoFeNi and Al0.3CoCrFeNi and to compare the data of friction stress σ0 and Hall-Petch coefficient K with published data. The base alloys for both these alloys are CoFeNi and CoCrFeNi respectively. It was observed by atom probe tomography (APT) that clustering of Al-Ni atoms in these two base CCAs was responsible for imparting such high values of K. Additionally the high value of K in the CoCrFeNi HEA can also be attributed to the presence of Co-Cr clusters.

The current work investigates how the interactions among constituent elements in high entropy alloys or complex concentrated alloys (HEA/CCAs) can lead to lattice instability and local chemical ordering which in turn affects the microstructure and properties of these alloys. Using binary enthalpies of mixing, the degree of ordering in concentrated multi-component solid solutions was successfully tailored by introducing Cr, Al and Ti in a CoFeNi HEA/CCA. CoFeNi was selected as the base alloy to achieve a close to random solid solution as indicated by the near-zero binary enthalpies in CoFeNi alloy system. The room temperature tensile properties of these alloys with varied degree of ordering follow a consistent trend where yield stress increased with degree of ordering. This novel approach provides a new alloy design strategy to obtain controlled ordering tendencies and consequently targeted mechanical properties. Further studies on specific alloys have been conducted to utilize this ordering tendency in attaining precipitation strengthening. For this purpose, Al, Ti and Ni were selected to promote ordering and Co, Fe, and Cr were chosen to strengthen the solid solution matrix. In Al0.25CoFeNi HEA/CCA, the ordering tendency between Al and Ni results in a competition between two long-range ordered phases, L12 and B2. While homogenous L12 precipitation takes place at an annealing temperature of 500oC, heterogeneous B2 precipitation occurs at 700oC. At 600oC, this competition between L12 and B2 phases results in a novel nano-lamellar microstructure. The alternating lamellae are mainly FCC and BCC based whose morphology is similar to pearlite in steels. However, the FCC lamella is made up of FCC and L12 phases and the BCC lamella is made up of BCC and B2 phases. A different thermomechanical processing route can be used to obtain the same phase composition but distributed in a nano-grained fashion. This nano-grained microstructure exhibits the best strength-ductility combination in this alloy. Thermomechanical processing can also be used to engineer the transformation pathway of L12 from homogenous to discontinuous precipitation. The homogenous and discontinuous L12 precipitation has been investigated in two different alloys namely, Al0.2Ti0.3Co1.5CrFeNi1.5 and Al0.3Ti0.2Co0.7CrFeNi1.7. While discontinuous precipitation (DP) is generally considered deleterious to mechanical properties, the results from this study suggests that microstructures with DP perform better compared to homogenous L12 up to 500oC. However, beyond 500oC, microstructures with homogenous L12 appears to perform better than discontinuously precipitated FCC+L12 microstructure.

Vývoj nových materiálů pro součásti v moderních technologiích vystavené extrémním podmínkám má v současné době rostoucí význam. Děje se tak v důsledku neustále se zvyšujících požadavků průmyslových odvětví na lepší konstrukční vlastnosti nosných materiálů. Ve světle těchto faktů si tato studie klade za cíl posoudit nové složení slitin s vysokou entropií, které se vyznačují vysokým aplikačním potenciálem pro kritické aplikace. Slitiny jsou připravovány práškovou metalurgií, t.j. kombinací mechanického legování a slinování v pevné fázi. Pro účely srovnávaní vlastností jsou vybrané kompozice vyrobeny také tradičními metalurgickými metodami v roztaveném stavu, jako je vakuové indukční tavení a následné lití nebo vakuové obloukové tavení. Prášková metalurgie umožňuje postupný vývoj kompozitů s kovovou matricí (MMC) prostřednictvím přípravy oxidicky zpevněných HEA slitin. To je možné díky inherentním in-situ reakcím během procesu výroby. Když se naopak zvolí výrobní postup z taveniny, připravený kovový materiál vykazuje velké rozdíly v mikrostrukturách a souvisejících vlastnostech, v porovnání se stejným materiálem vyrobeným práškovou cestou (PM). Vyrobené práškové a tavené materiály jsou detailně charakterizovány s ohledem na komplexní vyhodnocení vlivu různých metod zpracování. Práce se zejména orientuje na mikrostrukturní charakteristiky materiálů a jejich mechanické vlastnosti, včetně vlivu tepelného zpracování na fázové transformaci a mikrostrukturní stabilitu připravených materiálů.

<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>

<p dir="ltr">Advancements in material science are accelerating technological evolution, driven by initiatives like the Materials Genome Project, which integrates computational and experi- mental strategies to expedite material discovery. In this work, we focus on the reliability of advanced materials under extreme conditions, a critical area for enhancing their technological applications.</p><p dir="ltr">Multi-principal component alloys (MPEAs) exhibit remarkable properties under extreme conditions. However, their vast compositional space makes a brute-force exploration of potential alloys prohibitive. We address this challenge by employing a Bayesian approach to explore the oxidation resistance of hundreds of alloys, applying computational techniques to accurately calculate and quantify errors in the melting temperatures of MPEAs, and investigating the compositional biases and short-range order in their nucleation behaviors.</p><p dir="ltr">Furthermore, we scrutinize the role of wide bandgap semiconductors, which are essential in high-power applications due to their superior breakdown voltage, drift velocity, and sheet charge density. The lack of lattice-matched substrates often results in strained films, which enhances piezoelectric effects crucial for device reliability. Our research advances the pre- diction of piezoelectric and dielectric responses as influenced by biaxial strain and doping in gallium nitride (GaN). Additionally, we delve into how various common defects affect the formation of trap states, significantly impacting the electronic properties of these materials. These studies offer significant advancements in understanding MPEAs and wide bandgap semiconductors under extreme conditions. We also provide foundational insights for developing robust and efficient materials essential for next-generation applications.</p>

<p>Co and Ni are two major elements in high temperature structural alloys that include superalloys for turbine engines and hard metals for cutting tools. The recent development of complex concentrated alloys (CCAs), loosely defined as alloys without a single principal element (e.g. CoNiFeMn), offers additional opportunities in designing new alloys through extensive composition and structure modifications. Within CCAs and Co- and Ni-based superalloys, solid-solution strengthening and stacking fault energy engineering are two of the most important strengthening mechanisms. While studied for decades, the potency and quantitative materials properties of these mechanisms remain elusive. </p> <p><br></p> <p>Solid-solution strengthening originates from stress field interactions between dislocations and solute of various species in the alloy. These stress fields can be engineered by composition modification in CCAs, and therefore a wide range of alloys with promising mechanical strength may be designed. This thesis initially reports on experimental and computational validation of newly developed theories for solid-solution strengthening in 3d transition metal (MnFeCoNi) alloys. The strengthening effects of Al, Ti, V, Cr, Cu and Mo as alloying elements are quantified by coupling the Labusch-type strengthening model and experimental measurements. With large atomic misfits with the base alloy, Al, Ti, Mo, and Cr present strong strengthening effects comparable to other Cantor alloys. </p> <p> </p> <p>Stacking fault energy engineering can enable novel deformation mechanisms and exceptional strength in face-centered cubic (FCC) materials such as austenitic TRIP/TWIP steels and CoNi-based superalloys exhibiting local phase transformation strengthening via Suzuki segregation. We employed first-principles calculations to investigate the Suzuki segregation and stacking fault energy of the FCC Co-Ni binary alloys at finite temperatures and concentrations. We quantitatively predicted the Co segregation in the innermost plane of the intrinsic stacking fault (ISF). We further quantified the decrease of stacking fault energy due to segregation.  </p> <p><br></p> <p>We further investigated the driving force of segregation and the origin of the segregation behaviors of 3d, 4d and 5d elements in the Co- and Ni-alloys. Using first-principles calculations, we calculated the ground-state solute-ISF interaction energies and revealed the trends across the periodic table. We discussed the relationships between the interaction energies and the local lattice distortions, charge density redistribution, density of states and local magnetization of the solutes. </p> <p><br></p> <p>Finally, this thesis reports on new methodologies to accelerate first-principles calculations utilizing active learning techniques, such as Bayesian optimization, to efficiently search for the ground-state energy line of the system with limited computational resources. Based on the expected improvement method, new acquisition strategies were developed and will be compared and presented. </p>