6.4 Materialinformatik
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The microstructure of advanced high-strength steels often shows a sensitive dependence on alloying. For example, adding Cr to improve the corrosion resistance of medium-Mn steels also enhances the precipitation of carbides. The current study focuses on the behavior of H in such complex multicomponent carbides by employing different methodological strategies. We systematically analyze the impact of Cr, Mn, and Fe using density functional theory (DFT) for two prototype precipitate phases, M3C and M23C6, where M represents the metal sublattice. Our results show that the addition of these alloying elements yields strong nonmonotonic chemical trends for the H solubility. We identify magnetovolume effects as the origin for this behavior, which depend on the considered system, the sites occupied by H, and short- vs long-range interactions between H and the alloying elements. We further show that the H solubility is directly correlated with the occupation of its nearest-neighbor shells by Cr and Mn. Based on these insights, DFT data from H containing binary-metal carbides are used to design a ridge regression based model that predicts the solubility of H in the ternary-metal carbides (Fe-Cr-Mn-C).
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.
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.
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.
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.
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.
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.
Tungsten-tungsten carbide (W/W2C) composites are considered as possible structural materials for future nuclear fusion reactors. Here, we report on the effect of helium (He) implantation on microstructure evolution of polycrystalline W/W2C composite consolidated by field-assisted sintering technique (FAST), homogenously implanted at room temperature with 1 MeV 4He+ ions at the fluence of 8 × 1016 ions cm−2 and annealed at 1873 K for 20 minutes. Samples were analysed by scanning and transmission electron microscopy to study the presence and size of He bubbles. Monomodal He bubbles in W (30-80 nm) are limited to point defects and grain boundaries, with a considerable void denuded zone (150 nm). Bubbles do not form in W2C, but at the W|W2C interface and are considerably larger (200-400 nm). The experimental observations on He behaviour and migration in W and W2C were assessed by density functional theory (DFT) calculations, suggesting He migration and accumulation in the composite are determined by the effective He-He binding in clusters, which will give rise to decohesion. In the presence of He clusters, the decohesion of bulk W into free surfaces is energetically highly favourable but not sufficient in the W2C; hence bubbles are only observed in W grains and interfaces and not within bulk W2C.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
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.
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.
The energy crisis becomes more prominent in higher altitude countries like Germany, with higher annual energy demand. Thus, the generation of higher energy density fuel like hydrogen from renewable resources become the only way to solve the zero-emission energy system while avoiding the expensive batteries as an energy storage option. Therefore, water electrolysis cells to produce hydrogen and oxygen by storing of solar/wind energy in chemical bonds is a fruitful alternative for renewable and long-term energy generation. Thus, designing inexpensive water-splitting electrocatalyst material becomes a field of research of utmost importance. High entropy metal hydroxide organic frameworks (HE-MHOFs) are composed of high entropy hydroxide layer inside MOFs, resulting in a high degree of structural complexity and diversity than conventional MOFs. The concept of ‘high entropy’ refers to multiple types of metal ions (Metal = TM) in a near equimolar ratio in the same framework, creating a high degree of disorder and many possible structural configurations. Here, the HE-MHOF successfully synthesized by a conventional solvothermal process, crystallizes in the single phase with significant lattice distortion. A special-quasi-random (SQS) structure was simulated with equimolar compositions (~20% TM = Mn, Co, Ni, Cu and Zn) and a comparison was made with the ICP-AES (inductively coupled plasma atomic emission spectroscopy), XANES (X-ray absorption near edge structure) and XAFS (X-ray absorption fine structure) observations. Further, the elemental mapping (Energy dispersive Spectroscopy) of HE-MHOF shows the presence of all five different metals in the same crystallite to substantiate the ‘high entropy’ state of the MOF. The HE-MHOF offers improved thermal stability than mono-metallic MHOF and exhibit unique properties compared to traditional monometallic (Ni2+) MOF variants. Firstly, to elucidate the effect of the multimetallic system on the catalytic performance, we have performed density functional theory (DFT) calculations to investigate pre-redox cycles involved in the catalytic activation of HE (and Ni)-MOFs. HE-MHOF is further investigated as an electrocatalyst for oxygen evolution reaction (OER) due to its special high entropy hydroxide layered structure and electronic properties. Our DFT results have examined the traditional proton-coupled electron transfer (PCET) steps involving the single transition-metal site. The scrutiny of d-band centers and their behaviour in catalytic upgradation is investigated with density of states (DOS) analysis. It exhibits outstanding performance towards oxygen evolution reaction (OER) comparable to the experimental findings, which is also comparable to state-of-the-art OER catalysts based on precious metals such as iridium oxide and platinum carbon. We have considered different electrolyte solutions to elucidate the fast kinetics oxygen evolution reaction in the presence of various external nucleophilic anions. In hydroxyl-based MOFs, electrolytes' influence can substantially enhance catalytic activities. Here, with the help of DFT simulations, we have investigated the effect of the nucleophilicity of anion on each elementary reaction involved in the PCET mechanism of OER.
Ever more stringent regulations on greenhouse gas emissions from transportation motivate efforts to revisit materials used for vehicles. High-strength aluminium alloys often used in aircrafts could help reduce the weight of automobiles, but are susceptible to environmental degradation. Hydrogen ‘embrittlement’ is often indicated as the main culprit; however, the exact mechanisms underpinning failure are not precisely known: atomic-scale analysis of H inside an alloy remains a challenge, and this prevents deploying alloy design strategies to enhance the durability of the materials. Here we performed near-atomic-scale analysis of H trapped in second-phase particles and at grain boundaries in a high-strength 7xxx Al alloy. We used these observations to guide atomistic ab initio calculations, which show that the co-segregation of alloying elements and H favours grain boundary decohesion, and the strong partitioning of H into the second-phase particles removes solute H from the matrix, hence preventing H embrittlement. Our insights further advance the mechanistic understanding of H-assisted embrittlement in Al alloys, emphasizing the role of H traps in minimizing cracking and guiding new alloy design.
Extensive experimental observations indicate the presence of nano-voids and the increase of free volume along the grain boundaries in hydrogen contaminated metals. This rate-dependent phenomenon motivates theoretical investigations of the underlying mechanisms. Here, a hydrogen enhanced cross-slip (HECS) mechanism in the close vicinity of the grain boundaries is demonstrated by direct molecular dynamics simulations. To this end, the interaction of the screw dislocations with a variety of symmetric tilt grain boundaries in H-charged and H-free bicrystalline nickel specimens is examined. The presence of segregated hydrogen atoms at the grain boundaries induces a stress field in their vicinity, and thus the barrier for cross-slip of screw dislocations considerably decreases. The enhanced crossslip of dislocations facilitates the formation of jogs. These jogs can form vacancies during the glide process. This mechanism shows nano-scale evidence of enhanced vacancy formation and subsequent increase in the free volume along the grain boundaries in the presence of H. This increase of the free-volume along the grain boundary dmaages the material and induce further embrittlement in addition to the direct effect of hydrogen in decreasing the fracture energy.
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.
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.
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.
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.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
Defect-hydrogen interaction in Al alloys: Challenges and benefits revealed by ab initio calculations
(2023)
Climate change motivates the search for light-weight materials for transportation and energy storage solutions. As one of the challenges, the deleterious effect of hydrogen on the mechanical properties of metallic alloys is known to reduce the applicability of metallic alloys, motivating the characterization and simulation of hydrogen-defect interactions in these materials. In this work, the interaction of hydrogen with planar defects in aluminium has been investigated by means of ab initio simulations.
On the one hand, two distinct types of GBs have been considered – the Σ11(113) [011] with a close-packed interface structure and the Σ5(210) [001] with a more open interface structure – in order to reveal the mechanisms governing the H segregation energetics. The investigations are afterwards extended to the impact of solutes in the Al alloy. Two scenarios are compared: Their segregation to the grain boundaries and their binding in precipitates. We therewith gained insights into the role of the solute size on the structural and chemical embrittlement in absence and presence of hydrogen. A thermodynamic assessment of the impact of solutes onto H chemisorption in the interfacial vicinity is provided by performing a high-throughput analysis for potential alloying candidates. The identified trends of the solute-H interactions are used to examine the relative importance of changes in hydrogen enhanced decohesion as a thermodynamic effect.
On the other hand, the interaction of hydrogen with defects can be beneficial for the formation of metal hydrides. To enhance the formation and stability of such often highly volatile hydrides we have consider a novel concept: tailoring and employing the negative pressure of microstructural and structural defects to enhance H solubility and thus hydride formation. Using systematic ab initio and atomistic simulations, we demonstrate that an enhancement in the formation of hydrides at the negatively pressurized crack tip region 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. Based on these insights we derive strategies for enhancing the capability of metals as H-storage materials.