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Since the function of materials is controlled by properties and processes on the atomic scale, ab initio based high-throughput methods are valuable strategies in materials design. For computational efficiency, they are however often restriction to T=0K calculations, while many technologically relevant materials properties and thermodynamic stabilities change when going from low to high temperatures. On the other hand, the constantly increasing performance of digital tools for simulation and data-driven science enables more targeted material development including these kinds of finite-temperature effects. A flexible infrastructure, including data management and workflow solutions is required to make this symbiosis user-friendly efficient. Within this presentation, examples from ab initio thermodynamics for the design of phase stabilities in hard-magnetic alloys and defect-phases in advanced high-strength steels will be demonstrated. We will discuss physical concepts with a focus at the impact of magnetic excitations. At the same time, the examples will be used to derive requirements and present solutions for a digital infrastructure. An outlook will be given to current strategies with the NDFI initiative NFDI-MatWerk.
Thermodynamic bulk phase diagrams have become the roadmap used by researchers to identify alloy compositions and process conditions that result in novel materials with tailored microstructures. On the other hand, recent progress in experimental atomic-scale characterization techniques allows one to study the local chemical composition at individual defects such as interfaces, grain boundaries, dislocations and surfaces. They show that changes in the alloy composition can drive not only transitions in the bulk phases present in a material, but also in the concentration and type of defects they contain. Defect phase diagrams, using chemical potentials as thermodynamics variables, provide a natural route to study these chemically driven defects. Our results show, however, that the direct application of thermodynamic approaches can fail to reproduce the experimentally observed defect formation.
Therefore, we extend the concept to metastable defect phase diagrams to account for kinetic limitations that prevent the system from reaching equilibrium. We use ab initio calculations based on density functional theory to quantify the extension of regions where defect formation is expected. We successfully applied this concept to explain the formation of large concentrations of planar defects in supersaturated Fe2Nb Laves phases. In addition, we identify in a joint study with experiments conditions and structures in Mg-Al-Ca alloys for defect phase occurrence. The concept offers new avenues for designing materials with tailored defect structures.
Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable materials data space is therefore crucial in the digital transformation, both in academia and industry.
Therefore, the consortium NFDI MatWerk aims to develop a sustainable infrastructure for the standardized digital representation of materials science and engineering (MatWerk). The goal is to seamlessly integrate decentralized data and metadata, experimental and computational workflows, and a materials ontology to maximize interoperability and reproducibility of materials data processing. To this end, data use profiles of participant projects from different sub-disciplines are analyzed to identify the most relevant scientific scenarios within MatWerk.
Similarly, the Plattform MaterialDigital (PMD) is committed to provide a prototypical infrastructure for the digitalization of materials in an industrial context implemented by decentralized data servers, semantic data schemas and digital workflows. The standards, methods, and tools developed within the PMD are deployed and consolidated within the context of currently more than 20 BMBF-funded academic and industrial research consortia. Scientific workflow environments represent a major focus area, including efforts to improve the definition and representation of digital workflows, as well as their distribution in form of a workflow store.
In this presentation we will describe the overarching visions behind these initiatives, their status, and progress of dissemination with a focus on the workflow activities. Following the philosophy of both consortia, specific examples will be used to demonstrate innovative and pragmatic solutions.
Thermodynamic bulk phase diagrams have become the roadmap used by researchers to identify alloy compositions and process conditions that result in novel materials with tailored microstructures. On the other hand, recent progress in experimental atomic-scale characterization techniques allows one to study the local chemical composition at individual defects such as interfaces, grain boundaries, dislocations and surfaces. They show that changes in the alloy composition can drive not only transitions in the bulk phases present in a material, but also in the concentration and type of defects they contain. Defect phase diagrams, using chemical potentials as thermodynamics variables, provide a natural route to study these chemically driven defects. Our results show, however, that the direct application of thermodynamic approaches can fail to reproduce the experimentally observed defect formation.
Therefore, we extend the concept to metastable defect phase diagrams to account for kinetic limitations that prevent the system from reaching equilibrium. We use ab initio calculations based on density functional theory to quantify the extension of regions where defect formation is expected. We successfully applied this concept to explain the formation of large concentrations of planar defects in supersaturated Fe2Nb Laves phases. In addition, we identify in a joint study with experiments conditions and structures in Mg-Al-Ca alloys for defect phase occurrence. The concept offers new avenues for designing materials with tailored defect structures.
Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable materials data space is therefore crucial in the digital transformation of an industrial branch.
Therefore, the “Innovation Platform MaterialDigital (PMD) funded by the German Federal Ministry of Education and Research (BMBF), aims to develop a sustainable infrastructure for the standardized digital representation of materials science and materials engineering. With its partners (KIT, Fraunhofer IWM, FIZ, Leibnitz IWT, BAM, MPIE), the PMD is committed to build up a materials science data space. To achieve this the PMD provides a prototypical infrastructure for the digitalization of materials implemented by decentralized data servers, standardized data schemas and digital workflows. Following the FAIR principles, it will promote the semantic interoperability across the frontiers of materials classes.
Standards, methods, and tools developed within the platform are deployed and consolidated within the context of currently near 20 BMBF-funded academic and industrial research consortia and made available to the material science community in general. In this context scientific workflows represent a major focus area, represented within the platform by the workflow frameworks pyiron and SimStack. In consequence, the platform is building up a digital library in form of a workflow store along with common standards for the definition and representation of digital workflows.
In this presentation we will describe the status of our Platform MaterialDigital with a focus on the workflow activities. The current status and the vision for dissemination of the solutions developed in the PMD within the community are provided.
Material science problems have intrinsically multiscale and multiphysics characters, and require us to employ a combination of methods on different time and length scales to resolve critical features. Normally creating workflows that connect data in multiple scales and various methods is a cumbersome task. Pyiron, an integrated development environment (IDE) for material science, contains modules for the atomistic as well as continuum scale that make a seamless connection possible. To this end, it provides a high-level coherent language in a unified workflow platform to study materials, for example, with density functional theory (DFT) simulations in the same framework as with the finite element method (FEM). In this work, in addition to the introduction of different features in pyiron and its continuum module, a couple of exemplary workflows are demonstrated, bridging the scales in pyiron. One such workflow is analyzing the elastoplastic response of metallic alloys, where the elastic properties of the system are dependent on the atomistic composition and structure of the alloy. We use pyiron atomistics to model the dependence of elastic moduli on the atomistic composition of Al-Mg alloys. Benefiting from the integration of DAMASK in the continuum module of pyiron, the model can be used as an input to simulate the elastoplastic response of the alloy under various loadings. In addition, finite element simulations using the FEniCS package are currently integrated into the continuum module and will be demonstrated in the presentation.
Thermodynamic bulk phase diagrams have become the roadmap used by researchers to identify alloy compositions and process conditions that result in novel materials with tailored microstructures. Recent experimental studies show that changes in the alloy composition can drive not only transitions in the bulk phases present in a material, but also in the concentration and type of defects they contain. Defect phase diagrams in combination with density functional theory provide a natural route to study these chemically driven defects. Our results show, however, that direct application of thermodynamic approaches can fail to reproduce the experimentally observed defect formation. Therefore, we extend the concept to metastable defect phase diagrams to account for kinetic limitations that prevent the system from reaching equilibrium. We successfully applied this concept to explain the formation of large concentrations of planar defects in supersaturated Fe-Nb solid solutions and to identify in a joint study with experiments conditions in Mg-Al-Ca alloys for defect phase occurrence. The concept offers new avenues for designing materials with tailored defect structures.
Understanding segregation to grain boundaries, and eventually their defect phase diagrams, is critical to enable rational grain boundary engineering for alloys design. Here, we discuss the progress and challenges one may face when generating such a database of defect-solute interactions, in the context of studying of grain boundary segregation of solutes and impurities in Fe GBs. To compute the large number of relevant defect-solute interactions we have performed high-throughput ab initio calculations using efficient and highly automated workflows using pyiron. We study has been performed across a representative set of coincident-site-lattice (CSL) type tilt GBs. Based on the large ab-initio datasets, we extract and analyse the chemical and structural trends observed in the solute segregation behaviour across the periodic table. The features which are most important in evaluating site segregation are presented and discussed.
Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable materials data space is therefore crucial in the digital transformation and an important prerequisite for machine learning in materials science.
Therefore, the consortium NFDI MatWerk aims to develop a sustainable infrastructure for the standardized digital representation of materials science and engineering (MatWerk). The goal is to seamlessly integrate decentralized data and metadata, experimental and computational workflows, and a materials ontology to maximize interoperability and reproducibility of materials data processing. To this end, data use profiles of participant projects from different sub-disciplines are analyzed to identify the most relevant scientific scenarios within MatWerk.
Similarly, the Plattform MaterialDigital (PMD) is committed to provide a prototypical infrastructure for the digitalization of materials in an industrial context implemented by decentralized data servers, semantic data schemas and digital workflows. The standards, methods, and tools developed within the PMD are deployed and consolidated within the context of currently more than 20 BMBF-funded academic and industrial research consortia. Scientific workflow environments represent a major focus area, including efforts to improve the definition and representation of digital workflows, as well as their distribution in form of a workflow store.
In this presentation we will describe the overarching visions behind these initiatives, their status, and progress of dissemination with a focus on the workflow activities and the connection to machine learning applications. Following the philosophy of both consortia, specific examples will be used to demonstrate innovative and pragmatic solutions.
Since the function of materials is controlled by properties and processes on the atomic scale, ab initio based high-throughput methods are valuable strategies in materials design. For computational efficiency, they are however often restriction to T=0K calculations, while many technologically relevant materials properties and thermodynamic stabilities change when going from low to high temperatures. On the other hand, the constantly increasing performance of digital tools for simulation and data-driven science enables more targeted material development including these kinds of finite-temperature effects. A flexible infrastructure, including data management and workflow solutions is required to make this symbiosis user-friendly efficient. Within this presentation, examples from ab initio thermodynamics for the design of phase stabilities in hard-magnetic alloys and defect-phases in advanced high-strength steels will be demonstrated. We will discuss physical concepts with a focus at the impact of magnetic excitations. At the same time, the examples will be used to derive requirements and present solutions for a digital infrastructure. An outlook will be given to current strategies with the NDFI initiative NFDI-MatWerk.
Thermodynamic bulk phase diagrams have become the roadmap used by researchers to identify alloy compositions and process conditions that result in novel materials with tailored microstructures. On the other hand, recent progress in experimental atomic-scale characterization techniques allows one to study the local chemical composition at individual defects such as interfaces, grain boundaries, dislocations and surfaces. They show that changes in the alloy composition can drive not only transitions in the bulk phases present in a material, but also in the concentration and type of defects they contain. Defect phase diagrams, using chemical potentials as thermodynamics variables, provide a natural route to study these chemically driven defects. Our results show, however, that the direct application of thermodynamic approaches can fail to reproduce the experimentally observed defect formation.
Therefore, we extend the concept to metastable defect phase diagrams to account for kinetic limitations that prevent the system from reaching equilibrium. We use ab initio calculations based on density functional theory to quantify the extension of regions where defect formation is expected. We successfully applied this concept to explain the formation of large concentrations of planar defects in supersaturated Fe2Nb Laves phases. In addition, we identify in a joint study with experiments conditions and structures in Mg-Al-Ca alloys for defect phase occurrence. The concept offers new avenues for designing materials with tailored defect structures.
The effect of spin fluctuations on the α(bcc)-γ(fcc)-δ(bcc) structural phase transitions in iron is investigated with a tight-binding (TB) model. The orthogonal d-valent TB model is combined with thermodynamic integration, spin-space averaging, and Hamiltonian Monte Carlo to compute the temperature-dependent free-energy difference between bcc and fcc iron. We demonstrate that the TB model captures experimentally observed phonon spectra of bcc iron at elevated temperatures. Our calculations show that spin fluctuations are crucial for both the α−γ and γ−δ phase transitions but they enter through different mechanisms. Spin fluctuations impact the α−γ phase transition mainly via the magnetic/electronic free-energy difference between bcc and fcc iron. The γ−δ phase transition, in contrast, is influenced by spin fluctuations only indirectly via the spin-lattice coupling. Combining the two mechanisms, we obtain both the α−γ and γ−δ phase transitions with our TB model. The calculated transition temperatures are in very good agreement with experimental values.
Al3(Sc,Zr,Ti) nanoparticles with an ideal twin-type orientation relationship to Al host matrix were found in cold-rolled and subsequently annealed Al-based alloy. Atomic-scale investigations using high-resolution scanning transmission electron microscopy identified particles that form prominent coherent (111) twin-type interfaces along their longer facets and semi-coherent twin interfaces on their shorter facets. Ab-initio calculations showed that a coherent Al/Al3Sc twin-like phase boundary corresponds to a local energy minimum. A model is proposed explaining the formation of the twin orientation relationship of an Al3Sc nanoparticle with the Al host matrix.
La(FexSi1−x)13 and derived quaternary compounds are well-known for their giant, tunable, magneto- and barocaloric responses around a first-order paramagnetic-ferromagnetic transition near room temperature with low hysteresis. Remarkably, such a transition shows a large spontaneous volume change together with itinerant electron metamagnetic features. While magnetovolume effects are well-established mechanisms driving first-order transitions, purely electronic sources have a long, subtle history and remain poorly understood. Here we apply a disordered local moment picture to quantify electronic and magnetoelastic effects at finite temperature in La(FexSi1−x)13 from first-principles. We obtain results in very good agreement with experiment and demonstrate that the magnetoelastic coupling, rather than purely electronic mechanisms, drives the first-order character and causes at the same time a huge electronic entropy
contribution to the caloric response.
Tailoring negative pressure by crystal defects: Microcrack induced hydride formation in Al alloys
(2023)
Climate change motivates the search for non-carbon-emitting energy generation and storage solutions. Metal hydrides show promising characteristics for this purpose. They can be further stabilized by tailoring the negative pressure of microstructural and structural defects. Using systematic ab initio and atomistic simulations, we demonstrate that an enhancement in the formation of hydrides at the negatively pressurized tip region of the microcrack is feasible by increasing the mechanical tensile load on the specimen. The theoretical predictions have been used to reassess and interpret atom probe tomography experiments for a high-strength 7XXX-aluminium alloy that show a substantial enhancement of hydrogen concentration at structural defects near a stress-corrosion crack tip. These results contain important implications for enhancing the capability of metals as H-storage materials.
A giant Zn segregation transition is revealed using CALPHAD-integrated density-based modeling of segregation into Fe grain boundaries (GBs). The results show that above a threshold of only a few atomic percent Zn in the alloy, a substantial amount of up to 60 at.% Zn can segregate to the GB. We found that the amount of segregation abruptly increases with decreasing temperature, while the Zn content in the alloy required for triggering the segregation transition decreases. Direct evidence of the Zn segregation transition is obtained using high-resolution scanning transmission electron microscopy. Base on the model, we trace the origin of the segregation transition back to the low cohesive energy of Zn and a miscibility gap in Fe-Zn GB, arising from the magnetic ordering effect, which is confirmed by ab-initio calculations. We also show that the massive Zn segregation resulting from the segregation transition greatly assists with liquid wetting and reduces the work of separation along the GB. The current predictions suggest that control over Zn segregation, by both alloy design and optimizing the galvanization and welding processes, may offer preventive strategies against liquid metal embrittlement.
Ni-Mn-Ga shape-memory alloys are promising candidates for large strain actuation and magnetocaloric cooling devices. In view of potential small-scale applications, we probe here nanomechanically the stress-induced austenite–martensite transition in single crystalline austenitic thin films as a function of temperature. In 0.5 μm thin films, a marked incipient phase transformation to martensite is observed during nanoindentation, leaving behind pockets of residual martensite after unloading. These nanomechanical instabilities occur irrespective of deformation rate and temperature, are Weibull distributed, and reveal large spatial variations in transformation stress. In contrast, at a larger film thickness of 2 μm fully reversible transformations occur, and mechanical loading remains entirely smooth. Ab-initio simulations demonstrate how an in-plane constraint can considerably increase the martensitic transformation stress, explaining the thickness-dependent nanomechanical behavior. These findings for a shape-memory Heusler alloy give insights into how reduced dimensions and constraints can lead to unexpectedly large transformation stresses that need to be considered in small-scale actuation design.
One of the main challenges for the synthesis and application of the promising hard-magnetic compound CeFe11Ti is the formation of Laves phases that are detrimental for their thermodynamic stability and magnetic properties. In this paper, we present an ab initio based approach to modify the stability of these phases in the Ce-Fe-Ti system by additions of 3d and 4d elements. We combine highly accurate free-energy calculations with an efficient screening technique to determine the critical annealing temperature for the formation of Ce(Fe,X)11Ti. The central findings are the dominant role of the formation enthalpy at T = 0 K on chemical trends and the major relevance of partial chemical decompositions. Based on these insights, promising transition metals to promote the stability of the hard-magnetic phase, such as Zn and Tc, were predicted. The comparison with suction casting and reactive crucible melting experiments for Ce-Fe-Ti-X (X = Cu, Ga, Co, and Cr) highlights the relevance of additional phases and quaternary elements.
The influence of temperature and stacking fault energy (SFE) on the strain-hardening behavior and critical resolved shear stress for twinning was investigated for three Fe–22/25/28Mn–3Al–3Si wt.% transformation- and twinning-induced plasticity (TRIP/TWIP) steels. The SFEs were calculated by two different methods, density functional theory and statistical thermodynamic modeling. The dislocation structure, observed at low levels of plastic deformation, transitions from “planar” to “wavy” dislocation glide with an increase in temperature, Mn content, and/or SFE. The change in dislocation glide mechanisms from planar to wavy reduces the strain hardening rate, in part due to fewer planar obstacles and greater cross slip activity. In addition, the alloys exhibit a large decrease in strength and ductility with increasing temperature from 25 to 200 °C, attributed to a substantial reduction in the thermally activated component of the flow stress, predominate suppression of TRIP and TWIP, and a significant increase in the critical resolved shear stress for mechanical twinning. Interestingly, the increase in SFE with temperature had a rather minor influence on the critical resolved shear stress for mechanical twinning, and other temperature dependent factors which likely play a more dominant role are discussed.
Phase transitions are a common phenomenon in condensed matter and act as a critical degree of freedom that can be employed to tailor the mechanical or electronic properties of materials. Understanding the fundamental mechanisms of the thermodynamics and kinetics of phase transitions is, thus, at the core of modern materials design. Conventionally, studies of phase transitions have, to a large extent, focused on pristine bulk phases. However, realistic materials exist in a complex form; their microstructures consist of different point and extended defects. The presence of defects impacts the thermodynamics and kinetics of phase transitions, but has been commonly ignored or treated separately. In recent years, with the significant advances in theoretical and experimental techniques, there has been an increasing research interest in modeling and characterizing how defects impact or even dictate phase transitions. The present review systematically discusses the recent progress in understanding the kinetics of defect-characterized phase transitions, derives the key mechanisms underlying these phase transitions, and envisions the remaining challenges and fruitful research directions. We hope that these discussions and insights will help to inspire future research and development in the field.
We study single-site and two-site defect structures in B2-type Fe-Al alloys by means of density functional theory supercell calculations. The defect formation energies are calculated as functions of the chemical potential, which are used to obtain the dependence of the defect concentrations on Al content at different temperatures. We also examine the converging behavior of the formation energies with respect to the supercell size to study the corresponding limit of dilute defects. The effect of magnetism is investigated by considering nonmagnetic, ferromagnetic, and paramagnetic states, calculations for the latter showing that the magnitude of the local magnetic moments strongly impacts the defect formation energies. The methodological studies are used to provide explanations for the wide spread of defect formation energies reported by experiments and other theoretical investigations. Based on these insights, the stability of the B2-FeAl structure as a function of Al concentration is obtained and discussed.